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Volume 12, Number 1, 2013

ISSN 1945-8959

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Official Publication of the International Association for Cognitive

Education and Psychology

www.iacep-coged.org

Journal of Cognitive Education and PsychologyVolum

e 12, Num

ber 1, 2013


Editor

Marco G. P. Hessels, University of Geneva

AssociAtE Editor

Laura Berk, Illinois State University

EditoriAl BoArd

Fredi Büchel, University of Geneva

Sylvie Cèbe, University Blaise Pascal

Julian Elliott, Durham University

Douglas Fuchs, Vanderbilt University

Elena L. Grigorenko, Yale University

Yuriy V. Karpov, Touro College

Alex Kozulin, The International Center for Enhancement of Learning Potential

Zmira Mevarech, Bar Ilan University

Santiago Molina, University of Zaragoza

Jean-Louis Paour, University of Provence

Juan Pascual-Leone, York University

Wilma Resing, Leiden University

Carol Robinson-Zañartu, San Diego State University

Ursula Scharnhorst, Swiss Federal Institute for Vocational Education and Training

Robert Sternberg, Oklahoma State University

David Tzuriel, Bar-Ilan University

Karl H. Wiedl, University of Osnabrück

instructions for Authors

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SPECIAL ISSUE: WHAT IS COGNITIVE EDUCATION?Robert J. Sternberg and Marco G. P. Hessels, Editors

EDITORIAL

The CE of IACEP 3Marco G. P. Hessels

INTRODUCTION TO THE SPECIAL ISSUE

What Is Cognitive Education? 4Robert J. Sternberg

SPECIAL ISSUE ARTICLES

Cognitive Education: Constructivist Perspectives on Schooling, Assessment, and Clinical Applications 6

Jerry S. Carlson and Karl H. Wiedl

What Is Cognitive Education? The View From 30,000 Feet 26H. Carl Haywood

What Is Cognitive Education? 45Robert J. Sternberg

Mediated Learning Experience and Cognitive Modifiability 59David Tzuriel

Dynamic Testing and Individualized Instruction: Helpful in Cognitive Education? 81

Wilma C. M. Resing

Cognitive Education in the Digital Age: Bridging the Gap Between Theory and Practice 96

Adina Shamir

Current Views on Cognitive Education: A Critical Discussion and Future Perspectives 108

Marco G. P. Hessels and Christine Hessels-Schlatter

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Copyright © 2013 Springer Publishing Company, LLC, New York. ISSN 1945-8959

© 2013 Springer Publishing Company 3http://dx.doi.org/10.1891/1945-8959.12.1.3

Journal of Cognitive Education and PsychologyVolume 12, Number 1, 2013

From the Editor

The CE of IACEP

In this year’s first issue of the Journal of Cognitive Education and Psychology, we will dive right into the heart of the International Association for Cognitive Education and Psychology (IACEP). As you will have understood from the title of this short editorial,

our focus is on the CE of IACEP. According to the opening statement on the homepage of IACEP (http://www.ia-cep.org),

the International Association for Cognitive Education and Psychology “is a society of profes-sionals from throughout the world who are interested in advancing the cognitive education of children, youth, and adults.” Furthermore, we can read that its mission and purpose (http://www.ia-cep.org/about-us/mission) are, “through research and education:

• toadvancethecognitiveeducationofchildren,youth,andadults;• topromote,stimulateanddisseminateapplicationsofknowledgeonthedevelopment,

acquisition,andapplicationoflogicalthought;• toencourageandprovideopportunitiesfortheprofessionalgrowthofindividualmembers;• toinformthepublicaboutthepracticeofcognitiveeducation;• toadvancethestandardsofeducationandrelatedareas.”

The term “cognitive education,” the CE that is central to IACEP, is used relatively often in theseshortdescriptions,butitappearsdifficulttodefineoreventodescribewhatonethinksabout or understands when using it. For this reason, Robert Sternberg initiated the present specialissue“WhatisCognitiveEducation?”andaskedthecontributorstorespondtoaseriesof 5 questions. You will see that the invited contributions from the former, current and future president(s) of IACEP, who all responded from their own theoretical and research frame-works,provideaparticularlyvariedoverviewofthefieldofcognitiveeducation.Wehavetriedto bring these views together in our concluding integrative article. I hope that the richness of the contributions will further stimulate the scientific discussions about the importance of cognitive education for educational and remedial practice.

Marco G. P. Hessels Editor

4 © 2013 Springer Publishing Company http://dx.doi.org/10.1891/1945-8959.12.1.4


Introduction to the Special Issue

What Is Cognitive Education?

As my presidency of the International Association for Cognitive Education and Psy-chology (IACEP) was drawing to a close, I found myself pondering perhaps the most straightforward question any member of IACEP could ask himself or herself. What is

cognitive education? “Cognitive education” is in the name of the organization, so, I thought, we must know what it is. But after 2 years of presidency, I was not all so sure I was any closer to being able to answer the question than I had been when I started the presidency. I had my own views, of course, but were they idiosyncratic to me or were they shared? I decided to find out.

With the gracious support of the editor of the Journal of Cognitive Education and Psychol-ogy, Marco Hessels, and with the assent of the current president of IACEP, Wilma Resing, I undertook to edit this special issue on the topic “What Is Cognitive Education?” I could think of no question more basic to IACEP’s mission. Now the question was “whom to ask?” It seemed to me there was no group more appropriate than presidents of the organization, so I asked some past, present, and future presidents if they would kindly write for the spe-cial issue. Our current president, Wilma Resing, agreed, as did our president-elect, Adina Shamir. Happily, several past presidents also agreed, including Carl Haywood, Jerry Carlson, David Tzuriel, Karl Wiedl, and myself. Carlson and Wiedl collaborated on their article. So you will find in this special issue six main articles plus the concluding integrative comments by Christine Hessels-Schlatter and Marco Hessels.

I asked contributors to the special issue to address five questions:

1. What is cognitive education?2. How should it be done? How should it not be done?3. How should the effects of cognitive education be measured?4. What, if any, examples exist of successful programs?5. What recommendations do you have for cognitive education?

I was delighted that all of the contributors made a serious effort to address these questions. So my hope is that after reading this special issue, you will feel, as I now do, that you have a very good sense of different perspectives on the question of what is cognitive education as well as to the other questions posed previously.

Introduction 5

I think there has been no time in the history of our association when the question of what is cognitive education has been more important to society. We live in a time when education has not kept up with rapidly growing challenges to the world: global warming, wars, poverty, famines, overpopulation, disease, corruption, to name a few. Schools teaching in the mode of the 1800s—whereby students memorize material and spit it back—are not equal to the challenges that face the world today. Never has there been more of a need for creative, analyti-cal, practical, wisdom-based, and ethical thinking skills than there is today. If we do not start teaching students to think and learn better, the world is in trouble. I, for one, believe our very existence is at stake. So IACEP has an important mission to uphold, and that mission starts with the very basic question: “What is cognitive education?”

Enjoy and learn from our special issue!

Robert J. SternbergOklahoma State University



Special Issue Articles

Cognitive Education: Constructivist Perspectives on Schooling, Assessment,

and Clinical Applications

Jerry S. CarlsonUniversity of California, Riverside

Karl H. WiedlUniversity of Osnabrück, Germany

Our responses to the five questions concerning cognitive education that Robert Stern-berg raised focus on the school, the learner, and applications to clinical settings.

Considering the school and the learner, we emphasize constructivist theory and applications of learner-centered instructional and assessment approaches. Consider-ing applications to clinical settings, we focus on cognitive remediation and dynamic assessment (DA) approaches that address the impaired balance of cognitive level and task requirement for people with psychoses and other cognitive or developmental disorders. Emphasis is on the goal of including these persons into communities of learners that will be able to benefit from cognitive education.

Keywords: constructivism; schooling and clinical applications

When Robert Sternberg solicited contributions for the present issue of this journal, he suggested that the authors respond to five questions related to cognitive education:

1. What is cognitive education?2. How should it be done? How should it not be done?3. How should the effects of cognitive education be measured?4. What, if any, examples exist of successful programs?5. What recommendations do you have for cognitive education?

Cognitive Education: Constructivist Perspectives 7

Many of the issues raised by these questions were addressed in articles by Haywood (2010) and Feuerstein and Falk (2010) published in this journal. Our approach will focus on school-ing and on dynamic assessment (DA) and interventions in clinical settings.

WHAT IS COGNITIVE EDUCATION?

When one of us was preparing to leave for a meeting of the International Society for Cogni-tive Education and Psychology (IACEP), a neighbor, an attorney by trade, seemed bemused by the expression “cognitive education.” He asked, “Isn’t all education cognitive? What else could it be?” He had, of course, a point, but the answer depends on our understanding of the terms “education” and “cognitive.”

Formal education is typically represented by the curriculum of the school and generally reflects the educational purposes, goals, and expectations embedded in national and regional cultural histories and social/political contexts. The operational elements of the curriculum include what is taught, when it is taught, how and to whom it is taught, and how the results of learning are evaluated. Reflecting differing perspectives on learning and development, teach-ing approaches may range from emphasis on rote memorization and recitation to highly organized domain-specific learning sequences, guided discovery, and constructivism.

Figure 1 depicts a general representation of the complex relationships involved in school-ing. The interactions represented are dynamic. As perspectives on learning change, so may models of and approaches to teaching; as perspectives on what is considered important to know change, so may the subject matter content and methods of evaluating learning; and as perspectives on assessment of student progress change, so may the content of tests and the methods of testing.

We will approach the question of cognitive education by first summarizing the contri-butions of three individuals whose work made significant contributions to present-day per-spectives on schooling and the learner. We will then comment on aspects of cognitive and

FIGURE 1. Interactive relationships of formal schooling.

Interactive Relationships & Schooling

Schooling

Purposes

Curriculum

Teaching

The Learner

Cognitive

Affective

Cultural

Factors

Theories

Models

Philosophies

of Education

Culture,

History,

Circumstances

8 Carlson and Wiedl

educational psychology that inform our understanding of learning and cognitive change. Lastly, we will comment on the implications of cognitive education for assessment.

Three Major Contributors: John Dewey, Lev Vygotsky, and Jean Piaget

John Dewey (1859–1952). Although perhaps mainly thought of as a philosopher, John Dewey had a substantial impact on educational psychology, teaching, and the curriculum. Like other pragmatists, such as William James, Dewey did not consider ideas to be immutable, universal, or transcendent of human experience. He thought of them as instruments (hence the term in-strumentalism) for thought, for making conjectures, and for devising plans to solve problems.

For Dewey, learning begins with and is motivated by what he termed the “problematic situation.” This can be an event, a question, or a discrepancy that stimulates the learner’s curiosity and desire to find out and learn more. The activity of learning is through the pro-cesses of inquiry. Alone or in groups, the learner raises questions, frames and defines issues, and develops and tests hypotheses. The task of the educator is to provide the learner with the intellectual and emotional environment that will guide and stimulate disciplined and problem-solving–oriented thinking skills that may be applied widely, and provide the basis for the acquisition of domain-specific knowledge. The goal is to expand the learner’s interests and motivation for further learning and discovery (see, Dewey, 1938/1963, 1987; Dewey & Dewey, 1915; McClellan & Dewey, 1889).

Dewey’s impact on education began after he took a position in philosophy at the Uni-versity of Chicago and founded the Dewey Laboratory School where he could apply his educational philosophy and explore new applications for curriculum and teaching method-ologies. Dewey recognized that the educator must be aware of what children bring to school and the learning situation, that is, their interests, motivations, and knowledge. They are not blank slates. The inquiry model of learning that Dewey advocated for teachers was “to ‘psy-chologize’ the curriculum by ‘constructivizing’ an environment in which the activities of the child would include problematic situations that call on their knowledge and skills to learn how to solve problems and advance their own knowledge” (Westbrook, 1993, p. 285).

Dewey’s legacy is reflected in curricula as well as in models of learning and teaching. For example, in his widely used book, Educational Psychology, Cronbach (1992) took a decidedly Deweyian perspective on learning and inquiry. He credits Dewey’s writings for his own po-sition on learning and the “seven elements of learning” that, as Cronbach put it, “express a miniature theory of learning.”

1. Situation: The situation consists of all the objects, persons, and symbols of the learner’s environment.

2. Personal characteristics: All the abilities and all the typical responses that the person brings to the situation.

3. Goal: The goal of the learner is some consequence (i.e., state of affairs) that he or she wishes to attain.

4. Interpretation: Interpretation is a process of directing attention to parts of the situa-tion, relating observations to past experiences, and predicting what can be expected to happen if various actions are taken.

5. Action: The person’s actions include movement and statements; they are observable responses.


6. Consequences: Confirmation or contradiction. Some events that follow the action are regarded by the learner as consequences of it.

7. Reaction to thwarting: Adaptive or nonadaptive. Thwarting occurs when the person fails to attain a goal.

Lev Vygotsky (1896–1934). Like Dewey, Vygotsky described learning from a pragmatist perspective and stressed the importance of social and cultural relationships that engage the learner and deepen thinking and reflection. The dynamics of and motivations for learning are fundamentally rooted in the child’s social, cultural, and personal history and interactions with significant others and events in his or her environment. As did Dewey, Vygotsky stressed the dialectical nature of learning and the construction of knowledge.

Individuals’ cultural and social history and interactions serve to develop what Vygotsky called symbolic psychological “tools” that may be thought of as mediators for thought and schematized, self-regulated intellectual development. Learning occurs when there is a dis-crepancy between what is taught and the level of development at a given time. As Vygotsky put it, learning is “in advance of development” (Vygotsky, 1978/1930, p. 56). The task of the teacher then is “to make it possible for the child to internalize external knowledge and convert it into a tool for conscious control” (Bruner, 1985). (See also Karpov & Bransford, 1995; Kozu-lin, 1998; Kozulin & Presseisen, 1995 for elaboration of this perspective.)

Although criticized for misapplication of Vygotskian thought to education by some (P. Griffin & Cole, 1999; Tudge & Scrimsher, 2003), several cognitive psychologists and edu-cationists relate Vygotsky’s zone of proximal development concept to scaffolding (Bransford, Brown, & Cocking, 2000; Bruner, 1985; Puntambekar & Hübscher, 2005; Rohrkemper, 1989; Wood, Bruner, & Ross, 1976).

Vygotsky’s zone of proximal development provides a theoretical as well as a practical framework for scaffolding and assessment. The central idea is that assistance can be provided to learners that is sensitive to the learner’s initial level of knowledge and will systematically structure (scaffold) the interactions with the learner that will lead to higher levels of knowl-edge and tools for goal-directed learning. It is a dialectical process, not a recipe book, and can include interactive prompts, response-based aid, graduated assistance, peer interactions, and ongoing assessment of progress.

Perhaps the best known and most widely applied application of Vygotskian principles to education are the mediated learning experience (MLE) project developed by Feuerstein, Rand, Hoffman, and Miller (1980) and the learning potential assessment device (LPAD) developed by Feuerstein, Rand, and Hoffman (1979). The essential principles of MLE are (a) to ascertain the cognitive tools involved in the cognitive processes that lead to learning in various areas and (b) to provide the learner with experiences that will facilitate the development of the cog-nitive processes that are useful to that learning. The program emphasizes three important aspects of the mediation/learning process: focusing on the learner’s needs (“intentionality”), being attentive to the learner’s responses (“reciprocity”), and going beyond the present level of development of the learner. The LPAD consists of paper-and-pencil tests constructed to be independent from academic learning or specific school-related prior knowledge. The goal is to (a) assess the learner’s present level of cognitive functioning, (b) determine potential cognitive modifiability, and (c) ascertain the type of mediational program that would be most effective for the learner. The tests are often administered with a fairly commonly used DA test-mediate-retest format.

10 Carlson and Wiedl

Jean Piaget (1891–1980). Piaget’s writings were largely unnoticed in the United States until the publication of John Flavell’s The Developmental Psychology of Jean Piaget published in 1963. As Piaget offered new insights into the structure of the intellect, information process-ing, and memory, philosophies of curriculum changed, as did teaching and assessment meth-odologies (see Bruner, 1966; Furth, 1970; Sigel, 1979). The renewed interest in developmental psychology, particularly cognitive development, motivated educators and educational psychol-ogists to rethink the assumptions guiding their perspectives on learning (Cronbach, 1964; Karplus, 1979; Renner, Abraham, & Bernie, 1986).

According to Piaget’s developmental theory, learners, regardless of age, interpret objects and events within the bounds of their physical (biological) and environmental (social) con-straints. In Piagetian, as well as Vygotskian and Deweyian theory, optimal learning occurs when there is “a match” between the child’s cognitive level and instruction. Whether in Piag-etian terms of assimilation-accommodation or Vygotskian terms of the zone of proximal de-velopment, new learning begins with what one already knows, perceives, and reacts to, that is, what one knows shapes what is perceived and provides the basis for further learning and development. This general principle has been incorporated into neoPiagetian theory. Two examples are Fischer’s skills theory (Fischer, 1980) and Case’s emphasis on executive control and what he terms “central conceptual structures” (Case, 1985; Case & Griffin, 1990).

Somewhat similarly to Cronbach’s “miniature theory of learning,” Case (1985) viewed learning as a process of constructing what he called “conceptual bridges.” Building concep-tual bridges involves the following five steps:

1. Knowing what a given learner understands about the subject at hand.2. Knowing what knowledge the teacher wants the learner to construct and which aspects

of this knowledge lie just beyond the present level of understanding but within the learner’s zone of proximal development.

3. Providing carefully crafted learning materials and opportunities for the learner to “cross the bridge” and construct the target knowledge.

4. Helping the learner make the passage (scaffolding).5. Constantly shifting the “bridge” to accommodate to the learner’s growing knowledge

(from Griffin & Case, 1997).

Constructivism

One of the most influential perspectives in educational philosophy, with direct influence on cur-riculum, teaching, and the learner, is constructivism. Constructivism is not a unitary concept. It is a “fuzzy” concept, with neither a single agreed-upon definition nor a unitary set of epistemo-logical assumptions or educational claims (see Phillips, 1997). Being a “big tent” term, construc-tivism includes different models of cognitive development, learning, and thinking, each of which can be located between nonconstructivist poles. At one pole is psychological nativism, which is based mainly on evolutionary and genetically based models; at the other pole is radical behavior-ism, based largely on principles of operant conditioning and reinforcement contingencies.

Within the constructivist framework, psychological constructivists emphasize how individuals come to possess knowledge; social constructivists emphasize social communities. Regardless of emphasis, constructivist theories agree with the premise that new knowledge is based on what the learner already knows and believes (Bransford, Brown, & Cocking, 2000). Learning is not


passive assimilation or rote memorization; it is based on the affordances that engaged participa-tion with instructional materials and participation in interactive environments. Constructivist teaching approaches emphasize inquiry training, not memorization of facts (Hunt, 1997).

Cognitive constructivists assume that learning is intrinsically motivated and based on the dis-crepancy between new information and information that has already been assimilated. The natu-ral tendency for the learner is to make cognitive accommodations to reduce cognitive conflict. That is one reason why instructional approaches that use discovery learning are effective. The challenge for the educator is to present the learner with unexpected outcomes that will be optimally chal-lenging to the learner’s already developed schema of the way things are supposed to be.

Constructivistic models differ in emphasis and implication for instruction. Piagetians emphasize the individual’s relationship to the external world and the logical bases of thinking and mental processes involved in intellectual development. Vygotskians emphasize the indi-vidual’s relationship with the environment and the social and cultural categories and affor-dances it supplies. Information processing emphasizes concept acquisition mainly through identifiable cognitive processes such as memory, storage, and retrieval processes of domain-specific knowledge and inquiry skills.

Figure 2 depicts four constructivist models. Although they vary in emphasis on individual cognitive or social processes, they share the general perspective that learning is an active, prob-ing, constructing process. As Donald Norman puts it, “Students interpret. They overinterpret. They actively struggle to impose meaning and structure” (Norman, 1980, p. 89). Although it does not necessarily follow that educational policy, be it curricular or classroom instruction, fol-lows unproblematically from psychological theories and philosophical and epistemological as-sumptions, constructivism as a general principle is theoretically sound and practically relevant.

Cognitive Education and Assessment

Assessment in Schools. Student learning and effectiveness of instruction is often measured through summative assessment procedures. These can be end-of-chapter or instructional unit tests that may be used for grading purposes, or they may be standardized tests that may be administered at the school district, state, or national level and used for accountability indices

FIGURE 2. Comparisons of four models. Adapted from Prawat, R. S. (1997). Constructivist ontologies: The rest of the story. Issues in Education: Contributions from Educational Psychology, 3, 235–244.

What How Where When Why Epistemology

InformationProcessing

Frames orformats

Successiveprocessing

In headInput enters

system

To use environmental

affordancesRealist

PiagetLogical

structuresIntegration anddifferentiaton

In headDisequilibrium

occursTo adapt to theenvironment

Rationalist

VygotskyPsychological

tools

Appropriationfrom more

expert other

Between expert and

novice

Sharedproblem arises

To engage inefficient joint

actionPragmatist

Dewey IdeasSemiotic process

Between mind and

world

Sense ofdeeper

meaning arises

To wrest orderfrom a disorderly

universePragmatist


for schools and effectiveness of instruction in meeting curricula and content standards. The tests results represent a “point-in-time” index of achievement that provides little information about learning processes or potentially useful interventions. (For a critical review of standard-ized, high-stakes testing in the United States, see Paris, 2000).

In contrast to summative assessment, formative assessment is incorporated into classroom instructional sequences and informs both the teacher and students about progress or problems in learning. The purpose of formative assessment is to promote learning and guide instruction; its validity is assessed by “how effectively learning takes place in subsequent instruction” (Heri-tage, 2007). By providing feedback, formative assessment gives students the opportunity to re-flect on, revise, and elaborate on previous learning, which can be used as a “bridge” to further learning and, potentially, transfer. It can also be useful for improving instruction, sequencing of material, and emphasizing the educational goal that learning is for understanding.

An important aspect of formative assessment is that it drives self-regulated learning and the dynamic processes that involve the cognitive, metacognitive, and motivational strategies that the learner uses to develop and employ learning strategies. The process is consistent with Dewey’s notion of the active learner as well as social cognitive theory represented in Vygotsky’s writings and the work of several contemporary psychologists, for example, Cole (1996), Rogoff (2003), and Schunk and Zimmerman (1997). It is also consistent with Bandura’s (1986) con-cept of reciprocal determinism, that is, where individuals internalize cognitive, metacogni-tive, and tacit knowledge as well as motivation and the ability to reflect on their own thinking processes. (For a detailed review of formative assessment, see Clark, 2012).

Dynamic Assessment. Although varied in purpose, method, and outcome, DA approaches share several common assumptions. First, is the notion of cognitive modifiability; second, is that performance does not necessarily accurately reflect the cognitive competence of the indi-vidual tested; third, is that assessment approaches that involve interactions between the tester and the person tested can provide insight into the individual’s cognitive capacity as well as fac-tors that may facilitate development of new and more efficient cognitive activities; and fourth, is that fostering and evaluating developing abilities is important for accurate assessment of cognitive capacity and learning potential (see Haywood, 2001; Haywood & Lidz, 2007).

DA is based on models of cognitive development and change. Although there are different models, DA procedures usually employ a test-intervention-test paradigm, with the interven-tion focusing on the learner’s responsiveness or potential responsiveness to the mediation. At one level, it is similar to the interactive approach Piaget employed to determine levels of cognitive development. It is also similar to response-to-intervention (RTI) approaches that blend assessment and intervention to aid in determining potential success of learners to in-structional programs. As Grigorenko (2009) suggested, both DA and RTI “belong to one fam-ily of methodologies in psychology and education whose key feature is blending assessment and intervention into one holistic activity” (p. 114; see also Bransford, Delclose, Vye, Burns, & Hasselbring, 1987).

Knowledge of learning potential is important to guide instructional strategies and ap-proaches. Advocates of DA claim alternative, interactive approaches to mental ability testing can reduce false negatives and generally provide not only more accurate information about an individual’s cognitive abilities than standard, static testing approaches but also substantial evi-dence about effective teaching approaches (Robinson-Zanartu & Carlson, 2013). (For an over-view, see Haywood & Tzuriel, 1992; Haywood & Wingenfeld, 1992; Lidz, 1987; Lidz & Elliott, 2000; Sternberg & Grigorenko, 2001 accompanied by critical commentary from eight authors.)


Clinical Aspects of Dynamic Assessment. We pointed to individual and group differences that may affect learning, learning potential, and the valid assessment of ability and potential, thus justifying the development of alternative approaches of teaching and assessment. This issue is particularly significant when we consider individuals with mental disorders and dis-turbances. Epidemiological research shows lifetime prevalence rates of such individuals to be up to 50% for adults (18–65 years) and of about 20% for children and adolescents (Wittchen & Jacobi, 2005; Wittchen, Nelson, & Lachner, 1998).

Clinical research targeting cognitive variables indicates that various mental disorders are more or less related to neurocognitive dysfunctions. The implication of these data is that there is temporary or permanent impairment of learning and learning potential for a substan-tial part of the population. Avoiding false negatives for these persons, not only in the school system but also in systems of relearning or supplementary and adapted learning, is a specific challenge for assessment in this field of instruction and training. DA provides useful method-ologies for meeting this challenge because special groups of persons are often not adequately assessed by static conventional testing (Haywood & Lidz, 2007).

Summary: What Is Cognitive Education?

In our view, there is no single answer to this question. But consideration should be given to the following principles because they concern instruction and learning.

The School, Instruction, and the Learner. Cognitive education is learner and knowledge centered. This suggests awareness of and accommodation to cultural, social, cognitive, and personal factors that affect learning, learning potential, and the motivation to learn. It also suggests that the structure of the domain or area of instruction be clearly understood and reflected in educational goals and instructional strategies. Cognitive education is inquiry based and constructivist, facilitating the development of cognitive and metacognitive pro-cesses that guide further learning and deepen contextual knowledge that facilitates recall and applications of the acquired knowledge. Cognitive education provides the learner with the opportunity to be aware of his or her learning and develop insights that guide self-motivated and self-aware learning. Cognitive education uses assessment as a tool, a part of instruction, not a final “scorecard.” It assesses the quality of thinking in response to instructional goals.

Clinical Aspects. Following Dewey, Vygotsky, and Piaget, optimal learning requires a match between the learner’s cognitive level and instruction. This is of special importance to clinical groups because the match very often gets out of balance. Disorders where this phe-nomenon is well known are psychoses as well as developmental and cognitive disorders. For persons belonging to these diagnostic categories, various methods of remediation that help readjust the balance by matching the cognitive and instructional levels should be included under the label of cognitive education. This and adequate cognitive assessment will serve the goal of inclusion of these persons into the community of human learners that undergo cognitive education.

HOW SHOULD COGNITIVE EDUCATION BE DONE?

The School, Instruction, and the Learner

The answer to this question is anticipated in the response to the first question. The domains of instruction, the ages and characteristics of the learners, as well as the general educational


goals of the school and the society all effect the what, where, when, and how of schooling. This said, the general principles of how cognitive education should be done include the following:

1. Educational practices should be based on sound theory and empirically supported evi-dence. This does not mean that there is or can be one model of cognitive education. It does mean that a framework for a coherent but not static model of cognitive educa-tion is necessary for systematic developments and revisions in the field.

2. The learner should be aware of his or her prior knowledge and understandings. Recip-rocal teaching and other interactive strategies are useful to help provide these insights.

3. In learning-centered environments, emphasize mastery over performance goal learning.4. Emphasize instructional approaches such as reciprocal teaching that support

self-monitoring, metacognition, and self-assessment and emphasize “think-aloud” and the self-guidance function of overt and covert verbalization.

5. Support learning through assessment. This includes formative as well as DA.

Clinical Aspects

The match between cognitive level and task requirements has to be conceived based on these cognitive functions that hinder matching. For example, individuals with schizophrenia seem to have special problems with processing negative feedback, of set shifting, and of response inhibition (Pedersen et al., 2012). In addition, it has been demonstrated that these individuals have problems with metacognition (Lysaker et al., 2011). For the remediation of these kinds of impaired cognitive function(s), two strategies of intervention have been demonstrated to be useful: In case of sufficient modifiability of the impaired function, DA procedures that involve special functional training can be applied to facilitate subsequent interventions. An example of this is psychoeducation, particularly involving vocational training, skills train-ing, and cognitive remediation. Given a low degree of cognitive modifiability when applying available functional training, modification of the learning context and techniques are neces-sary. We (Carlson & Wiedl, 2000) termed these strategies “modification” and “compensation” and discussed them within a complex framework of assessment and intervention.

HOW SHOULD THE EFFECTS BE MEASURED?

The School, Instruction, and the Learner

The effects of instruction and schooling should be measured along two continua: (a) the knowledge gained by the learner and (b) the ability of the learner to apply that knowledge. The former includes factual and conceptual knowledge; the latter includes procedural knowledge and a host of cognitive and metacognitive activities.

The effects of DA should also be measured along two continua: (a) responsiveness to the intervention and (b) the durability and generalizability of the response.

Clinical Aspects

Effects of cognitive interventions in the clinical field are usually evaluated with the help of conventional tests of cognitive performance and functioning and shall therefore not be given special consideration in this section.


Regarding DA, to date, there is no tradition in applying measures of DA to assess the effects of cognitive education. The application of DA would make sense, however, when specific aspects of cognitive education can be related to certain methods of DA. For instance, if the goal of a cognitive education program is to help learners focus their attention on feedback and instruction, a candidate for evaluating this program could be a testing-the-limits approach used with the Raven Coloured Progressive Matrices by Carl-son and Wiedl (1979) for normally developed children or of a dynamic version of the Wis-consin Card Sorting Test (WCST) for persons with (a diagnosis of) schizophrenia (Wiedl, 1999). In both cases, the processes of trial-by-trial verbal feedback are the focal mediator of the effects which can be assessed not only on the level of performance but also on process level (eye tracking; Bethge, Carlson, & Wiedl, 1982; see also Hessels, Vanderlin-den, & Rojas, 2011) and via neurophysiological patterns of activation and compensation (Pedersen et al., 2012).

Consistent with the goals for both schooling and rehabilitation, effects should also be measurable at the level of far transfer. This could be achieved with the help of behavioral rat-ing scales. An example of this are the scales of the Osnabruck Working Capabilities Profile (O-AFP; Wiedl, Uhlhorn, & Jöns, 2004). One of these scales assesses “learning ability at the work place” and is related to training via near transfer measures assessed with a measure of DA (WCST-Dynamic; Wiedl, Kemper, Uhlhorn, & Schöttke, 2005).

WHAT, IF ANY, EXAMPLES OF SUCCESSFUL PROGRAMS EXIST?

The School

It is not in the purview of this article to describe them, but there are several curricular pro-grams and instructional approaches that are excellent. Some of them have been developed by past and present members of the IACEP. See for example, Haywood, Brooks, and Burns (1992) for descriptions of the Bright Start curriculum for young children; or Klein (1996) for descriptions of mediational programs for children from different cultures; or Carlson and Das (1997); Das (2009); and Das, Georgiou, and Janzen (2008) for applications of a cog-nitively based reading program for elementary school-age children based on the planning, attention, simultaneous, and successive (PASS) theory of intelligence (Das, Naglieri, & Kirby, 1994); or Greenberg (2000) for teaching cognitive enrichment programs to young children; or Sternberg, Jarvin, and Grigorenko (2009) for their work with the wisdom, intelligence, cre-ativity, and success (WICS) program and extending the model to K-12 classroom instruction and assessment; and Missiuna and Samuels (1989) for descriptions of cognitive education applied to preschool children with severe learning difficulties.

In their 2005 book, How Students Learn: History, Mathematics, and Science in the Classroom, John Bransford and M. Suzanne Donovan point out that learners’ preconceptions of phenom-ena are tenacious, often difficult to change but necessary to address. As we suggested in our discussion of Dewey, Piaget, and Vygotsky, the learner brings knowledge with him or her to the learning situation. Knowledge in the Piagetian sense may be largely related to cognitive developmental processes or, closer to Vygotsky, it may be mainly a function of prior, cultur-ally mediated, learning. Regardless of focus, learning involves cognitive reorganization and conceptual change.

Some programs, such as Bright Start (Haywood et al., 1992), successfully focus on cogni-tive functions that affect learning across domains. Our purpose is to provide a few examples


of successful domain-specific programs in early mathematics learning and science. The goals and accomplishments of each program meet the following criteria:

1. Taking into consideration students’ prior knowledge (conceptions and misconceptions) and relating new concepts to previous knowledge

2. Providing learning situations that are student focused and activity based3. Focusing on learners integrating their knowledge into broader conceptual systems4. Fostering in the learners’ understanding of their own processes of learning

Early Mathematics. Douglas Clements and Julie Sarama have developed a useful and in-tegrated approach to early mathematics education. Their central focus is how young learners can be guided through increasingly sophisticated levels of mathematical knowledge. To ac-complish this, they developed research-based and pedagogically applicable learning trajecto-ries aimed at attaining specific learning goals. Learning trajectories include developmental progressions of subgoals and instructional tasks that provide learning experiences that foster students’ thinking. Instructional approaches include peer tutoring and reciprocal teaching with emphasis on formative assessment and fostering the ability of students to reflect on and critique their own problem-solving strategies. Instructional activities include physical as well as computer manipulatives.

Details of Clements and Sarama’s view on and approaches to teaching elementary math-ematics can be found in several publications. In both Clements and Sarama (2009, 2012), they describe their approach in detail, specifically learning mathematics, teaching mathematics, and learning to teach mathematics. Learning mathematics explores the question of how stu-dents learn mathematics, that is, what do we know about the cognitive and affective aspects of learning that can guide teaching practices and curriculum development. Teaching math-ematics provides a review of the literature and draws conclusions about what instructional approaches are supported by research. Learning to teach mathematics offers “best practices approaches” for teacher training and in-service programs.

Case (1985, 1988) described children’s intellectual development in terms of conceptual structures and cognitive networks that represent core knowledge in a domain. Consistent with Piagetian theory, Case’s model of central conceptual structures was applied to early mathematics instruction and learning by Case and Griffin (1990). They extended their work to include a developmental approach to “everyday” mathematics learning (Griffin, Case, & Sandieson, 1988) and to applications for teaching and elementary mathematics curriculum (Griffin & Case, 1996; Griffin, Case, & Capodilupo, 1995).

The early mathematics curriculum developed by Case and Griffin (1990) is inclusive and effective. Learning objectives are clearly spelled out as are the tools for assessing stu-dents’ mathematical knowledge. The Number Worlds program developed for early learning ( kindergarten) teaches the implicit and explicit mathematical knowledge that their and other research has shown to be useful for later learning. The program is child centered and empha-sizes hands-on activities with the learners constructing their knowledge.

For details, see Griffin (2004); Griffin and Case (1997); and Griffin, Case, and Siegler (1994). For other effective “cognitive” approaches to early mathematics learning, see Carpenter, Fennema, Franke, Levi, and Empson (1999) and Baroody and Coslick (1998).

Physical Science. In their chapter on science education in the Handbook of Educational Psychology, Second Edition, Linn and Eylon (2006) underscore the significance of


constructivism in science learning and the importance of instructional approaches designed to assess and foster the development of student-formulated ideas. The facet-based instruction program developed by Minstrell and Hunt (1996) focuses on just that: the conceptions and misconceptions that high school students have about elementary physics and physical phe-nomena and using an instructional program designed to “breach the gap” between naive and incorrect perspectives to perspectives of greater accuracy and sophistication. The program comprises four parts: (a) a preinstruction quiz to establish for the student as well as the in-structor the student’s level of knowledge, (b) a “benchmark” lesson, (c) experimentation, and (d) assessment.

Students’ notions of elementary physics (or any area in science) are represented by what Hunt and Minstrell (1996) call facets: “often reasonable interpretations of local situations, with-out necessarily being part of a consistent picture of general laws” (p. 130). The “benchmark” lesson presents scientific problems (in this case from physics) that the students discuss, pre-dict answers for, and rationales for their answers. The solutions to or representation of the principles are demonstrated, and the students discuss their interpretations and how the new information informs their original thinking. Depending on the principles/problems dealt with and the level of sophistication the students have achieved further instruction and laboratory work may be done.

The goal of instruction is to develop students’ knowledge to conform to the scientific prin-ciples studied, be self-aware of this development, and be able to more accurately represent the principles involved. Comparative studies consistently show the efficacy of facet-based instruction in general knowledge of the scientific principles taught, higher performance on standardized state assessment tests, and more sophisticated scientific reasoning. For details, see Hunt and Minstrell (1994, 1996); Minstrell, (1989); and Minstrell and Stimpson (1996).

Clinical Applications and Dynamic Assessment

Corresponding with the boom of research in cognitive psychology and the cognitive per-spective in clinical psychology, various developments or programs were published since the 1990s. We will briefly present some successful examples of DA for individuals with diagnoses of psychosis, cognitive disorders, and/or developmental disorders.

Psychoses. Most programs were developed for schizophrenia but are usually applicable to other psychotic disorders as well, targeting various domains of dysfunctions.

Programs applying principles of “errorless learning” focus on breaking down complex tasks into small units, which are successively taught and trained with the goal of minimiz-ing negative feedback (Kern, Liberman, Kopelowicz, Mintz, & Green, 2002). The application of this approach proved successful not only for academic tasks but also for the organization of vocational training in various domains within rehabilitation settings for persons with the diagnosis of schizophrenia.

Programs teaching problem solving are basic to many rehabilitation programs. The pro-grams of the social and independent living skills (SILS) series (Liberman & Wallace, 1992) have been well evaluated. The focus of these programs involves training of formal problem solving connected to various modules of teaching everyday living skills.

Metacognition. Moritz, Veckenstedt, Randjbar, and Vitzthum (2011) developed a program for modifying metacognitive dysfunctions which are considered risk factors for the development of psychotic symptoms. The approach addresses attributional style, jumping to conclusions, the


bias against disconfirming evidence, and aspects of theory of mind and empathy. The program is available as a group program in different languages in the Internet (www.uke.de/mkt).

Integrative Approaches. The integrative psychotherapy program (IPT) was developed by Brenner, Roder, Hodel, and Kienzle (1994) and brings together modules of basic cognitive training (cognitive differentiation, social perception) with modules of communication, so-cial skills, and social problem-solving training within one comprehensive treatment. It has gained wide acceptance and is being used in several countries (see Roder, Zorn, Andres, Pfammatter, & Brenner, 2002).

Compensation. In a program developed by Wiedl (1997) designed to improve coping with schizophrenia, the principle of compensation is systematically applied. The learning context and methodology is modified and adapted in a way, which at least partly neutralizes neurocog-nitive impairments (attention, memory, executive processes) of patients with schizophrenia to maximize their potential to profit from psychoeducation and rehabilitation training.

Dynamic Assessment. DA for people with psychosis was introduced into clinical research by Wiedl (1999) for the assessment of executive and memory functions. It has been applied in several studies by different researchers. These include studies of construct validity (Wiedl, Schöttke, Green, & Nuechterlein, 2004), including the level of neurophysiological activation (Pedersen, Wiedl, & Ohrmann 2009; Pedersen et al., 2012), and short- and long-term predic-tions of criteria of rehabilitation in the context of different methods of rehabilitation training (Sergi, Kern, Mintz, & Green, 2005; Watzke, Brieger, Kuss, Schoettke, & Wiedl, 2008 ).

Cognitive Disorders. Two target groups have attracted special interest for developing methods of intervention and assessment: the older adults and children and adolescents with learning difficulties.

Focusing on older adults, Calero and Navarro (2006) employed the research paradigm es-tablished by Paul Baltes (Baltes, Staudinger, & Lindenberger, 1999) to investigate the concept of cognitive plasticity as a mediator for the effects of memory training within a group format. They found evidence for the moderating effects of activity and style of living regarding plas-ticity and the maintenance of training gains (Calero, Navarro, & Munoz, 2007). Along with their training procedures, Calero (2012) and Navarro and Calero (2009) developed or adapted various methods of testing for the DA of cognitive plasticity.

Focusing on persons with learning difficulties, Hessels and Hessels-Schlatter (2008) and their colleagues developed interventions with four target constructs: metacognition, induc-tive reasoning, executive control, and metacognitive awareness. Training included principles of guided prompting and compensation. The implementation of the intervention is particu-larly relevant for special education. Its special approach lies in the complementary training of the basic cognitive capabilities using both curriculum-related and curriculum-unrelated tasks (Bosson et al., 2010; Hessels, Hessels-Schlatter, Bosson, & Balli, 2009).

Related to the latter issue is the use and adaptation of games for developing basic cogni-tive capabilities (Hessels & Hessels-Schlatter, 2008). Besides the effects of these interventions on the specific target variables, it can be assumed that the principles of the intervention apply to persons with severe learning difficulties to facilitate their understanding the world around them, thus contributing to the inclusion of these people in the society (Hessels & Hessels-Schlatter, 2008).

Besides the approaches for people with diagnoses of psychosis and with severe learn-ing problems, subgroups of persons with developmental disorders such as Asperger syndrome are gaining increasing interest regarding cognitive education and cognitive


remediation, including strategies of DA (Haywood & Lidz, 2007). First studies indicate the relevance of the context of assessment and remediation in terms of minimizing fail-ures (Donaldson & Olswang, 2007) and the use of methods of DA for assessing cognitive potential in children with Asperger syndrome (Bonete, Vives, Fernándes-Parra, Calero, & Garcia-Martin, 2010).

Finally, we want to point to two developments in the field of DA which are of increas-ing practical and theoretical significance. The first relates to the worldwide phenomenon of migration, in particular to special issues of assessment and education of migrant chil-dren. Accumulating research shows that DA is effective for improving the validity of as-sessment by avoiding false negatives and thus providing fair assessment for these children (Hessels, 2000; Resing, Tunteler, de Jong, & Bosma, 2009). The second is relevant for DA in general: The possibility of identifying and measuring “online” the cognitive processes which are involved in performance and learning with the help of special, computerized pro-cedures of DA using tangible electronics (Resing & Elliott, 2011). This kind of innovative theory-guided methodology promises to offer helpful solutions to bridge the gap between assessment and learning.

WHAT RECOMMENDATIONS DO YOU HAVE FOR COGNITIVE EDUCATION?

Schools

Effective teacher education is essential for successful cognitive education. Two types of knowl-edge are necessary: domain and pedagogical knowledge, which Shulman (1986, 1987) termed pedagogical content knowledge. To foster and develop this type of knowledge, teacher education should be an ongoing process implemented by leadership at the school, district, and state levels. This is relevant for all levels of instruction, particularly in mathematics and science.

Organizations committed to cognitive education, such as the IACEP, might explore the potential of relationships with professional organizations that focus on teaching in particular domains such as science education, mathematics education, reading, history, and social stud-ies education.

Efforts should be made to expand the use of appropriate DA and testing-the-limits ap-proaches by school psychologists and teachers as is done in the special education teaching program at Geneva University (see Hessels, 2009).

Clinical Applications and Developments in Dynamic Assessment

Practitioners should take into account the great variety of “cognitive needs” for interventions and possible targeted approaches, depending on the specific clinical problems in the single case or in clinical subgroups, reaching from errorless learning and the cognitive remediation of specific functions to metacognitive processes and components of theory of mind.

Cognitive education should be related to everyday learning. An example of this is sup-ported employment where cognitive remediation is tied to regular work activity (Bell, Zito, Groig, & Wexler, 2008). Cognitive education should not only target (impaired) functions or variables but should also address the person as a whole. This would increase the salience of concepts such as self-esteem and autonomy, self-determination and self-reflectivity, and expertise.


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Correspondence regarding this article should be directed to Prof. Dr. Jerry S. Carlson, 219 Nisbet Way, Riverside, CA 92507. E-mail: [email protected]



What Is Cognitive Education? The View From 30,000 Feet

H. Carl HaywoodVanderbilt University, Nashville, TN

Cognitive education is defined and described according to aspects that are common to various curricula and programs as well as aspects that vary across programs. Its most basic and universal characteristic is its focus on processes of systematic logi-cal thinking and especially the application of basic tools of learning. The application of fundamental cognitive and metacognitive concepts in teaching and learning is described with examples. Selected curricula, programs, and approaches are listed and briefly characterized. Criteria for evaluating cognitive education programs are proposed, and some examples of successful evaluation strategies are given. Evalua-tion of effectiveness across different cognitive education programs shows effects on cognitive development, IQ, school achievement, intrinsic motivation, and reductions in referral to special education, although such effects depend on age of learners, spe-cific program characteristics, and effectiveness criteria.

Keywords: cognitive education; metacognition; evaluation; learning; thinking skills

The term cognitive education has been in professional use for only about 30–40 years, but the notions that underlie the term are as old as education itself. My own first published use of the term and the first that I can find is in a paper on cognitive edu-

cation with adolescents who had learning disabilities (Arbitman-Smith & Haywood, 1980). In that paper, it referred specifically to application of Instrumental Enrichment (Feuerstein, Rand, Falk, & Feuerstein, 2006; Feuerstein, Rand, Hoffman, & Miller, 1980) in classroom settings, but the authors’ intent was to see that program as a sample of the domain of educational approaches that would share certain common characteristics. In the ensuing years, psychologists and educators have come to agree on at least some of those common characteristics. In this article, I offer a view of what is commonly accepted as defining characteristics of cognitive approaches in education and what characteristics vary across programs and curricula, some suggestions on selecting and evaluating cognitive education programs, an illustrative list of available programs of cognitive education, and a brief sum-mary of their demonstrated effects.

There has always been a creative tension among philosophers of education for whom the overriding goal is to expand and enrich learners’ abilities to think systematically and effectively

What Is Cognition Education? 27

and those for whom the goal is to impart a defined body of knowledge ( Aristotle, ca. 344 BCE; see Brumbaugh & Lawrence, 1959; Cahn, 2009). Indeed, the very nature of knowledge itself has been and remains a subject of intense thought and investigation (Plato, ca. 370 BCE; ca. 380 BCE; see Cahn, 2009), as demonstrated in our time by the long and distinguished career of epistemologist Jean Piaget (e.g., Piaget, 1950). Springing from philosophical inquiry into the nature of knowledge, there is the very practical inquiry into the processes by which knowl-edge is acquired, elaborated, related to other knowledge, stored, applied, and evaluated. That discussion bridges the disciplines of genetic (i.e., developmental) epistemology, developmen-tal psychology, and cognitive science and reaches well into the applied discipline of education as well as such applications as speech and language therapy and even psychotherapy.

Just more than one century ago, Western educational philosophy was engaged in a con-troversy regarding appropriate educational curricula (much as we are today). “Classical” education, with its emphasis on classical studies, philosophy, mathematics, natural sciences, and theology, was increasingly criticized as irrelevant to the demands of modern civilization, which seemed to call for greater emphasis on practical and technical studies whose mastery could extend the technical advances of the industrial age. Classical education was defended by a group known as the “formal disciplinarians,” who held that how one studied and acquired knowledge was more important than what one studied, and further that certain subjects, such as the Latin and Greek languages and mathematics, held the ability to promote the kind of study and learning that could be generalized to many other fields of study. Henderson (1911) described it in this way:

We may distinguish, in the first place, between the information and the discipline that we may derive from a subject; and again between the specific discipline, or increased power of dealing with similar material, and the general discipline or increased ability to deal with any sort of material, the treatment of which involves somewhat the same general powers of the mind. Although formal discipline, a discipline derived from the form of the study rather than from its content, may be said to include both specific and general results, it is in connection with the latter especially that educational con-troversy has arisen.

The idea of a general mental discipline to be derived from the form of specific stud-ies becomes especially prominent at times in the history of education when a well-established curriculum begins to have less content value than it had at the time of its foundation. Under these circumstances the schoolmasters who advocate the studies that are becoming a trifle antiquated naturally reply to the attack of practical men who question the usefulness of their teaching by saying that, although the information they give is of little practical value, the discipline that their subjects afford increases the general ability of their students to deal with any sort of material. The students learn to observe, to analyze, compare, and classify, to imagine and remember, to rea-son and judge, to will, even to create. They acquire habits of punctuality, of attention, of regularity, of application to work. All these accomplishments are useful, no matter what one tries to do. It is far more useful, the disciplinary argument runs, to possess such general training than merely to have in mind certain specific facts, which must of necessity have a very limited application. (pp. 642–643)

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The argument continues to this day, albeit with less and less emphasis on disciplines of the mind and greater emphasis on defined bodies of knowledge as “relevant” to labor market demands. I have pointed out repeatedly the folly of focusing education primarily on defined bodies of knowledge on the ground that the world’s fund of knowledge now doubles every few months and that citizens of the future will have to be able to learn challenging new bodies of knowledge several times during their adult lives (see, e.g., Haywood, 1990, 2004). Learning to learn is more important than ever before because of the enormous explosion of knowl-edge that has characterized the last two centuries. The discipline of learning depends rather obviously on clear and systematic logical thinking as well as on habits of metacognition and dispositions to seek knowledge and apply effective thinking processes. Cognitive education is a way of pursuing such goals.

Cognitive education may be defined broadly as a teaching and learning strategy whose major goal is the development and encouragement of systematic processes of perceiving, thinking, learning, and problem solving. Such a broad definition owes no allegiance to any specific conception of what constitutes those “systematic processes” or how to reach the goal, rather, it acknowl-edges the necessity, at the current stage of development of the field, to leave room for various theoretical and methodological approaches. Various proposed responses to these two primary questions, the nature of systematic thinking and the best methods for teaching and learning to think systematically, arise from differing conceptions of the nature of ability itself, the de-velopmental processes by which ability grows, the roles of other persons in that development, and the most effective tactics for teaching and learning.

SOME COMMON ASPECTS OF COGNITIVE EDUCATION

The most obvious common aspect of cognitive education is an emphasis on systematic thinking. Even in content-oriented education, encouragement of metacognition (awareness of and de-liberate application of one’s own thinking modes) is usually at least in the background. Every student can recall hearing teachers in the early grades instruct the children to “put your thinking caps on.” Philosophically, that is a bit distressing because it carries the inherent implication that it is acceptable to have those thinking caps off when not instructed to don them. The uniqueness of cognitive approaches in education derives first from the fact that systematic thinking is a primary goal of education, and that goal, with greater or lesser em-phasis, appears to be shared by the various organized programs of cognitive education that are now available.

The second common aspect is the conviction that there are tools of learning that are at least useful and perhaps essential for effective and efficient learning. Most proponents of cognitive education have their own inventory of such tools. Although these tools usually consist of a solid core of processes of formal thought, characterized variously as cognitive and metacogni-tive operations, cognitive functions (Feuerstein et al., 2006; Feuerstein et al., 1980; Haywood, Brooks, & Burns, 1992), cognitive structures (Piaget, 1950), habits of mind (Costa & Kallick, 2009), tools of learning, and building blocks of thinking (Greenberg, 2000a, 2000b), they very often go well beyond such intellective aspects of thinking to include habits, attitudes, motives, dispositions toward learning, and such personal-social variables as self-concept as learner (Feuerstein et al., 2006; Feuerstein et al., 1980; Haywood, 1986; Henderson, 1911). Depending on one’s theoretical orientation, these modes of logical thought may be absorbed from one’s culture; acquired and elaborated through maturation; or acquired, elaborated,


and applied through interaction with more cognitively competent persons such as parents, grandparents, and teachers.

The third common characteristic is focus on processes of thinking and learning (how one learns) rather than exclusive focus on content (what is to be learned). Although it is prob-ably true that content-free learning is neither possible nor desirable, it is the relative balance of process and content focus in favor of a shift toward greater process focus that helps to define cognitive education. To quote a frequent statement by a colleague, “You cannot just think; you have to think about something.” Still, an exclusive or near-exclusive focus on the content (subject matter, topic, information) that is to be learned leaves a substantial lacuna in the learning progression. On the more positive side, we do know largely from studies of dynamic assessment that the learning effectiveness of very many persons can be improved by focusing their attention and efforts on the processes by which they apply their intellectual resources (e.g., Feuerstein, Rand, & Hoffman, 1979; Haywood, 2012; Haywood & Lidz, 2007; Haywood & Tzuriel, 1992; Paour & Soavi, 1992; Rey, 1934; Tzuriel, 2011; Tzuriel & Kaufman, 1999; Vygotsky, 1978, 1934/1986). By analogy, it is not sufficient for an aspiring carpenter to be given a hammer and a saw; he or she must have some idea—and frequently some instruction—about how to use those tools to accomplish tasks. Similarly, baseball players can-not simply be handed bats and expected to hit home runs. Different hitters have virtually the same tools (bats). The vast differences are seen in how those tools are used. In fact, there are enormous individual differences in the ways in which different hitters combine and employ their available resources—not only the primary tool, the bat, but also their personal resources as well, such as their height, reach, eye–hand coordination, strength, speed, patience, deter-mination—and prior knowledge, including the ability to “psych out” the pitcher’s sequence of pitches. In the realm of thinking, marshalling and application of relevant resources (tools) is at least equally important.

The interplay of process focus and content learning presents interesting challenges to teachers and learners. In a cognitive education classroom, the curriculum content is often seen as a set of vehicles for learning and practicing use of formal tools of learning, that is, modes of logical thinking. That does not mean that the content is only incidental, rather, that cognitive teachers keep constantly in mind their process goals while teaching content. In some organized cognitive education programs, a distinction is made between process-oriented teaching and content-oriented teaching, but they are never mutually exclusive. In Bright Start (Haywood et al., 1992), for example, one brief class period per day is devoted to lessons that are sharply focused on processes of thinking and learning, whereas the rest of the school day is devoted to lessons and activities with a focus on academic content. Even with this kind of distinction, the twin foci are inextricably—and purposely—mixed. In an impor-tant way, cognitive and metacognitive processes are indeed the content of the cognitive les-sons, whereas the content activities are conducted with emphasis on the thinking modes that the children have acquired and are still acquiring and elaborating in the cognitive lessons. In my former role as dean of a graduate school of education and psychology, I asked course instructors to specify both content and cognitive goals on their course outlines and to indicate how the cognitive goals would be pursued, although they did not always do so. Here is an example of how that can work. In a graduate course, Psychological Foundations of Education, which I taught for several years at Vanderbilt University, I established both content and cogni-tive goals. The content goals were to have the students demonstrate knowledge of four major domains of the application of psychology to classroom teaching and learning, specifically

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learning theory, motivation, human development, and individual differences. In some semes-ters, the principal cognitive goal was to increase the students’ need for logical evidence and their ability to apply it. Other times, it was to enhance the students’ need for and insistence on precision and accuracy in both information gathering and their own expression. These cognitive goals were built in to reading and writing assignments, classroom discussion, and exams. The consensus (somewhat influenced by the professor, to be sure) was that the goals and related activities were mutually reinforcing.

A vital and distinctive characteristic of programs and approaches in cognitive education is the goal of broad generalization of systematic thinking modes to the widest possible variety of content, subjects, situations, circumstances, problems, and challenges in everyday life. This goal that I often refer to as the “one to many” phenomenon is what gives cognitive education its economic efficiency. The idea is that a relatively small number of fundamental modes of systematic thinking can be applied in perhaps an infinite number of situations in everyday life, and that doing so can help to make such everyday situations more comprehensible and manageable. For example, one may learn to compare geometric figures according to their similarities and differences first on a single dimension such as shape, then on multiple di-mensions such as size, color, number, and spatial orientation. Having practiced doing that, one may then apply that cognitive operation to the comparison of persons, nations, auto-mobiles, aircraft, vacation destinations, restaurants, stock market offerings, tennis racquets, hotels, and an infinite variety of objects and ideas. Furthermore, it is then possible to use that basic operation of comparing to acquire and elaborate a higher level of operation such as clas-sification and class inclusion, enabling one to spread out to an even broader field of applica-tions. The notion of wide generalization of basic cognitive functions, operations, strategies, and modes of thinking is still somewhat controversial, with some cognitive psychologists defending a “domain specificity” position, that is, the idea that cognitive learning generalizes only within the content domains in which the cognitive learning took place (e.g., learned principles of mathematics are applicable only to mathematics or at best to mathematical logic systems). For most proponents of cognitive education, a “domain independent” position is part of the justification for cognitive education itself.

SOME ASPECTS OF COGNITIVE EDUCATION THAT DIFFER ACROSS PROGRAMS

Although some of the defining aspects of cognitive education are shared across programs and approaches that are offered by different thinkers and developers in this field, such as the ones outlined in the preceding paragraphs, there are important differences that can be expected to affect the efficacy of such programs and that consequently should be examined.

Perhaps the most obvious way in which programs differ from each other is the relative breadth of their goals and consequently their methods. I refer to the emphasis on cogni-tive processes versus academic content. As mentioned earlier, these are not and should not be mutually exclusive categories, and there is some combination of process and content in all cognitive education programs, but the balance of the two emphases may differ greatly. In programs whose principal goal is to promote improved learning within a specific content domain such as reading or mathematics, broad generalization may be less heavily empha-sized than in programs whose goals are more general. Such programs may encompass those


designed to enhance “creative” or “critical” thinking, that is, to help learners establish habits of thinking more divergently and perhaps skeptically than they currently do without particular borders around the content domains in which they do their thinking and learning. General goals extend from improvement of all domains of academic learning to enhancing effective thinking in academic, social, and occupational domains and onward to thorough restructur-ing of learners’ habitual thinking and learning modes. This most general goal encompasses the broad realm of “thinking skills” and “learning to learn.”

Such differences in the goals of the programs dictate corresponding differences in their authors’ conceptions of essential cognitive (logic) processes. For example, Carr (1985) studied effects of specific cognitive coaching on spatial orientation of adults who had suf-fered right cerebral hemisphere stroke. She applied a single curriculum unit, Orientation in Space, from the Instrumental Enrichment program, and focused her assessment of that intervention primarily on the criterion variable of spatial orientation. Carr, thus, was em-phasizing the specific importance of spatial orientation as a fundamental logic mode for these patients. Others who apply such programs as Instrumental Enrichment (Feuerstein et al., 2006; Feuerstein et al., 1980), Bright Start (Brooks & Haywood, 2003; Haywood et al., 1992), Philosophy for Children (e.g., Lipman, 2003), Cognitive Research Trust (CoRT; e.g., de Bono, 1970), Cognitive Enhancement Training (COGENT; Das, 2009), Habits of Mind (Costa & Kallick, 2009), and Cognitive Enrichment Advantage (CEA; Greenberg, 2000a, 2000b) focus on a much wider array of cognitive modes and operations because their goals are to improve cognitive functioning in general and thereby to improve learning effective-ness across a broad spectrum of content domains.

APPLYING COGNITIVE APPROACHES IN EDUCATION

Generalization of cognitive modes, strategies, and operations to everyday thinking and learn-ing does not always occur spontaneously or without assistance. This observation probably derives from the fact that cognitive education has been carried out typically with atypical learners, that is, with learners who have special need for help in achieving effective thinking, learning, problem solving, and social adaptation. Achieving generalization requires special methods of teaching, the essential aspect being activities and discussion specifically designed to promote generalization. In fact, “activities” and “discussion” are the principal methods for doing so. A venerable principle in the psychology of learning is that an association is learned most securely to the extent that it is experienced in various situations and circumstances, that is, the desired response attached to many different cues (Bower & Hilgard, 1981). Thus, a classroom activity designed to promote acquisition and elaboration of a particular cognitive operation, let us say, for example, arranging items according to serial position (by size, inten-sity, number) should be repeated with different content and in different contexts. Ordering by size of animals from the largest (elephants, whales, hippopotamuses) to the smallest (say, e.g., mice, ladybugs, fleas, amoebae) will not usually be sufficient to “secure the schema,” as Piaget would have said, so the ordering activity should be repeated by sequencing plants, vehicles, states or provinces, persons, countries, size, and so forth. The sequencing activity may then be varied by ordering according to population (in the United States, e.g., Georgia is the largest state east of the Mississippi River by land area, but New York has a much larger population) or by average income or by volume of exports. The principle that useful order-ing depends on the criterion (size, intensity, population, land area) contributes both to the

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security of the operation of seriating and to the flexibility of its application across various circumstances.

Fortunately for human learners, we (and who knows what other animals) are able to prac-tice applying cognitive principles without actually having to solve a large number of problems or encounter many problem situations. We do that by imagining those situations. We can discuss the ordering of the Eastern states by different criteria without visiting them or even referring to a map or globe because we can conceptualize them, that is, think about them in abstract terms. With young children, for example, one can ask them to use their minds to arrange the children in their classroom according to height, from shortest to tallest, and espe-cially in small classes, they would not actually have to stand the children up and place them in order. Learners may also be asked to discuss examples of times when it is useful to be able to put objects or events in serial order. Such discussions are often referred to as “bridging” (Feuerstein et al., 1980; Haywood, 1988)—the idea being to construct and reinforce “bridges” between specific cognitive operations and their applications in everyday life. In the Bright Start program, in each cognitive lesson, the children are given a main activity focused on a particular cognitive concept or operation, followed by a variation on that activity using slightly different content, then a “generalizing” activity designed to promote transfer and generaliza-tion of the cognitive concept or operation to new content domains, then a bridging discus-sion. Finally, in each lesson, the children are asked to nominate situations in three different domains of their everyday lives (school, home, and peer group) when applying that cognitive concept or operation is useful. Similarly, in Instrumental Enrichment, the teachers are en-couraged to bridge as often and to as many different contexts as possible. Teachers often es-tablish a “cognitive function of the day” that is posted in clear view, and the learners are asked often what it is and how it is applied to whatever content is being taught. Experience suggests that all of this emphasis on promoting generalization is by no means excessive and, in many instances, might not even be sufficient (Cèbe, 2000).

Intentionally promoting metacognition is similarly important in cognitive education. Metacognition has two levels of meaning: (a) awareness of one’s own thinking processes and (b) scanning those processes, selecting appropriate ones, applying them to thinking, learning, and problem solving situations, and evaluating the effects. The latter is a vital executive func-tion, that is, deliberately managing one’s thinking processes. In cognitive education, learn-ers are encouraged to call on their own resources to find or construct solutions to problems and even answers to information questions. In one well-known program, teachers typically present a problem and then ask the learners, “What do you already know that could help you here?” Almost always, there is some useful prior knowledge. Similar questions (Haywood, 1993) put to learners are the following:

“Have you seen something like this before?”“What do you think the problem is here?”“What kind of problem is this?”“How did you do that one the last time?”“What should you do first?”“How many parts does this have?”“What do you think would happen if we put this piece here?”“I wonder whether today’s cognitive function would help us here.”“What kinds of thinking might be needed here?”


These are essentially mediating (see next paragraphs) questions as well as metacognitive questions, focusing learners’ attention on their own thought processes and their own cogni-tive resources.

It should be apparent that methods and styles of teaching make a considerable difference in the effectiveness of cognitive education. Mechanistic styles, such as those based on con-ditioning models (behavior modification, applied behavior analysis, “direct” instruction) may not be expected to produce the generalized effects that one can anticipate from other more metacognitive approaches, although they often lead to more immediate and sometimes larger gains in content-based knowledge (i.e., information). In general, the teaching methods and styles that characterize the most successful applications have at least these following charac-teristics in common:

1. Teachers as catalysts between learner and material to be learned2. Teachers’ confidence in learners’ ability to learn3. Interactive, often questioning, approach rather than purely didactic instruction4. Deliberate combining of content and process5. Major goal of generalization of thinking processes

Perhaps the most widely applied teaching method in cognitive education is referred to as a “mediational” teaching style. This is an approach based on the notion of “mediated learn-ing experience” (Feuerstein & Rand, 1974) applied to classroom teaching in the Instrumental Enrichment program (Feuerstein et al., 2006; Feuerstein et al., 1980) and elaborated by Hay-wood (1985, 1988, 1993). According to Haywood (1985), teachers who employ this approach do the following:

1. Do more asking than telling, thereby expressing confidence in the learners’ ability to respond

2. Act as information resources for the learners3. Challenge both correct and incorrect answers4. Ask process questions (how did you know, how did you do that?)5. Require logical justification for learners’ responses to questions6. Promote task-intrinsic motivation, that is, learning for its own sake and as its own

reward7. Emphasize order, structure, and predictability

This style of teaching may also be referred to as a “catalytic” teaching style, that is, one in which the role of teachers is to function so as to bring about a reaction between learners and the material that is to be learned in the manner of chemical catalysts. Catalyzing such learn-ing reactions entails teaching of basic cognitive operations by way of classroom exercises as well as presenting cognitive and metacognitive models from which the learners can general-ize principles and concepts (as in “theoretical learning”; Karpov, 2003b; Karpov & Haywood, 1998; see also Tzuriel & Shamir, 2010).

Different cognitive educators have employed somewhat different approaches to the na-ture of the interactions between teachers and learners. The nature of the teacher–learner interaction is considered to be of such compelling importance that it has been the subject of symposia in international conferences such as the International Association for Cognitive

34 Haywood

Education and Psychology (IACEP) conference held in Jyväskylä, Finland, in 2001 (Deutsch, 2003; Hansen, 2003; Haywood, 2003; Karpov, 2003a).

PROGRAMS OF COGNITIVE EDUCATION

The broad template of cognitive education can be adapted to various circumstances, learn-ers’ needs, ages, teachers, learning environments, and educational goals. Costa (1991) listed and described 29 programs whose focus was on development of systematic thinking. Subsequently, the inventory has been greatly expanded (see, e.g., Armstrong, 1994; Costa, 2001; Hoon, Hoon, & Tan, 2003; Tan & Seng, 2005). The small list presented here includes only programs with a wide scope, that is, the broad goal of developing and applying system-atic thinking processes across varied content domains. There is a very large number of pro-grams that purport to teach “thinking skills,” “critical thinking,” and “creative thinking” but with applications focused on the teaching and learning of specific content such as reading and mathematics. There are also general approaches to teaching that emphasize develop-ment and reliance on one’s thinking processes but that, so far at least, are not accompanied by structured programs and classroom materials.

The primary purpose of this article is to provide a general description of cognitive educa-tion rather than exhaustive reviews of individual programs and curricula while suggesting the range of such programs; thus, individual programs are not reviewed in detail. Table 1 shows a sample of programs designed to enhance generalizable processes of systematic thinking and, in some cases, to apply those processes in classroom learning of academic content. The programs listed in Table 1 are all based on communicable theories of cognitive development and/or learning, are described by their authors in sufficient detail for assess-ment of their appropriate application, and have the benefit of a body of research on their effectiveness.

Education officials and teachers are besieged with proposed programs and materials for teaching thinking—more than 300 at my latest, and conservative, count. Given the plethora of such materials, it is useful to have some criteria for selecting cognitive education programs. For this discussion, I have divided program selection criteria into “input” characteristics, that is, properties of the programs themselves and “output” characteristics, that is, effects of the programs.

Program Properties (Input Characteristics)

Among desirable input characteristics, the most important is the requirement that programs be based on and derived from solid theories of cognitive development. Such theories should treat at least the nature of human abilities (e.g., intelligence, motivation, cognitive processes) and how they come about, learning processes, the nature of knowledge, and individual dif-ferences. The theoretical base should be clearly communicable and should be emphasized in teacher training in order for trained teachers to be able to devise their own strategies, tactics, and materials in such ways as to be conceptually consistent.

A second criterion is that the programs’ exercises and materials should be demonstrably interesting to learners and their teachers. To borrow a medical analogy, it is axiomatic that medicine not taken has a very poor record. Uninteresting materials, no matter how theo-retically relevant, will wind up not being used at all or being given only cursory treatment.


TABLE 1. A Sample of Programs of Cognitive Education (in Alphabetical Order)

Name of Program Author(s)a Target Population Goals

Training for Abstraction and Coordination of Arbitrary Relations

Paour & Soavi (1992)

Children, adults with learning disabilities

Abstract thinking, categorical reasoning

Bright Start Haywood et al. (1992)

Children aged 3–7 years, elementary school children with disabilities

Cognitive develop-ment, preparation for school learning, integration in regular classes

Cognitive Acceleration through Science Education (CASE)

Adey, Shayer, & Yates (1992)

Children aged 5–15 years

Cognitive develop-ment, accelerated school learning

CATEGO, ORDO, PHONO

Cèbe, Paour, & Goigoux (2002); Paour, Bailleux, Cèbe, & Goigoux (2011); Goigoux, Cèbe, & Paour (2004)

Preschool and primary grades, special needs

Cognitive development, improve learning

COGENT Das (2009); Das, Hayward, Samantaray, & Panda (2006)

Preschool and primary grades

Improve school learning, emphasis on reading

Cognitive Enrichment Advantage

Greenberg (2000a, 2000b)

Primary grades to high school

Cognitive development, improve school learning

Das Eigene Lernen Verstehen (DELV; (Development of Learning Strategies)

Büchel & Büchel (2010/2011)

Adolescents, adults Improve thinking and learning, metacognition

Denktraining für Kinder ( Cognitive Training for Children)

Klauer & Phye (1995)

Early education Cognitive development, learning

Habits of Mind Costa & Kallick (2009)

School-age children, adults

Establish and practice metacognitive habits

(continued)

36 Haywood

Instrumental Enrichment

Feuerstein et al. (2006); Feuerstein et al. (1980)

School-age children, adults

Cognitive develop-ment, school achieve-ment, cognitive remediation

Intelligence Applied Sternberg (1986) School-age children, adults

Enhance learning by applying one’s intelligence

Mind Ladder Jensen (2003) School-age children Cognitive develop-ment, school achievement

Multiple Intelligences

Armstrong (1994);

Gardner (1993)

Wide range Make use of different kinds of intelligence in learning

Philosophy for Children

Lipman (2003) Older children, adolescents, advanced learners

Enhance logical thinking

Tools of the Mind Bodrova & Leong (2007)

Young children Apply Vygotskian principles to learning

aSee References section for full citations.COGENT: Cognitive Enhancement Training.

TABLE 1. (Continued)

Name of Program Author(s)a Target Population Goals

The programs’ goals and methods should be clearly specified in order for teachers (and learners) to know what they are to do. Such specification should include both what to teach and how to teach it, that is, both content and pedagogic process must be clear.

It is important that the programs’ procedures be replicable, that is, what is done in one classroom must be reasonably similar to—and not contradictory to—what is done in others.

Cognitive education programs should call on the ingenuity of teachers. This is true be-cause program authors cannot think of all possible classroom situations for all teachers and all possible learners. It is also true because having teachers call on their own thinking pro-cesses in full view of the learners sets a good example for the learners. “Do not as I do but do as I say” is not an effective teaching strategy.

A metacognitive emphasis is essential for excellent cognitive education programs. This requires constant focus on the learners’ own thinking resources and frequent practice at managing those resources and promotes growth of “executive functions,” that is, cognitive resource management.

Programs should be internally consistent. In an obvious way, for example, the methods employed for teaching academic content should be basically the same as those used for teach-ing thinking processes. Furthermore, the methods for behavior management (encouraging desirable behavior, dealing with undesirable behavior) should be consistent with teaching


methods used throughout the day. It would be counterproductive, for example, to use a mediational teaching style for teaching thinking, a drill-and-practice style for teaching aca-demics, and a behaviorist, contingent reinforcement method for behavior management.

Parent participation should be encouraged and provided for in the cognitive education programs. If a proposed program does not have its own scheme for parent participation, the teachers, often in collaboration with the parent organizations, should develop or adopt one that is conceptually consistent with what occurs in the classroom.

Output Characteristics

There should be evidence based on well-designed evaluation research that proposed programs are effective at achieving the goals for which they were designed. Programs not supported by such evidence of effectiveness should be viewed with suspicion. If adopted, they should be evaluated locally. See evaluation criteria in the succeeding section.

The evidence should show that the programs actually enhance important aspects of cog-nitive development. This is a “first-order” effect, that is, if the expectation that a program promotes cognitive development and that enhanced cognitive development leads to more effective learning, then it is essential that the first level of those effects be demonstrated.

Usually, the most important second-order effect is enhanced achievement in academic sub-jects. Without evidence of such effects, school officials are (justifiably) unlikely to invest the resources necessary to promote cognitive education. Positive effects of any education program should not be limited to “predictor” variables such as scores on intelligence and other aptitude tests. The practical criterion is school achievement, and if one cannot observe improvement in that criterion, it matters little that the programs are associated with increases in IQ.

In many cases of application of cognitive education, more molar variables are appro-priate criteria of effectiveness. Such large variables, usually second- or third-order effects, may include reducing the need for special educational services (special classes, classroom accommodations, tutors, various therapists such as speech and language services, and psy-chological services) as well as improved attendance and classroom participation.

Excellent programs of cognitive education, especially those focused on young children, are associated with improvements in social interaction and group integration of children. This appears to be true because much social conflict may be related to inadequate and even distorted patterns and habits of thinking and learning in such ways that social interactions may be misperceived and/or misinterpreted, leading to conflict (Haywood, 2000).

It should also be demonstrated that proposed programs enhance learners’ motivation to learn, their enthusiasm for novel events, and their willingness to engage in mental work. Such motivation is the key to lifelong independent learning that can continue after formal education has ended.

EFFECTIVENESS OF COGNITIVE EDUCATION

So far, there has not been a comprehensive study incorporating or comparing a representative sample of cognitive education programs; therefore, evaluation of the effectiveness of cogni-tive education must be based on separate evaluative studies of specific programs. I point this out to emphasize the point that, given the differences among cognitive education programs, evaluation of a single program does not constitute evaluation of the broad concept of cog-nitive education. This is especially true and important in cases of negative or inconclusive

38 Haywood

studies; that is to say, lack of evidence for the effectiveness of a specific program is not to be taken as evidence against cognitive education in general because any given program might not constitute a valid example of the general field and concept. Even so, an accumulation of separate evaluative studies that have produced positive effects on relevant criterion variables can have a cumulative effect on evaluation of cognitive education in general. Let us look at some characteristics of good educational program evaluation.

Evaluation of education programs in general is fiendishly difficult because school-based education involves a large number of uncontrolled and uncontrollable variables. That is why one sees inconclusive and sometimes contradictory results from such studies. To justify con-fidence in their conclusions, evaluation of the effectiveness of cognitive education programs should have at least the following characteristics:

• Randomselectionandrandomassignmentofclassesandsubjects• Selectionofcriterionmeasuresthatreflectspecificgoalsofprogram• Precisespecificationofmethods(forteachersandreplication)• Multipleteacherspermethod,permittingassessmentofteachereffects• Relevantcomparison,control,orcontrastgroups• Blindtesting(examinersunawareofsubjects’treatmentgroup)• Multipleassessments(toidentifyinflectionpointsinchangecurves)• Follow-upassessments(toassessdurabilityofeffects)

Few, if any, studies have met all of these requirements. It is especially difficult to achieve ran-dom selection and assignment of subjects and classes. One usually must take whole classes rather than select individuals, in which case the strictly correct procedure for data analysis is to treat classes as subjects, that is, N 5 number of classes. That is only feasible if one has access to a large number of classes. The current availability of hierarchical linear modeling (HLM) techniques mitigates this problem significantly.

Comparison across studies is not very meaningful partly because the exact procedures used in the classrooms are rarely specified in sufficient detail to support replication. Teachers might or might not carry out faithfully what they were trained and requested to do, which makes supervision essential for assuring fidelity of treatments.

It is likely that the greatest problem in evaluation of cognitive education programs is in-adequate teacher training. With rare exception, one does not yet see specific training in cog-nitive education theories and methods as part of preservice teacher education; consequently, training is usually limited to brief in-service workshops or seminars. When the theories that underlie the programs are not adequately taught or learned, teachers must devise their own classroom tactics, and these do not always reflect the philosophy of the programs. Teachers may drop out of research programs, leaving researchers uncertain about selective factors: who stayed in, who dropped out, and why (see, e.g., Blagg, 1991; Haywood, 1992).

Choice of evaluation criteria is a critical matter. These should reflect the actual goals of the programs. If a primary goal is to enhance cognitive development, that should be assessed with tests of logical thinking, reasoning, and problem solving rather than tests of acquired knowledge (information, skill). Given that a primary goal of cognitive education is to enhance learners’ ability to benefit from learning opportunities, use of dynamic assessment techniques for evaluating effectiveness of cognitive education programs makes good sense (see Samuels, Killip, MacKenzie, & Fagan, 1992; Tzuriel, 2011; Tzuriel & Kaufman, 1999). The best test of


learning is learning; that is, one criterion task should be new learning situations rather than simply how much has been learned—although neither should be used alone. That is exactly what is done in dynamic assessment (see, e.g., Tzuriel, Kaniel, Kanner, & Haywood, 1999).

In presenting the evidence regarding effectiveness of one program, it is useful for au-thors to summarize the evaluative research by categories of effects (e.g., effects on cognitive development, motivation, school achievement) and to indicate how each study does or does not meet the criteria of good program evaluation. Effects revealed consistently across studies, even including some less-than-perfect studies, can inspire some confidence, provided the imperfect studies do not suffer from a consistent imperfection. See, for example, Brooks and Haywood (2003) for an example of this presentation strategy.

Evaluation outcomes also depend on the nature of the population one samples, that is, what problems one intends to address. So far, cognitive programs have been applied with at least the following groups: preschool, school age, and postsecondary learners; industrial workers; military trainees; persons with disabilities, including intellectual disabilities, au-tism, learning disabilities, hearing and vision impairment, psychiatric disorders, and chronic illness; migrant, immigrant, and “transcultural” children; chronically unemployed adults; children of poverty and socioeconomic disadvantage; intellectually gifted children; university students; juvenile delinquents; and incarcerated adults.

There is reliable evidence of positive effects of most cognitive education programs on measured intelligence (IQ) and cognitive development (e.g., reasoning, abstract thinking); school achievement in several areas such as language, reading, mathematics, social studies, and geography; task-intrinsic motivation as well as reduced referral for special education; enhanced enthusiasm for school learning; and reduction in interpersonal conflict. Often, the most prominent positive effect has been on scores on intelligence tests such as Raven’s Progressive Matrices, the Wechsler Intelligence Scales, and McCarthy Scales of Children’s Abilities; that is, on scholastic aptitude, a predictor variable, as opposed to achievement, a criterion variable. Most cognitive education programs’ authors do not aspire to raise intel-ligence, rather, a primary goal is to help learners gain access to and apply effectively the intel-ligence they have. Intelligence tests may, of course, reflect such cognitive variables as well as individual differences in “native” ability and in amount of information previously acquired. It is also true that changes in IQ (the manifest variable) do not necessarily reflect changes in intelligence (the latent variable) but may instead merely reflect changes in subjects’ test-taking behavior or in ability to use their intelligence to respond to the test items. Moreover, the exercises commonly used in cognitive education programs bear some similarity to the tasks present in intelligence tests, so the tests constitute “near transfer” at best; thus, examin-ing other effects can be at least equally useful.

Table 2 is a modest attempt to show the various reported effects of several fairly widely used (and obviously highly selected) cognitive education programs. The effects reported in Table 2 represent a composite of data from studies of different programs of cognitive educa-tion applied with varying degrees of fidelity to samples of different populations of learners over differing periods. Because of those differences, the programs from whose study these inferences were derived are not identified in Table 2. This is also because the table is not to be seen as a comparison of the programs, given that their goals differ and that a single conclu-sion will have been drawn from evaluation of more than one program.

There is promising evidence of intermediate-term positive effects (1–3 years) on school achievement, especially in children who are culturally different, transcultural, and

40 Haywood

TABLE 2. Some Demonstrated Effects of Classroom Cognitive Education Programs

Magnitude of Effect

Effect Modest Positive Moderate Positive Strong Positive

IQ and similar tests Modest in some studies to dramatically large in others

Cognitive development, reasoning, problem solving

Tests of reasoning, problem solving, and cognitive tasks related to the train-ing usually show substantial positive effects

Intrinsic motivation Tests based on self-report of subjects show modest improvement; tests of actual behavior show larger effects.

School achievement Modest to dramatic superiority of cognitive education over comparison treatments

Referral to special education

Few studies, but substantial reductions in referral to special education, may endure at least from first to fourth grades

Other (e.g., task persistence); following instructions; volunteering to do mental work

Few studies, but consistently positive effects; teachers’ reports of greater enthusiasm for learning


socioeconomically disadvantaged (Cèbe, 2000; Paour, Cèbe, & Haywood, 2000). The evidence for effects on learning motivation is sparse but positive. Perhaps because reading is such a fundamental academic skill, and schooling is such a cumulative enterprise, positive effects on reading acquisition and comprehension appear to be durable and substantial in some programs (e.g., Cèbe & Paour, 2001). The same is true for mathematics.

Paour (2002) reviewed the cognitive education programs of Adey, Shayer, and Yates (1992); Büchel and Büchel (2010, 2011); Das (2009); Griffin, Case, and Carpenter (1992); Haywood et al. (1992); Klauer and Phye (1989/1995); and Paour and Soavi (1992). He found evidence of improvement of cognitive functioning as shown by problem-solving effectiveness (4/7 programs) and knowledge acquisition (3/7) as well as on school achievement as shown by standardized tests (4/7) and independent assessments (2/7). These data should not be taken to suggest that such effects were not present in the programs where they are not reported; rather, not all specific effects were actually examined in all programs.

SUMMARY

There is now a wide variety of programs whose purpose is to assist learners in developing and applying defined processes of systematic logical thinking, gaining access to and applying their intellectual resources, and improving their learning effectiveness. Such programs cover an age range from preschool to adulthood and have been applied in schools, clinics, remedial learn-ing centers, industrial settings, the military, correctional institutions, and many less formal settings. With such a plethora of programs, one needs to follow guidelines for selection of ap-propriate programs. Although program evaluation research in this area has not always been of distinguished caliber, there is now a sufficient accumulation of convincing studies to support a set of fairly consistent positive effects when the programs are applied systematically by well-trained and supervised teachers. Such effects include significant elevations in IQ, improved cognitive development, enhanced school achievement, greater enthusiasm for learning, and some social effects such as reduced interpersonal conflict and greater cooperative learning.

NOTE

1. The Thinking Teacher is no longer in publication. Articles from The Thinking Teacher may be ob-tained from [email protected]

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pp. 642–647). New York, NY: Macmillan.Hoon, A. S. S., Hoon, L. P. K., & Tan, O-S. (Eds.). (2003). Mediated learning experience with children: Ap-

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Correspondence regarding this article should be directed to H. Carl Haywood, Vanderbilt University, 144 Brighton Close, Nashville, TN 37205. E-mail: [email protected]



What Is Cognitive Education?

Robert J. SternbergOklahoma State University

Cognitive education is education that seeks to improve the cognitive (mental) skills of the student in order that the students can lead constructive and satisfying lives. There are many different models for cognitive education, but I have constructed a career doing cognitive education through a “theory of successful intelligence” (Stern-berg, 1997, 2010; Sternberg & Grigorenko, 2007; Sternberg, Jarvin, & Grigorenko, 2009; Sternberg, Kaufman, & Grigorenko, 2008)—a theory that can be used in teach-ing not only on a small scale but also on a large scale.

In this article, I first describe the theory of successful intelligence. Next, I describe how the theory has been augmented in recent years through the addition of wisdom. Then I discuss an even more recent addition, the role of ethical reasoning and behav-ior. Finally, I draw some conclusions.

Keywords: successful intelligence; analytical intelligence; creative intelligence; practical intelligence; wisdom

SUCCESSFUL INTELLIGENCE

Background

Traditional teaching typically develops and also rewards a rather narrow spectrum of cognitive skills, in particular, those associated with rote memorization and, on occa-sion, superficial reflection on the material that is memorized. The result is the world

we have today, where many students have failed adequately to develop their skills in think-ing creatively, analytically, practically, and wisely. From this point of view, it is not surprising that the world is in what sometimes seems to be a perpetual state of stress and turmoil. One solution is to value other ability patterns and then change teaching and assessment so that these other ability patterns can lead to success in school. The theory of successful intelligence attempts to provide a broader basis for the teaching of cognitive skills.

The Theory

According to the proposed theory, successful intelligence is (a) the use of an integrated set of abilities needed to define and attain success in life within an individual’s sociocultural context. People are successfully intelligent by virtue of (b) recognizing their strengths and making the most of them at the same time that they recognize their weaknesses and find ways to correct

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or compensate for them. Successfully intelligent people (c) adapt to, shape, and select en-vironments through (d) finding a balance in their use of analytical, creative, and practical abilities (Sternberg, 1997, 2005a). A person can excel in analytical, creative, and/or practical abilities—all of them or none of them. The main attribute for successful intelligence is to be able to capitalize on strengths and compensate for weaknesses (Sternberg, 2003a, 2005b; Sternberg, Jarvin, & Grigorenko, 2011). Consider each element of the theory in turn.

The first element makes clear that there is no one definition of success that works for everyone. For some people, success is brilliance as a lawyer; for others, it is originality as a novelist; for others, it is caring for one’s children; for others, it is devoting one’s life to God. For many people, it is some combination of things. Because people have different life goals, education needs to move away from single targeted measures of success such as grade point average.

The second element asserts that there are different paths to success, no matter what goal one chooses. Some people achieve success in large part through personal charm, oth-ers through brilliance of academic intellect, others through stunning originality, and others through working extremely hard. For most of us, there are at least a few things we do well, and our successful intelligence depends in large part on making these things “work for us.” At the same time, we need to acknowledge our weaknesses and find ways either to improve on them or to compensate for them. For example, we might work hard to improve our skills in an area of weakness or work as part of a team so that other people compensate for the kinds of things we do not do particularly well.

The third element asserts that success in life is achieved through some balance of adapt-ing to existing environments, shaping those environments, and selecting new environments. Often, when we go into an environment—as do students and teachers in school—we try to modify ourselves to fit those environments, in other words, we adapt. But sometimes it is not enough to adapt: We are not content merely to change ourselves to fit the environment, but rather, we also want to change the environment to fit us. In this case, we shape the environ-ment to make it a better one for us and possibly for others as well. But there may come times when our attempts to adapt and to shape lead us nowhere—when we simply cannot find a way to make the environment work for us. In these cases, we leave that old environment and select a new environment. Sometimes the smart thing is to know when to get out.

Finally, we balance three kinds of abilities to achieve these ends: analytical abilities, cre-ative abilities, and practical abilities. We need creative abilities to generate ideas, analytical abilities to determine whether they are good ideas, and practical abilities to implement the ideas and to convince others of the value of our ideas. Most people who are successfully intel-ligent are not equal in these three abilities, but they find ways of making the three abilities work harmoniously together.

This definition of successful intelligence contains within it several implications for teach-ing (Sternberg & Grigorenko, 2007; Sternberg et al., 2009).

Teaching for Successful Intelligence

The theory of successful intelligence implies several things regarding teaching and assessment.First, because students have different life goals, and hence different outcomes that—for

them—are successful, student success needs to be defined in terms that are meaningful to the students as well as to the institution. Second, teachers should help students to capitalize

What Is Cognitive Education? 47

on strengths and at the same time help them correct or compensate for weaknesses. Third, there is no one right way of teaching and learning. Fourth, there is no one right way of assess-ing students’ achievement. Fifth, teachers should teach and assess to weaknesses as well as to strengths. Sixth, students need to learn to balance adaptation to, shaping of, and selection of environments.

We should encourage teachers to teach and assess achievement in ways that enable stu-dents to analyze, create with, and apply their knowledge. When students think to learn, they also learn to think. And there is an added benefit: Students who are taught analytically, cre-atively, and practically perform better on assessments, apparently without regard to the form the assessments take. That is, they outperform students instructed in conventional ways, even if the assessments are for straight factual memory (Sternberg, Torff, & Grigorenko, 1998). Moreover, our research shows that these techniques succeed, regardless of subject matter area. But what exactly are the techniques used to teach analytically, creatively, and practically? (See Table 1 for a summary.)

1. Teaching analytically means encouraging students to (a) analyze, (b) critique, (c) judge, (d) compare and contrast, (e) evaluate, and (f) assess. When teachers refer to teaching for “critical thinking,” they typically mean teaching for analytical thinking. How does such teaching translate into instructional and assessment activities? Consider the following various examples across the school curriculum:

(a) Analyze the development of the character of Heathcliff in Wuthering Heights. (Literature)

(b) Critique the design of the experiment (just gone over in class or in a reading) show-ing that certain plants grew better in dim light than in bright sunlight. (Biology)

(c) Judge the artistic merits of Roy Lichtenstein’s “comic book art,” discussing its strengths as well as its weaknesses as fine art. (History of Art)

(d) Compare and contrast the respective natures of the American and the French Revo-lution, pointing out ways both in which they were similar and those in which they were different. (History)

(e) Evaluate the validity of a solution to a mathematical problem and discuss weak-nesses in the solution, if there are any. (Mathematics)

(f ) Assess the strategy used by a winning player in a tennis match you just observed, stating what techniques he or she used to defeat his or her opponent. (Physical Education)

TABLE 1. Summary of Selected Prompts for Analytical, Creative, and Practical Instruction and Assessment

Analytical Creative Practical

(a) Analyze (a) Create (a) Apply(b) Critique (b) Invent (b) Use(c) Judge (c) Discover (c) Put into practice(d) Compare and contrast (d) Imagine if . . . (d) Implement(e) Evaluate (e) Suppose that . . . (e) Employ(f ) Assess (f ) Predict (f ) Render practical

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2. Teaching creatively means encouraging students to (a) create, (b) invent, (c) discover, (d) imag-ine if . . ., (e) suppose that . . ., and (f) predict. Teaching for creativity requires teachers not only to support and encourage creativity but also to role model it and to reward it when it is displayed (Sternberg & Lubart, 1995). In other words, teachers need not only to talk the talk but also to walk the walk. Consider some of the following examples of instructional or assessment activities that encourage students to think creatively:

(a) Create an alternative ending to a short story you just read that represents a different way things might have gone for the main characters in the story. (Literature)

(b) Invent a dialogue between an American tourist in Paris and a French man he or she encounters on the street from whom he or she is asking directions on how to get to the Rue Pigalle. (French)

(c) Discover the fundamental physical principle that underlies all of the following prob-lems, each of which differs from the others in the “surface structure” of the prob-lem but not in its “deep structure . . . .” (Physics)

(d) Imagine if the government of China keeps evolving over the course of the next 20 years in much the same way it has been evolving. What do you believe the gov-ernment of China will be like in 20 years? (Government/Political Science)

(e) Suppose that you were to design one additional instrument to be played in a sym-phony orchestra for future compositions. What might that instrument be like and why? (Music)

(f ) Predict changes that are likely to occur in the vocabulary or grammar of spoken Spanish in the border areas of the Rio Grande over the next 100 years as a result of continuous interactions between Spanish and English speakers. (Linguistics)

3. Teaching practically means encouraging students to (a) apply, (b) use, (c) put into practice, (d) implement, (e) employ, and (f) render practical what they know. Such teaching must relate to the real practical needs of the students not just to what would be practical for individuals other than the students (Sternberg et al., 2000). Consider some examples as follows:

(a) Apply the formula for computing compound interest to a problem people are likely to face when planning for retirement. (Economics, Math)

(b) Use your knowledge of German to greet a new acquaintance in Berlin. (German) (c) Put into practice what you have learned from teamwork in football to making a class-

room team project succeed. (Athletics) (d) Implement a business plan you have written in a simulated business environment.

(Business) (e) Employ the formula for distance, rate, and time to compute a distance. (Math) (f ) Render practical a proposed design for a new building that will not work in the aes-

thetic context of the surrounding buildings, all of which are at least 100 years old. (Architecture)

WISDOM

Background

In recent years, we have augmented the theory of successful intelligence to include wis-dom and teaching for wisdom (Sternberg, 2003b; Sternberg et al., 2009; Sternberg, Jarvin, & Reznitskaya, 2008; Sternberg, Reznitskaya, & Jarvin, 2007). The reason for this augmentation


is the observation that many people are smart but foolish (Sternberg, 2002). In particular, they show the following certain cognitive fallacies:

1. The unrealistic optimism fallacy. This fallacy occurs when one believes one is so smart or powerful that it is pointless to worry about the outcomes, and especially the long-term ones, of what one does because everything will come out all right in the end—there is nothing to worry about, given one’s brains or power. If one simply acts, the outcome will be fine. Bill Clinton tended to repeat sexual behavior that, first as Governor and then as President, was likely to come to a bad end. He seemed not to worry about it.

2. The egocentrism fallacy. This fallacy arises when one comes to think that one’s own interests are the only ones that are important. One starts to ignore one’s responsibili-ties to other people or to institutions. Sometimes, people in positions of responsibility may start off with good intentions but then become corrupted by the power they yield and their seeming unaccountability to others for it. Muammar Gaddafi, for example, seemed to let egocentrism get the better of him when he became president and ran Libya like a personal fiefdom favoring his immediate family.

3. The omniscience fallacy. This fallacy results from having available at one’s disposal essentially any knowledge one might want that is, in fact, knowable. With a phone call, a powerful leader can have almost any kind of knowledge made available to him or her. At the same time, people look up to the powerful leader as extremely knowledgeable or even close to all knowing. The powerful leader may then come to believe that he or she really is all knowing. So may his or her staff.

4. The omnipotence fallacy. This fallacy results from the extreme power one wields or be-lieves one wields. The result is overextension and, often, abuse of power. Sometimes leaders create internal or external enemies to demand more power for themselves to deal with the supposed enemies. In Zimbabwe, Robert Mugabe has turned one group against another, with the apparent goal of greatly expanding and maintaining his own power.

5. The invulnerability fallacy. This fallacy derives from the presence of the illusion of com-plete protection, such as might be provided by a large staff. People, and especially leaders, may seem to have many friends ready to protect them at a moment’s notice. The leaders may shield themselves from individuals who are anything less than syco-phantic. The Republican win in Massachusetts in 2010 showed Democrats they were not invulnerable at the polls despite the decisive win in 2008.

6. The ethical disengagement fallacy. This fallacy occurs when one starts to believe that eth-ics are important for other people but not for oneself. Many leaders of countries and corporations alike have seemed to think themselves exempt from the ethical standards to which they hold others. Kim Jong Il of North Korea comes to mind as an individual who held countrymen to a high level of sacrifice and ethical standards while not living the kind of life he required of so many others.

So it is not enough to be smart. To be successfully intelligent in life, one needs also to be wise.

The Theory

We refer to this augmented theory as WICS, standing for wisdom, intelligence, creativity, and synthesized.

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Wisdom requires one to (a) apply their knowledge to a common good; (b) over the long and short terms; (c) through the infusion of ethical values; (d) by balancing intrapersonal (one’s own), interpersonal (others’), and extrapersonal (larger) interests; and (e) to balance adaptation to, shaping of, and selection of environments.

Teaching for Wisdom

Here are some examples of teaching for wisdom:

(a) Can a war ever promote a common good? (Political Science)(b) Can the use of stem cells from embryos ever be based on positive ethical values? (Biology)(c) Does a massive economic stimulus package, resulting in a great increase in national

debt, promote short-term interests at the expense of long-term ones? (Economics)(d) Was the bombing of Hiroshima ethically justified? (History)(e) Can one argue that creating a weapon of mass destruction can serve an extrapersonal

good, that is, a good for the preservation of a society? (Engineering)(f) Should euthanasia be legalized under certain circumstances as balancing intrapersonal

with extrapersonal interests? (Social Studies/Ethics)

Table 2 summarizes some of the ideas.We have separated teaching for wisdom in this article because some teachers will believe

that this is beyond their purview. For example, a mathematics teacher may not feel that wis-dom is relevant to his or her particular goals, or a physics teacher may view wisdom-based teaching as a distraction. We believe that many of the problems the world faces stem not from a lack of intelligence, at least as conventionally defined, but rather from a lack of wisdom. Hence, we believe that teaching for wisdom can be an important part of K-12 education.

ETHICAL REASONING AND BEHAVIOR

Background

In the psychological literature, perhaps the greatest credit for opening up the issue of ethical be-havior is because of Latané and Darley (1970) who opened up a new field of research on bystander intervention. They showed that, contrary to expectations, bystanders intervene when someone is in trouble only in very limited circumstances. For example, if they think that someone else might intervene, the bystanders tend to stay out of the situation. Latané and Darley even showed that

TABLE 2. Summary of Selected Prompts for Wisdom-Based Instruction and Assessment

Use for the common good

Balance interests: intrapersonal (one’s own), interpersonal (others), and extrapersonal (beyond the individual)

Balance responses of adaptation to, selection of, and shaping of environments

Plan for the long term as well as the short term

Infuse positive ethical values


divinity students who were about to lecture on the parable of The Good Samaritan were no more likely than other bystanders to help a person in distress who was in need of—a good Samaritan!

Gardner (1999) has wrestled with the question of whether there is some kind of existen-tial or even spiritual intelligence that guides people through challenging life dilemmas. Coles (1998) is one of many who have argued for a moral intelligence in children as well as adults. Is there some kind of moral or spiritual intelligence in which some children are inherently supe-rior to others? Piaget (1932) and Kohlberg (1984) believed that there are stages of moral reason-ing, and that as children grow older, they advance in these stages. Some will advance faster and further than others, creating individual differences in levels of moral development. Harkness, Edwards, and Super (1981) have questioned whether the stages are culturally generalizable. In contrast to the Kohlberg model, Gilligan (1982) argued that Kohlberg overly emphasized the development of principles of universal justice over a psychology of caring and compassion.

Some believe that ethical reasoning has a large nonrational component (e.g., Rogerson, Gottlieb, Handelsman, Knapp, & Younggren, 2011), but the claim here is that ethical reason-ing can be largely rational but usually is not because people fail to follow through on the com-plete set of steps needed to reach an ethical conclusion. And they often fail to follow through because they lack sufficient creative imagination to reach such a conclusion.

Drawing in part on the Latané and Darley (1970) model of bystander intervention, I have constructed a model of ethical behavior that would seem to apply to various ethical problems. The model specifies the specific skills students need to reason and then behave ethically. It can be used as a basis for educating students to behave in an ethical manner. The model assumes that, contrary to our usual beliefs, ethical behavior is challenging rather than easy.

The basic premise of the model is that ethical behavior is far harder to display than one would expect simply on the basis of what we learn from our parents, from school, and from our religious training (Sternberg, 2009a, 2009b, 2009c). To intervene in an ethically challeng-ing situation, individuals must go through a series of steps, and unless all of the steps are completed, the individuals are not likely to behave in an ethical way, regardless of the amount of training they have received in ethics and regardless of their levels of other types of skills. The example I will draw on most is genocides, such as in Rwanda and Darfur, where there is a potential for outside intervention, but the intervention, in fact, never happens or happens only to a minor extent.

The Theory

According to the proposed theory (Sternberg, 2009a, 2009b, 2011), enacting ethical behavior is much harder than it would appear to be because it involves multiple, largely sequential steps. To behave ethically, the individual has to do the following:

1. Recognize that there is an event to which to react.2. Define the event as having an ethical dimension.3. Decide that the ethical dimension is of sufficient significance to merit an ethics-guided

response.4. Take responsibility for generating an ethical solution to the problem.5. Figure out what abstract ethical rule(s) might apply to the problem.6. Decide how these abstract ethical rules actually apply to the problem so as to suggest a concrete

solution.

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7. Prepare for possible repercussions of having acted in what one considers an ethical manner.8. Act.

Students need to learn these steps of ethical reasoning so that they can apply them to their own ethical reasoning.

Consider each of the following step in turn:

1. Recognize that there is an event to which to react. In cases where there has been an ethical transgression, the transgressors often go out

of their way to hide that there is even an event to which to react. For example, many countries hide the deplorable condition of their political prisoners. The Nazis hid the existence of death camps and referred to Jews, Roma, and other peoples merely as being “resettled.” The Rwandan government tried to cover up the massacre of the Tut-sis and also of those Hutus who were perceived as sympathetic to the Tutsis. The goal of the transgressors is to obscure the fact that anything is going on that is even worth anyone’s attention. One has to recognize that the situation as described by the govern-ment may be different from the actual situation. When people hear their political, educational, or religious leaders talk, they may not believe there is any reason to question what they hear. After all, they are listening to authority figures. In this way, leaders, and especially cynical and corrupt leaders, may lead their followers to accept corruption and even disappearances as nonevents.

2. Define the event as having an ethical dimension. Given that one acknowledges that there is an event to which to pay attention, one still

needs to define it as having an ethical dimension. Given that perpetrators will go out of their way to define the situation otherwise—as a nonevent, a civil war, an internal con-flict that is no one else’s business, and so on—one must actually redefine the situation to realize that an ethical component is involved. Redefinition of problem situations is one of the keys to creativity. Again, a creative component is central to ethical reasoning. In the case of the Nazi genocide, the campaign against Jews was defined as a justi-fied campaign against an internal enemy bent on subversion of the state (Sternberg & Sternberg, 2008). It was of course not defined as a genocide. And in Rwanda, the gov-ernment defined the genocide as a fight against invading aggressors who came from outside the country and did not belong there in the first place.

3. Decide that the ethical dimension is significant. If one observes a driver going 1 mph over the speed limit on a highway, one is unlikely

to become perturbed about the unethical behavior of the driver, especially if the driver is oneself. A genocide is a far cry from driving 1 mph over the speed limit. And yet, if one is being told by cynical, dishonest leaders that the events that are transpiring are the unfortunate kinds of events that happen in all countries—did not America have its own civil war?—then it may not occur to people that the event is much more serious than its perpetrators are alleging it to be.

4. Take personal responsibility for generating an ethical solution to the problem. People may allow leaders to commit wretched acts, including genocide, because they

figure it is the leaders’ responsibility to determine the ethical dimensions of their ac-tions. Is not that why they are leaders in the first place? Or people may assume that the leaders, especially if they are religious leaders, are in a uniquely good position to


determine what is ethical. If a religious leader encourages someone to become a sui-cide bomber or to commit genocide, that “someone” may feel that being such a bomber must be ethical. Why else would a religious leader have suggested it?

5. Figure out what abstract ethical rule(s) might apply to the problem. Most of us have learned, in one way or another, ethical rules that we are supposed to

apply to our lives. For example, we are supposed to be honest. But who among us can say he or she has not lied at some time, perhaps with the excuse that we were protect-ing someone else’s feelings? By doing so, we insulate ourselves from the effects of our behavior. Perhaps, we can argue that the principle that we should not hurt someone else’s feelings takes precedence over not lying. Of course, as the lies grow larger, we can continue to use the same excuse. When leaders encourage genocide, they clearly violate one of the Ten Commandments, namely, “Thou shalt not kill.” This is why the killings, to the extent they are known, are posed by cynical leaders as “justifiable executions” rather than as murders. The individual must analyze the situation carefully to realize whether the term “murder” applies.

6. Decide how these abstract ethical rules actually apply to the problem so as to suggest a concrete solution.

This kind of translation is, I believe, nontrivial. In our work on practical intelligence, some of which was summarized in Sternberg et al. (2000), we found that there is, at best, a modest correlation between the more academic and abstract aspects of intel-ligence and its more practical and concrete aspects. Both aspects, though, predicted behavior in everyday life. People may have skills that shine brightly in a classroom, but that they are unable to translate into real-world consequential behavior.

7. Prepare for possible repercussions of having acted in what one considers an ethical manner. When Harry Markopolos (see Markopolos, 2011) pointed out to regulators that Bernard

Madoff’s investment returns had to be fraudulent, no one wanted to listen. It was Markopolos who was branded as a problem, not Madoff. In general, when people blow the whistle, they need to be prepared for their bona fides to be questioned, not necessarily those of the person on whom they blew the whistle (as Marianne Gingrich, ex-wife of a former U.S. Speaker of the House and presidential candidate, discovered when she was branded a liar by her former husband on her revelation that her ex-husband wanted an open marriage when she discovered that he was having an affair, later resulting in divorce). People must imagine the possible repercussions of acting ethically—will they lose their friends, will they lose their job, will they lose their reputation? During the Enron scandal, whistle-blower Sherron Watkins lost all three. Relatedly, when reports first came in of Nazi genocide, there was a general reaction of disbelief—how could such atrocities possibly be happening? Whistle-blowers not only need to imagine all the things that could go wrong but also need to imagine what could go right and how they can maxi-mize the chances of things going right. Such imagination requires creative thinking.

8. Act. In ethical reasoning as in creativity, there may be a large gap between thought and ac-

tion. Both often involve defying the crowd, and hence even people who believe a certain course of action to be correct may not follow through on it. In the Latané and Darley (1970) work, the more bystanders there were, the less likely an individual was to take action to intervene. Why? Because one figured that if some-thing was really wrong, then someone among all the others witnessing the event would

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have taken responsibility. You are better off having a breakdown on a somewhat lonely country road than on a busy highway because a driver passing by on the country road may feel that he or she is your only hope.

Teaching for Ethical Reasoning and Behavior

We need to teach for ethical reasoning (Sternberg, 2010). First, students need to see how ethi-cal reasoning applies in their own lives. How can a student apply this to his or her own life? Consider a typical event in the life of a college student.

A student, John, is trying to decide whether he should turn in a fellow student, Bill, whom he saw cheating on an examination.

1. Recognize that there is an event to which to react. John has to observe the cheating and decide that it is a situation in which he potentially

can do something.2. Define the event as having an ethical dimension. John has to define the cheating as unethical. Many students do so, but some others see it

as a utilitarian matter—it’s okay if Bill gets away with it.3. Decide that the ethical dimension is significant. John has to decide that Bill’s cheating on the examination is a big enough deal that it

is worth paying attention to. Some students may see it as an ethical issue but not as a significant one.

4. Take personal responsibility for generating an ethical solution to the problem. There are ethical problems that are serious but that are not necessarily your ethical

problems. John may decide that there is an ethical problem here, even a big one, but that it is none of his business. For example, John may look at it as the teacher’s respon-sibility, not his, to turn in Bill.

5. Figure out what abstract ethical rule(s) might apply to the problem. What rule applies? If there is no honor code, is there a rule by which John should turn

in Bill? Perhaps John believes, on the contrary, that the rule is to mind his own busi-ness, or to avoid cheating himself, but not to turn in Bill.

6. Decide how these abstract ethical rules actually apply to the problem so as to suggest a concrete solution.

Perhaps John believes that one should turn in cheaters but cannot apply the rule in this situation, realizing that he could not prove that Bill cheated.

7. Prepare to counteract contextual forces that might lead one not to act in an ethical manner. John may be reluctant to turn in Bill because he believes that other students, including

but not limited to Bill, will shun him or retaliate against him for being a “snitch.”8. Act. In the end, the question becomes one not of how one thinks, but of what one does. It

can be very difficult to go from thought to action. But the ultimate test of ethical reason-ing is not just in how one thinks but also in how one acts. John may believe he should turn in Bill but just not get up the guts actually to do so.

Sometimes, the problem is not that other people seem oblivious to the ethical implica-tions of the situation, but that they actively encourage you to behave in ways you define as


unethical. In the Rwandan genocides, Hutus were encouraged to hate Tutsis and to kill them even if they were within their own family (see discussion in Sternberg & Sternberg, 2008). Those who were not willing to participate in the massacres risked becoming victims themselves (Gourevitch, 1998). The same applied in Hitler’s Germany. Those who tried to save Jews from concentration camps themselves risked going to such camps (Totten, Parsons, & Charny, 2004). It is easier to follow the crowd than to act creatively or, in many instances, ethically. And that is why corruption is so common throughout the world. Even when people know of it, they often reelect corrupt leaders, allowing the corruption to persist.

In recent years, we have seen the end of U.S. banks such as Bear Stearns, Lehman Broth-ers, Merrill Lynch, and numerous other financial enterprises. Few people reached the depths of Bernard Madoff, the epitome of unethical behavior on Wall Street, who sits in a prison cell. The irony is that firms such as Bear Stearns and Lehman Brothers hired only those they considered to be the best and the brightest. They recruited from the very top colleges and universities in the nation. It appears that whatever qualities one needs to be accepted by these institutions and to be graduated from them with distinction are not the qualities that would have led to success in the firms. In large part, university success reflects a student’s ability to absorb a knowledge base and to reason analytically with it. But success in business and in life requires creative and ethical reasoning—none of which are at a premium in university life or in the standardized tests now used to admit students to universities. In a nutshell, we are selecting for and developing qualities that, although important, are woefully incomplete when it comes to success in the world.

The model applies not only to analyzing others but also to evaluating one’s own ethical rea-soning. When confronted with a situation having a potential ethical dimension, students can learn literally to go through the steps of the model and ask how they apply to a given situation.

Effective teaching of ethical reasoning involves presenting case studies, but it is impor-tant that students as well generate their own case studies from their own experience, and then apply the steps of the model to their own problems. They need to be actively involved in seeing how the steps of the model apply to their own individual problems. Most impor-tantly, they need to think creatively as they use the model of ethical reasoning in thinking about ways of defining and redefining ethical dilemmas that enable them to get through the various steps.

As a university administrator, I, like other administrators, have discovered that students’ ethical skills often are not up to the level of their ability test scores. Colleges run the full gamut of unethical behavior on the part of students: drunken rampages, cheating on tests, lying about reasons for papers turned in late, attacks by students on other students, and ques-tionable behavior on the athletic field. Faculty members, of course, are not immune either: Few academic administrators probably leave their jobs without having had to deal with at least some cases of academic or other misconduct on the part of faculty. In hearing excuses students invent for work not done, I often have wished that students and faculty alike would apply their creativity to ethical rather than unethical uses.

In speaking of the challenges of leadership, and particularly of leaders who become fool-ish, I have spoken of the risk of ethical disengagement (Sternberg, 2008). Ethical disengage-ment (based on Bandura, 1999) is the dissociation of oneself from ethical values. One may believe that ethical values should apply to the actions of others, but one becomes disengaged from them as they apply to oneself. One may believe that one is above or beyond ethics or simply not see its relevance to one’s own life. Unless one seeks creatively to redefine the way

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one sees oneself, one sees oneself as ethical when in fact one has entered into a period of downward ethical drift (Sternberg, 2012).

Schools should teach ethical reasoning; they should not necessarily teach ethics. There is a difference. Ethics is a set of principles for what constitutes right and wrong behavior. These principles are generally taught in the home or through religious training in a special school or through learning in the course of one’s life. It would be challenging to teach eth-ics in a secular school because different religious and other groups have somewhat differ-ent ideas about what is right and wrong. There are, however, core values that are common to almost all these religions and ethical systems that schools do teach and reinforce, for example, reciprocity (the Golden Rule), honesty, sincerity, and compassion in the face of human suffering.

Ethical reasoning is how to think about issues of right or wrong. Processes of reasoning can be taught, and the school is an appropriate place to teach these processes. The reason is that, although parents and religious schools may teach ethics, they do not always teach ethical reasoning or, at least, do so with great success. They may see their job as teaching right and wrong, but not how to reason with ethical principles. Moreover, they may not do as good a job of it as we would hope for.

Is there any evidence that ethical reasoning can be taught with success? There have been successful endeavors with students of various ages. Paul (Paul & Elder, 2005), of the Foun-dation for Critical Thinking, has shown how principles of critical thinking can be applied specifically to ethical reasoning in young people. On the present view, for the instruction to be fully successful, teachers also would have to teach for creative thinking. DeHaan and Narayan (2007) at Emory University have shown that it is possible successfully to teach ethical reasoning to high school students. Myser, Kerridge, and Mitchell (1995) of the University of Newcastle has shown ways specifically of teaching ethics to medical students. Weber (1993) of Marquette University found that teaching ethical awareness and reasoning to business school students can improve from courses aimed at these topics, although the improvements are often short term. But Ponemon (1993; “First Center to Study Accounting Ethics Opens”) and Jordan (2007) both found that as leaders ascend the hierarchy in their businesses, their tendency to define situations in ethical terms actually seems to decrease.

CONCLUSION

Cognitive education, according to the view presented here, involves a multifaceted effort. It requires more than just teaching for “critical thinking.” First, it involves teaching for ana-lytical, creative, and practical thinking. Second, it involves going beyond this to teaching for wisdom. Finally, it involves teaching for ethical thinking and behavior. It is not enough that students are smart. From all we know, the leaders of the current government in Syria—who are massacring their own citizens—are smart. What they lack are the wisdom and ethical behavior that turn “smartness” in a positive and constructive, rather than negative and de-structive, direction.

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ing the gap between knowledge about ethics and its use in clinical practice. Journal of Medical Ethics, 21(2), 97–103.

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Piaget, J. (1932). The moral judgment of the child. London, United Kingdom: Kegan Paul, Trench, Trübner.

Ponemon, L. (1993). First center to study accounting ethics opens. Retrieved from http://www.thefreelibrary.com/First+center+to+study+accounting+ethics+opens.+%28Binghamton+University ...-a014240267.

Rogerson, M. D., Gottlieb, M. C., Handelsman, M. M., Knapp, S., & Younggren, J. (2011). Nonrational processes in ethical decision making. American Psychologist, 66(7), 614–623.

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189–202.Sternberg, R. J. (2008). The WICS approach to leadership: Stories of leadership and the structures and

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55(33), B14–B15.Sternberg, R. J. (2009c). Reflections on ethical leadership. In D. Ambrose & T. Cross (Eds.), Morality,

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Sternberg, R. J. (2011). Ethics: From thought to action. Educational Leadership, 68(6), 34–39.Sternberg, R. J. (2012). Ethical drift. Liberal Education, 98(3), 60.Sternberg, R. J., Forsythe, G. B., Hedlund, J., Horvath, J., Snook, S., Williams, W. M., . . . Grigorenko, E.

L. (2000). Practical intelligence in everyday life. New York, NY: Cambridge University Press.Sternberg, R. J., & Grigorenko, E. L. (2007). Teaching for successful intelligence (2nd ed.). Thousand Oaks,

CA: Corwin.Sternberg, R. J., Jarvin, L., & Grigorenko, E. L. (2009). Teaching for wisdom, intelligence, creativity, and

success. Thousand Oaks, CA: Corwin.Sternberg, R. J., Jarvin, L., & Grigorenko, E. L. (2011). Explorations in giftedness. New York, NY: Cam-

bridge University Press.Sternberg, R. J., Jarvin, L., & Reznitskaya, A. (2008). Teaching of wisdom through history: Infusing wise

thinking skills in the school curriculum. In M. Ferrari & G. Potworowski (Eds.), Teaching for wisdom (pp. 37–57). New York, NY: Springer.

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Correspondence regarding this article should be directed to Robert J. Sternberg, Oklahoma State Uni-versity, Office of Academic Affairs, Whitehurst 101, Stillwater, OK 74078. E-mail: [email protected]



Mediated Learning Experience and Cognitive Modifiability

David TzurielBar-Ilan University

The focus of this article is on the effects of mediated learning experience (MLE) inter-actions on children’s cognitive modifiability. In this article, I discuss the MLE theory, and selected research findings demonstrating the impact of MLE strategies in facilita-ting cognitive modifiability. Research findings derive from mother–child interactions, peer-mediation and cognitive education programs. Mediation for transcendence (expanding) was found consistently as the most powerful strategy predicting cognitive modifiability and distal factors in samples of children with learning difficulties directly predict cognitive modifiability. Findings of peer-mediation studies indicate that chil-dren in experimental groups participating in the Peer Mediation with Young Children program showed better mediational teaching style and higher cognitive modifiability than children in control groups. Application of dynamic assessment as a central evalu-ation method reveals that the contribution of the cognitive education program was not simply supporting the development of a particular skill practiced during the program; it also involved teaching children how to benefit from mediation in a different setting and consequently improve their cognitive performance across other domains.

Keywords: mediated learning experience; cognitive modifiability; dynamic assessment; mother–child interaction; peer-mediation

Cognitive education starts from a very early age in the spontaneous interactions between parents and their children and continues later with peers and in more structured interactions with teachers. I chose therefore to focus in this article on

developmental aspects of cognitive education processes carried out informally within the family system. More specifically, the focus is on mediated learning experience (MLE) interac-tions (e.g., Feuerstein, Feuerstein, Falik, & Rand, 2002; Feuerstein, Rand, & Hoffman, 1979) and their effects on children’s cognitive modifiability. A growing body of theory and research in the last three decades supports the crucial role of active parental and peer mediation in enhancing children’s cognitive development (Belsky, Goode, & Most, 1980; Berk & Spuhl, 1995; Bornstein & Tamis- LeMonda, 1990; Bradley & Caldwell, 1984; Clarke-Stewart, 1993; Cristofaro, & Tamis-LeMonda, 2012; Klein, 1996; Laosa, 1980; Parker, Boak, Griffin, Ripple, & Peay, 1999; Ramey, Farran, & Campbell, 1979; Rodriguez et al., 2009; Tamis-LeMonda,

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Bornstein, & Baumwell, 2001; Tzuriel, 1996, 1999, 2001; Vygotsky, 1978; Wachs, 1992). Grap-pling with the specific mediational strategies that enhance children’s thinking skills and cognitive processes, researchers suggested various parents’ behaviors such as distancing (e.g., Siegel, 1982), scaffolding (e.g., Wood, 1989; Wood, Bruner, & Ross, 1976), responsive-ness (e.g., Bornstein, Azuma, Tamis-LeMonda, & Ogino, 1990; Bornstein & Tamis-LeMonda, 1990; Vibbert & Bornstein, 1989), and MLE (Feuerstein et al., 2002; Klein, 1988, 1996; Tzuriel, 1999, 2001, 2011a, 2011b). Children’s outcome criteria also varied along a continuum from specific behaviors (e.g., gazing behavior) to general thinking skills (e.g., reasoning, metacog-nitive competence, cognitive plasticity, cognitive modifiability).

The purpose of this article is to focus specifically on the theory of MLE as a proximal factor of cognitive modifiability (Feuerstein et al., 1979) and present empirical validation for the role of MLE strategies in parent2child and peer interactions in enhancing children’s cognitive modifi-ability. In the first section of this article, I will provide some definitions of the main concepts and describe briefly the MLE theory. In the second section, I will discuss selected research findings demonstrating the impact of MLE strategies in facilitating cognitive modifiability. In the third section, some conclusions will be discussed, followed by suggestions for future research.

THEORETICAL FOUNDATIONS OF MEDIATED LEARNING EXPERIENCE

Definitions of Mediated Learning Experience and Cognitive Modifiability

MLE processes describe a special quality of interaction between a mediator and a learner (Feuerstein et al., 1979; Tzuriel, 2002, 2011a). In this qualitative interactional process, parents or substitute adults or peers interpose themselves between a set of stimuli and the developing human organism (learner) and modify the stimuli for him or her (Tzuriel, 1999, 2001). MLE processes are considered as the proximal factor that explains cognitive modifiability. Cogni-tive modifiability is defined as the individual’s propensity to learn from new experiences and learning opportunities and to change one’s own cognitive structures. Feuerstein et al. (1979) MLE theory is in some aspects similar to Vygotsky’s (1978) concepts of the zone of proximal development and internalization and the concept of scaffolding (Wood et al., 1976), which have captured the interest of many developmental psychologists and educators (e.g., Rogoff, 1990; Valsiner, 1988; Wertsch, 1985).

The Mediated Learning Experience Theory

A basic assumption of MLE theory is that individuals learn by way of two main modalities: direct exposure to stimuli and MLE (see model in Figure 1). Direct exposure is characterized

FIGURE 1. The mediated learning experience (MLE) model. S 5 stimuli; H 5 human; O 5 organism; R 5 response. From You love me . . . don’t accept me as I am by Feuerstein, R, Rand, Y. & Feuerstein, R. (2006). Copyright by International Center for Enhancement of Learning Potential. Reprinted with permission.

S H O H R

MLE and Cognitive Modifiability 61

by unmediated encounters of individuals with stimuli in the environment. In Figure 1, the top and bottom arrows from the stimuli (S) to the organism (O, learner) represent the direct exposure. In MLE interaction, on the other hand, learning is carried out by means of an ex-perienced adult, usually the parent, who interposes himself or herself between the child and the world of stimuli. This is represented by arrows directed from the S to the H (human) and from the H to the O. The mediator (H) modifies the stimulus in various ways and presents it to the child (O) so that it can be registered efficiently. The mediator presents stimuli to the chil-dren by modifying their frequency, order, intensity, and context; by arousing in the children curiosity, vigilance, and perceptual acuity; and by trying to improve and/or create in the child the cognitive functions required for temporal, spatial, and cause–effect relationships.

Parents mediate to their children not only the external stimuli but also their own responses to the stimuli. This is represented by the arrows from the child (O) and his or her own response (R). Mediational processes are complex, circular, and depend not only on parental characteristics but also on children’s cognitive strengths and deficits, motivational orienta-tion, emotional needs, behavioral tendencies, stimulus characteristics, and situational condi-tions. It should be emphasized that the H is elastic; it expands (i.e., mediation is enhanced) or shrinks (i.e., withdrawal of mediation) as a function of the child’s level of understanding and of situational variables that determine task difficulty.

The MLE processes are gradually internalized by the child and become an integrated mechanism of change within the child. Adequate MLE interactions facilitate the development of various cognitive functions, learning sets, mental operations, strategies, and need systems. The internalized MLE processes allow developing children later on to use them indepen-dently, to benefit from learning experiences in diverse contexts, and to modify their cognitive system by means of self-mediation. The more the child experiences MLE interactions, the more he or she is able to learn from direct exposure to formal and informal learning situa-tions, regardless of the richness of stimuli they provide.

Lack of MLE may be derived from two broad categories: (a) lack of environmental oppor-tunities for mediation and (b) inability of the child to benefit from mediational interactions, which are potentially available. In the first case, lack of mediation derives from parents’ low educational level, traumatic life events, lack of parents’ awareness to the importance of me-diation, and lack of knowledge and/or sophistication in applying MLE strategies. In the sec-ond case, children might suffer from physical and/or mental disabilities that act as barriers to register mediation offered to them.

Feuerstein et al. (1979) conceived MLE interactions as a proximal factor that explains indi-vidual differences in learning and cognitive modifiability. Factors such as organic deficit, poverty, socioeconomic status (SES), and emotional disturbance are considered to be distal factors, that is, factors that might correlate with learning ability, but which affect the child through the proxi-mal factor of MLE. Feuerstein and Feuerstein (1991) suggest 12 criteria of MLE, but only the first three are conceived as necessary and sufficient for an interaction to be classified as MLE: intentionality and reciprocity, meaning, and transcendence (see description in the following text). These three criteria, which are responsible for the individual’s cognitive modifiability, are also considered to be universal and can be found in all races, cultures, ethnic groups, and socioeco-nomic strata. Mediation does not depend on the language modality or content and can be carried out by gestures, mimicry, and verbal interaction, provided that the three major criteria are pres-ent. The other criteria are task dependent; strongly related to culture; and reflect variations in cognitive styles, motivation, type or content of skills mastered, and the structure of knowledge.

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The first five MLE criteria were operationalized and observed in interactions of mother–child (e.g., Klein, 1988, 1991, 1996; Klein, Weider, & Greenspan, 1987; Lidz, 1991; Tzuriel, 1999, 2001, 2011a), peer-assisted learning (e.g., Tzuriel & Shamir, 2007, 2010), siblings (Klein, Zarur, & Feldman, 2002; Tzuriel & Hanuka-Levy, 2012; Tzuriel & Rokach, 2009), and teach-er–student instruction (e.g., Remer & Tzuriel, 2011; Tzuriel & Gross, 1992; Tzuriel, Kaniel, Zeliger, Friedman, & Haywood, 1998). The first five MLE criteria that were operationalized for research are as follows:

(a) Intentionality and reciprocity refers to a mediator’s deliberate efforts to change a child’s attention, awareness, perception, processing, or reaction. Mediation for intentional-ity alone is inadequate without the child’s reciprocity. Reciprocity is defined when the child responds vocally, verbally, or nonverbally to the mediator’s behavior. For instance, intentionality and reciprocity are observed when a caregiver intentionally offers a toy to a child or verbally focuses a child’s attention on some aspect of the environment and the child undeniably responds. This criterion is considered crucial for the “ignition” of the mediation process and later on for the development of feelings of competence and self-determination.

(b) Mediation of meaning refers to a mediator’s response that conveys the affective, moti-vational, and value-oriented significance possessed by the presented stimuli. This can be expressed verbally by enlightening the present context; relating it to other events; and emphasizing its importance and value, or nonverbally by facial expression, tone of voice, repetitious actions, and rituals. According to MLE theory, children who experi-ence mediation of meaning will actively connect future meanings to new information rather than passively wait for meaning to appear.

(c) Mediation of transcendence refers to interactions in which the mediator provides both the immediate or concrete needs of the children and attempts to reach additional goals that are beyond the specific situation or activity. In mother–child interactions, the mother may go beyond the specific experience by teaching strategies, rules, and principles to generalize to other situations. For instance, in a play situation, the mother may mediate the rules and principles that direct a game and generalize them to other situations. Mediation for transcendence depends on the first two criteria, intentionality/reciprocity and meaning, although the combination of all three crite-ria enhances the development of cognitive modifiability and expands the individual’s need system.

(d) Mediation of feelings of competence is observed in interactions in which a mediator con-veys to a child that he or she is capable of functioning both successfully and inde-pendently. The mediator may organize the surroundings to supply opportunities for success, interpret them to the child, and reward attempts to master the situation or deal with problems efficiently.

(e) Mediation of control behavior refers to interactions in which a mediator regulates a child’s reaction, depending on the child’s reactive style and the task demands. The mediator may either reduce impulsivity or accelerate the child’s behavior. Control of behavior can be mediated in various ways such as arousing awareness to task char-acteristics and suitable responses, analyzing the task components, modeling of self-control, and providing metacognitive strategies.


An integrative component of the MLE approach is related to the conceptualization of the developing individual as an open system that is modified by mediating agents. This compo-nent has led to both theoretical elaboration of dynamic assessment (DA) of learning potential (Feuerstein et al., 2002; Tzuriel, 2001) and development of an applicative system of measur-ing cognitive modifiability (Embretson, 1992; Haywood & Tzuriel, 1992; Lidz & Elliott, 2000; Sternberg & Grigorenko, 2002; Tzuriel, 1997, 2001, 2012). The term DA refers to an assess-ment of thinking, perception, learning, and problem solving by an active teaching process aimed at modifying cognitive functioning.

MEDIATED LEARNING EXPERIENCE AND COGNITIVE MODIFIABILITY: SCIENTIFIC RESEARCH

Methodological Aspects

Observation of Mediated Learning Experience Processes. Research on MLE processes and cognitive modifiability has been carried out using both observation techniques and a DA procedure. Usually, the interaction has been videotaped and analyzed later by trained observ-ers using the observation of mediation interaction (OMI; Klein et al., 1987). Klein (1988) has preferred to assess the quality of mother–child interaction by a macroanalytic rather than by a microanalytic approach. For example, when a parent focuses the child’s attention on some aspects of a stimulus (handing an object to a child), it has been coded as behavior reflecting focusing only if it was reciprocated by the child’s response. Whenever the parent made an attempt to generalize a rule, suggest a concept, or a principle that goes beyond the concrete-ness of the situation, it is coded as expanding regardless of the specific content being con-veyed. The basis of Klein’s observation system is an interaction “event” that might contain one or more MLE criteria.

An advantage of the MLE molar observational approach is its allowance of the identifica-tion of meaningful patterns of continuity in parents’ behavior across a developmental dimen-sion. Sroufe (1995) mentioned that understanding of continuity in child development is not characterized by mere additions of behavioral components but rather on transformations and epigenesis. The qualitative characteristics of the MLE observation approach allow comparison of similarities in behavioral patterns across generations and coincide with other patterns such as emphasis on holism and the need to look at the meaning of behavior within a psychologi-cal context rather than as isolated events (Santostefano, 1978; Sroufe, 1995; Sroufe & Waters, 1977). One of the basic assumptions behind the OMI is that observation of MLE processes in a seminatural experimental context reflects the spontaneous MLE processes at home. This assumption has been supported in several studies (e.g., Klein, 1988; Klein & Aloni, 1993). In my own studies, dyads of mothers with their children (or peers or siblings) were videotaped during free-play and/or structured situations and analyzed later by the OMI. Each dyad was videotaped in a seminatural context of an adjunct room of the kindergarten or in the child’s home; both places were familiar to children and their mothers. In the free-play condition that took 15 min, sets of games and play materials were placed on the table. The only instruction to the mother was “you can play in whatever way you want with your child during the next 15 min, try to do as you are used to at home.” In the structured situation, the dyad was given one or two problem-solving tasks, which the mother had to teach her child. The tasks were composed of teaching analogies, picture arrangement, and/or inferences; all tasks were not

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related to the tasks used in the DA procedure. In other words, the tasks used for the interac-tions required similar inductive processes as in the DA tasks given later but were composed of different content. It should be emphasized that while the tasks were explained to the mothers, no directions were given about how to teach the child. The OMI was found as strongly reli-able as measured by interrater reliability and as a robustly valid in many studies (Klein, 1996; Tzuriel, 1999). A summary of interrater reliability coefficients compiled from 12 samples is presented in Table 1. As can be seen in Table 1, the interrater reliability coefficients across the samples are high and significant.

Measuring Cognitive Modifiability. Cognitive modifiability was measured in most studies by DA, which allows recording of change criteria. The conceptualization behind using change criteria as predicted outcome of MLE interaction is that interactions by which the child is mediated how to process information are more closely related to measures of modifiability than they are to standardized static measures of intelligence. The mediational strategies used within the DA procedure have more “matching value” to learning processes in other life con-texts than do conventional static methods and therefore give better indications about future changes of cognitive structures. Accumulating evidence from educational research provides indications that a score reflecting individual differences in “modifiability” added substantially to the predictive power of learning (Embretson, 1992) and future academic success (Haywood & Lidz, 2007; Sternberg & Grigorenko, 2002; Tzuriel, 2000a, 2000b; Tzuriel, Kaniel, Kanner, & Haywood, 1999).

Use of Structural Equation Modeling to Validate the Mediated Learning Experi-ence Theory. A comprehensive venue for data analysis used in many studies is the structural equation modeling (SEM) analysis. The use of SEM for the validation of MLE theory seems to be a promising approach because we can design complex models and infer causal relations among variables without having to use experimental designs. Also, the nature of the variables involved in testing the theory are not always given to experimental manipula-tions, and the accumulated effects that several variables have on outcome variables are not easily given to manipulate simultaneously. The holistic approach used in SEM contributes to understanding of the conceptual whole more than the sum of fragmentary separate analy-ses. The SEM analysis is considered in the literature to support causal inferences (Joreskog & Sorbom, 1984) and was found as useful statistical tool in MLE strategies and cognitive modifiability research.

A summary of characteristics of studies relating MLE interactions to cognitive modifiability is presented in Table 2. The studies in Table 2 are limited only to those in which MLE interac-tions were observed and analyzed using the OMI, and cognitive modifiability was examined using DA measures for young children (i.e., K-Grade 3). In most studies, the focus was on mother–child interactions, whereas in other studies, mediation was examined also with peers (Shamir & Tzuriel, 2004; Tzuriel & Caspi, 2010) and siblings (Tzuriel & Hanuka-Levy, 2012; Tzuriel & Rokach, 2009).

The most striking finding emerging from Table 2 is that in 9 out of 12 studies, the strategy that has emerged as most powerful in predicting cognitive modifiability was mediation for transcendence (expanding)—a finding that will be discussed later.

In the following text, I will present some studies demonstrating the relation between parent–child MLE interactions and cognitive modifiability and the effects of intervention for peer mediation on cognitive modifiability. Because of space limitation, only example studies are presented.


TAB

LE 1

. R

elia

bilit

y C

oeffi

cien

t of

Med

iate

d Le

arn

ing

Exp

erie

nce

Cri

teri

a U

sin

g th

e O

bser

vati

on o

f M

edia

tion

In

tera

ctio

n

Tzu

riel

&

Tzu

riel

&

Tzu

riel

, Kan

iel,

Tzu

riel

Tz

uri

el

Tzu

riel

&

Tzu

riel

&

Tzu

riel

&

K

lein

E

rnst

W

eiss

Z

elig

er, F

ried

man

, &

Wei

tz

& W

eitz

G

eraf

y Sh

omro

n

Rok

ach

M

LE C

rite

ria

(198

8)

(199

0)

(199

8)

& H

ayw

ood

(199

8)

(199

8)

(200

8)

(199

8)

(200

9)

(200

9)

Inte

nti

onal

ity

.9

1***

.5

4 .4

2 .7

5**

.95*

**

.95*

**

.90*

**

.91*

**

.97*

**

& r

ecip

roci

ty

Mea

nin

g .8

7**

.85*

* .7

3*

.78*

* .8

6**

.86*

* .8

5***

.9

0***

.9

9***

Tran

scen

den

ce

.84*

* .8

0**

.83*

* .9

8***

.8

6**

.86*

* .5

3 .9

5***

.9

6***

Feel

ings

of

.92*

**

.87*

* .9

4***

.8

0**

.86*

* .9

5***

.5

8 .9

3***

.9

7***

co

mpe

ten

ce

Reg

ula

tion

of

.87*

**

.55

.85*

* .8

1**

.95*

**

.85*

* .8

3**

.92*

**

.95*

**

beh

avio

r

MLE

tota

l .8

9***

.9

3***

.9

3***

.9

4***

.8

5**

.89*

**

.72*

* .9

2***

.9

7***

MLE

5 m

edia

ted

lear

nin

g ex

peri

ence

.*p

, .0

5. *

* p

, .0

1. *

**p

, .0

01.

66 TzurielTA

BLE

2.

Stud

ies

on M

edia

ted

Lear

nin

g E

xper

ien

ce S

trat

egie

s an

d C

ogn

itiv

e M

odifi

abili

ty

Stu

dyG

rade

Age

nC

har

acte

rist

ics

Dya

dD

A T

ests

An

alys

isM

LE S

trat

egie

s E

xpla

inin

g C

ogn

itiv

e M

odifi

abili

ty

Tzu

riel

& E

ran

(199

0)K

5–6

47

Typi

cal

Mot

her

–ch

ildC

ITM

Reg

ress

ion

MLE

tota

l

Tzu

riel

& E

rnst

(199

0)K

5–6

48

Typi

cal

Mot

her

–ch

ildC

AT

MSE

MTr

ansc

ende

nce

Tzu

riel

& W

eiss

(199

8)2

7–8

54

Typi

cal

Mot

her

–ch

ildC

ITM

SEM

Tran

scen

den

ceR

egu

lati

on o

f be

hav

ior

Tzu

riel

& H

atzi

r (2

002)

K5–

6 6

0Ty

pica

lM

oth

er–c

hild

1

fat

her

–ch

ildC

AT

M c

ompl

exR

egre

ssio

nTr

ansc

ende

nce

Inte

ntio

nalit

y an

d re

cipr

ocity

Tzu

riel

& W

eitz

(199

8)3–

45–

8 5

6LB

W 1

NB

WM

oth

er–c

hild

CA

TM

com

plex

fi

gure

Reg

ress

ion

Tran

scen

den

ce

Reg

ula

tion

of

beh

avio

r

Tzu

riel

& W

eitz

(200

8)3–

49–

10 8

5LB

W 1

NB

WM

oth

er–c

hild

An

alog

ies

(CM

B)

com

plex

figu

reR

egre

ssio

nTr

ansc

ende

nce

Tzu

riel

&

Shom

ron

(200

9)2–

47–

1010

0LD

Mot

her

–ch

ildA

nal

ogie

s (C

MB

)SE

MTr

ansc

ende

nce

Tzu

riel

& B

etta

n (2

010)

K5–

6 7

2A

DH

DM

oth

er–c

hild

An

alog

ies

(CM

B)

SEM

Tran

scen

den

ce

Tzu

riel

&

Rok

ach

(200

9)9–

10 9

0Ty

pica

lSi

blin

gsA

nal

ogie

s (C

MB

)SE

MTr

ansc

ende

nce

Tzu

riel

& C

aspi

(201

2)3

8–9a

100

Typi

cal

Mot

her

–ch

ild

1 p

eers

An

alog

ies

(CM

B)

Seri

a-T

hin

kM

AN

OV

A

Reg

ress

ion

Tran

scen

den

ce

DA

5 d

ynam

ic a

sses

smen

t; M

LE, m

edit

ated

lear

nin

g ex

peri

ence

; K 5

kin

derg

arte

n; C

ITM

5 C

hild

ren’

s In

fere

nti

al T

hin

kin

g M

odifi

abili

ty; C

AT

M 5

Ch

ildre

n’s

An

alog

ical

Th

inki

ng

Mod

ifiab

ility

; SE

M 5

str

uct

ura

l equ

atio

n m

odel

ing;

LB

W 5

low

-bir

th w

eigh

t; N

BW

5 n

orm

al b

irth

wei

ght;

CM

B 5

Cog

nit

ive

Mod

ifiab

ility

B

atte

ry; L

D 5

lear

nin

g di

sabl

ed; A

DH

D 5

att

enti

on d

efici

t/h

yper

acti

vity

dis

orde

r; M

AN

OV

A 5

mu

ltiv

aria

te a

nal

ysis

of

vari

ance

.a A

ge o

f ol

der

sibl

ing.


Mother–Child Mediated Learning Experience Interactions and Children’s Cognitive Modifiability

The main objectives of the studies reported in the following text were (a) to validate the relationship between MLE processes and children’s cognitive modifiability and especially the relative strength of distal and proximal factors (MLE) in predicting cognitive modifiability and (b) to find the specific combination of MLE strategies that best predicts cognitive modifiability.

A major finding repeated in almost all studies was that children’s postteaching scores on DA measures were better predicted by MLE in mother–child interactions than by static test scores (or preteaching DA scores). In our first study, a sample of kibbutz mother–child dyads (N 5 47) was observed in a free-play situation for 20 min (Tzuriel & Eran, 1990). The kibbutz young children (22 boys and 25 girls, age range 5 4:7–7:8 years) were then adminis-trated the Raven’s Colored Progressive Matrices (CPM; Raven, 1956) and the Children’s Inferential Thinking Modifiability (CITM; Tzuriel, 1992) test. Three scores are derived from the CITM: preteaching, postteaching, and gain. In a series of three stepwise regression analyses, the CPM and MLE total scores were assigned as predictors of the preteaching, postteaching, and gain scores, respectively. The findings revealed that the preteaching (static) was predicted only by the CPM (R 5 .40, p , .004); the postteaching was predicted by both MLE total and CPM scores (R 5 .69, p , .002); and the gain was predicted only by MLE total score (R 5 .43, p , .001). The preteaching score was predicted only by the CPM scores because both tests are actually conventional static tests. This result verifies what is commonly known: the common variance of two cognitive tests is higher than the common variance of a cognitive test with an observed behavior (i.e., MLE in mother–child interactions). The postteaching score seems to be composed of two components: the previously acquired inferential skills as manifested in children’s preteaching performance and what has been learned as a result of mediation given by the examiner in the teaching phase of the DA procedure. It is plausible to assume that the first component (preteaching score) is attributed to the CPM score, and the second component (postteaching score) to the MLE total score. When the gain scores were taken as the criterion variable, only MLE total score emerged as a significant predictive variable. This predictability pattern across the three regression analyses is quite intriguing because it shows that the more the criterion score was saturated with teaching effects, within the testing DA procedure, the higher was the variance explained by MLE in mother–child processes.

The SEM analysis approach was applied in a series of six studies (Bettan & Tzuriel, 2007; Tzuriel & Ernst, 1990; Tzuriel & Rokach, 2009; Tzuriel & Shomron, 2009; Tzuriel & Weiss, 1998; Weitz & Tzuriel, 2007); because of space limits, only two studies are presented here in detail. In the first study by Tzuriel and Ernst (1990), we observed a young sample of kin-dergarten children (N 5 48) and their mothers and tested the children with the Children’s Analogical Thinking Modifiability (CATM) test (Tzuriel & Klein, 1985). In the second study by Tzuriel and Weiss (1998), we observed a sample of children in Grade 2 (7–8 years old, N 5 54) and their mothers and tested the children with the CITM test. Both the CATM and CITM are DA tests of learning potential. In both studies, we used the SEM approach to test a theoretical model of the effects of distal and proximal factors on cognitive modifiability. Figures 2 and 3 describe the findings of the SEM of Tzuriel and Ernst and of Tzuriel and Weiss, respectively. The two studies are different in the set of distal variables used, the age of subjects, and the DA tests used (see Table 1).

68 Tzuriel

The findings in Figure 2 show that the MLE criteria of transcendence predicted the CATM postteaching score more than did children’s static test score (i.e., the CPM administered in a standard way). As can be seen in Figure 2, the MLE criterion of meaning predicted the preteaching score, whereas the MLE criterion of transcendence predicted the postteaching score. Mediation of meaning, which involves labeling of information, was crucial for first encounters with information such as the analogies presented to children in the CATM pre-teaching phase. Mediation for transcendence, on the other hand, was found to be important when performance depends on learning of abstract rules, cognitive strategies, and principles such as those taught in the teaching phase and later tested in the postteaching phase. The authors explained the results in that the children whose mothers used high level of mediation for meaning internalized this mechanism of mediation and therefore performed better on

FIGURE 2. Structural equation analysis—effects of distal factors (mother’s socioeconomic level and intelligence) and proximal factors (mediated learning experience [MLE] strategies) on children’s cognitive modifiability. SES 5 socioeconomic status; CATM 5 Children’s Analogical Thinking Modifiability. From “Mediated learning experience and structural cognitive modifiability: Testing of distal and proximal factors by structural equation model” by D. Tzurel and H. Ernst, 1990, International Journal of Cognitive Education and Mediated Learning, 1, 119–135. Copyright 1990. Reprinted with permission.

.53

.47

.67

.49

.72

.55

.76

.30

MLE CRITERIA

RAVENCHILD

CATMPOST

CATMPRE

a

b

SES

RAVENMOTHER

INTENTIONALITY&

RECIPROCITY

MEANING

TRANSC-ENDENCE

FEELINGSOF

COMPETENCE

REGULATIONOF

BEHAVIOR

1

2

3

4

5

.78


the preteaching phase. Children whose mothers used a high level of mediation for transcen-dence internalized this specific mechanism and used it later in other learning contexts. These results support the “specificity” (Wachs, 1992) of the MLE criteria as predictors of cognitive outcomes.

One of the striking findings shown in Figure 2 is related to the causality paths between the distal and proximal factors as conceptualized by the MLE theory. None of the exogenic (distal) factors (i.e., mothers’ intelligence and SES) explained the children’s cognitive modifiability as represented by the postteaching CATM score. The exogenic (distal) factor of SES, however, explained four of the mothers’ MLE strategies: intentionality and reciprocity, meaning, tran-scendence, and feelings of competence; the higher the SES level of the mother, the higher her mediation scores. Mothers’ intelligence, as measured by the Raven’s CPM (Raven, 1956), on the other hand, did not explain any of the MLE strategies.

Tzuriel and Weiss (1998) reported similar findings by using a different DA measure (the CITM) for a different sample (older children in Grade 2, 7–8 years old) and a different set of distal factors. All the children were videotaped interacting with their mothers in free-play and

FIGURE 3. Structural equation analysis—effects of distal factors (mother’s acceptance/rejection and children’s personality orientation) and proximal factors cognitive modifiability. From “Cognitive modifiability as a function of mother–child mediated learning strategies, mothers’ acceptance–rejection, and children’s personality,” by D. Tzuriel and S. Weiss, 1998, Early Development and Parenting, 7(2), 79–99. Copyright 1998. Reprinted with permission.

.19*

.28*

.29*

.55*

.18*

�.21*

.37*

�.24*

�.19*

.19*

.31*

.33*

Rc�

.67*

**R

c�.5

9***

G.O.F �.98 A.G.O.F �.98 R.M.S.R �.04 �2 �6.17 df �12 p �.90

*p � .05, **p � .01, ***p � .001

MOTHER’SEMOTIONALREJECTION

MOTHER’SPHYSICALREJECTION

CHILD’SOUT-

DIRECTEDBEHAVIOR

CHILD’SINNER-

DIRECTEDBEHAVIOR

INTENTIO-NALITY

&RECIPROCITY

MEANING

TRANSC-ENDENCE

FEELINGSOF

COMPETENCE

REGULATIONOF

BEHAVIOR

CITMPOST

CITMPRE

70 Tzuriel

structured situations, and the interactions were analyzed with the OMI. A model of distal and proximal factors was constructed to explain causal paths among distal (e.g., mothers’ accep-tance–rejection and children’s personality orientation) and proximal factors (MLE strategies) and between the proximal factors and cognitive modifiability defined by the postteaching score of the CITM.

The findings in Figure 3 show that MLE strategies of transcendence and regulation behavior explained the children’s postteaching score but not the preteaching score. Both MLE criteria reflect a typical mother–child interaction in which the mother is involved in mediat-ing rules and principles (transcendence) and monitoring the flow of the children’s behavior (regulation). The findings become even clearer when we compare the MLE criteria to task analysis of the CITM problems. Successful performance of the CITM problems requires a systematic exploration, planning behavior, hypothetical thinking, applications of cognitive rules, and generalization of principles. These cognitive functions (Feuerstein et al., 1979) are perceived to be dependent not only on adequate internalization of general mediational pro-cesses but also more specifically on self-regulation and application of generalized principles and rules—cognitive processes that correspond to the MLE criteria found to be predictive of cognitive modifiability. It seems that these two MLE components, acquired during normal mother–child interactions, were assimilated by the children and equipped them with the thinking tools and mechanisms that are required later in other tasks and learning settings. When similar mediation for transcendence and regulation of behavior are provided in other learning situations, these children can retrieve their previous mediational experiences, apply them efficiently with different tasks, and modify their cognitive structures.

Similar to the earlier study (Tzuriel & Ernst, 1990), the distal factors in the second study did not explain cognitive modifiability as represented by the CITM postteaching score (see Figure 3). The distal factors however explained, as expected, the MLE strategies. Mothers’ emotional rejection explained their mediations for intentionality and reciprocity (.19) and for meaning (2.21), and mothers’ physical rejection explained their mediation for feelings of com-petence (.18). As can be seen from the direction of the relation, the more rejection the mother expresses, the higher she mediates for intentionality and responsiveness and feelings of com-petence, but the lower are her mediations for meaning.

The children’s out-directed behavior (e.g., aggression) explained positively four MLE cri-teria: intentionality and reciprocity, meaning, transcendence, and control of behavior. These findings indicate that the higher the children reveal aggression or hostility toward others, the more mediation they receive from their mothers. In contrast, the children’s inner-directed behavior (e.g., withdrawal, apathy, negative self-adequacy) negatively predicted the mothers’ MLE strategies. The more the child is characterized by inner-directed behaviors, the less the mother mediates feelings of competence (2.24) or control of behavior (2.19). The specificity of the results, especially the opposite predictions of MLE criteria by children’s inner- versus out-directed behaviors, are of great theoretical and practical importance. It seems that the inner-directed child is “penalized” twice, first for having a nonadequate personality orienta-tion and second by getting less mediation from the mother.

The overall results of the two SEM analyses reported previously are congruent with MLE theory, according to which proximal factors explain individual differences in children’s cognitive functioning, whereas distal factors (i.e., SES level, child’s personality, mother’s acceptance–rejection of the child) do not have a direct effect on children’s cognitive factors, although they do explain some of the proximal factors.


In contradiction to the MLE theory, in two studies, distal factors were found as directly predicting cognitive modifiability; the samples in both studies were composed of children with learning and behavioral difficulties. For example, in the Bettan and Tzuriel (2007) study carried out on kindergarten children with attention deficit/hyperactivity disorder (ADHD), two proximal factors (i.e., MLE strategies in a structured teaching situation) predicted, as ex-pected, cognitive modifiability: mediation for meaning (b 5 .26) and mediation for transcen-dence (b 5 .46). However, unexpectedly, two distal factors also explained directly the children’s cognitive modifiability: severity of the ADHD (b 5 2.26) and mother’s socioeconomic level (b 5 .46). The meaning of these findings is that the higher the severity of the child’s ADHD and the lower the mother’s socioeconomic level, the lower is the cognitive modifiability of the child. Similarly, in Tzuriel and Shomron’s (2009) study on children with learning disabil-ity, one distal factor: Home Observation for Measurement of the Environment (HOME; Bradley, Caldwell, Rock, Hamrick, & Harris, 1988) was found as directly explaining cognitive modifi-ability (b 5 .60) together with a combined score of four mediation strategies (b 5 .41). These empirical findings raise the question whether, with children experiencing learning difficul-ties, the distal factors might also influence directly the child’s cognitive modifiability, a finding that contradicts the MLE theory. A possible explanation for these findings might be related to the sample characteristics. It might be that in samples of children with learning difficulties (e.g., ADHD, learning disabled [LD]), even the best mediation, given naturally by mothers, is not enough to overcome or “nullify” the strength of the distal factor. In other words, the moth-ers of children with learning difficulties, who were observed during spontaneous interactions with their children, had no prior training for mediation. It is plausible to assume that should mothers receive training for higher level of mediation, the effects of the distal factors would be reduced significantly or disappear. Our findings suggest an elaboration of MLE theory. Although in typically developing children distal factors do not affect directly cognitive modifi-ability, as suggested in the theory, in samples of children with learning difficulties, a much higher level of mediation is required to overcome the effects of the distal factors. In other words, in situations where children demonstrate learning or behavioral difficulties, distal factors can directly affect cognitive modifiability. The MLE process must be more powerfully directed toward amelioration of disability when the distal factors are salient.

This specific proposition should be investigated in further research where mothers of children with learning difficulties will be assigned to experimental and control groups. Moth-ers in the experimental group will receive a program of mediation and be compared with a control group of mothers who do not receive a program. Mother–child MLE interactions should be observed a year later to assure that the effects of the program are internalized and assimilated into the mother–child interactional system. The children should then be tested by cognitive modifiability measures. My expectation is that distal factors will directly affect children’s cognitive modifiability in the control group but will be significantly lower or disap-pear in the experimental group.

INTERVENTION FOR PEERS MEDIATION AND CHILDREN’S COGNITIVE MODIFIABILITY

Recent research of peer mediation showed that participation in a Peer Mediation With Young Children (PMYC) program improved children’s MLE strategies (e.g., Shamir, this issue; Shamir & Tzuriel, 2004; Tzuriel & Caspi, 2010; Tzuriel & Shamir, 2010) and enhanced their cognitive

72 Tzuriel

modifiability (Tzuriel & Caspi, 2010; Tzuriel & Shamir, 2007, 2010) and math performance (Shamir, Tzuriel, & Guy, 2007; Shamir, Tzuriel, & Rozen, 2006). Because of space limits, other programs based on the MLE approach are not included in this article, and readers are referred to the relevant research literature (e.g., Feuerstein, Rand, Hoffman, & Miller, 1980; Greenberg, 1990; Haywood, Brooks, & Burns, 1986, 1992; Samuels, Killip, MacKenzie, & Fagan, 1992; Tzuriel & Eiboshitz, 1992; Tzuriel & George, 2009; Tzuriel et al., 1999; Tzuriel et al., 1998).

The PMYC program is a relatively new peer-assisted learning model that draws on both Vygotsky’s (1978) concept of zone of proximal development and Feuerstein’s MLE theory (Feuerstein et al., 1979). The concept of peer mediation was developed recently (Shamir & Tzuriel, 2004; Shamir, Tzuriel, & Rozen, 2006; Shamir et al., 2007; Tzuriel & Caspi 2010; Tzur-iel & Shamir, 2007, 2010) following Tzuriel’s studies about the effects of mother–child MLE strategies on children’s cognitive modifiability (i.e., Tzuriel, 1999, 2001). The PMYC program is a process-oriented program designed to teach children how to mediate effectively irrespective of the mediated content. The PMYC has three main objectives: (a) to enhance a mediating teaching style, (b) cognitive modifiability of tutors, and (c) to facilitate performance and learn-ing skills of young children who are mediated by their experienced tutor peers. The principal assumption is that teaching for peer mediation will both elicit better mediating skills from the tutors and improve cognitive skills in both tutees and tutors. The mediation skills acquired and internalized as a result of the intervention will enable children to apply them in future learn-ing contexts, whether when teaching peers or being exposed to new learning experiences.

The PMYC program is characterized by five main points: (a) it combines cognitive and emo-tional components, (b) it is focused on “learning how to learn” strategies and metacognitive principles, (c) it transcends content domains and contexts of learning, (d) it determines clearly the mediator’s status; the mediator’s status is higher than the learner’s status. The mediator, as a more experienced person who has learned how to mediate, has an active modifying role in the interaction; and (e) the mediation procedures used are not only structured and theoretically guided but also contain creative ways to promote intersubjectivity (Newson & Newson, 1975). The PMYC has three classical components: direct teaching, demonstration, and practice. Direct teaching includes presentation and explanation of the basic mediated learning principles. Demonstration includes observation and discussion of a didactic movie. The movie demon-strates mediation processes using the mediated learning criteria and specific components (i.e., empathy, respect) for peer interaction in an actual learning event. Practicing of the mediated learning principles with peers is carried out using varied means such as multimedia programs, role-playing, and the use of tasks required for later teaching activities. The PMYC consists of seven lessons (with each lesson lasting for 1 hr) given over a period of 3 weeks. Each lesson includes presentation of a mediation principle, understanding its significance in general and particularly in a peer-mediation situation, and practicing and applying the principles in varied learning situations. The program also includes didactic videotape demonstrations aimed at enhancing internalization of mediation principles and learning aids (i.e., computer programs, games, posters, stickers with the visual symbols of the principles, and work sheets).

The effects of the PMYC on MLE strategies were reported in a series of studies (Shamir & Tzuriel, 2004; Shamir et al., 2006; Shamir et al., 2007; Tzuriel & Caspi, 2010; Tzuriel & Shamir, 2010). The findings show consistently that children participating in the PMYC program dem-onstrated higher level of MLE strategies than children in control groups who received a sub-stitute program. In three studies, however, the effects of the PMYC were studied specifically in relation to cognitive modifiability, which is the focus of this article (Tzuriel & Caspi 2010;


Tzuriel & Shamir, 2007, 2010). For example, in Tzuriel and Shamir’s (2007) study, Grade 3 mediators participating in the PMYC program (experimental group, n 5 43) were compared to mediators in a control group (n 5 46) who received a substitute program. Following the intervention stage, the experimental and control children participated in a peer-mediation condition, which was videotaped for 30 min. The mediators were instructed to assist their young counterparts in solving problems based on the operation of seriation. All mediators were administered at the end of the program: the analogies subtest from the cognitive modifi-ability battery (CMB; Tzuriel 1995, 2000a). The analogies were composed of two subscales: test and transfer; the transfer subscale was composed of more difficult items than the test sub-scale in terms of number of dimensions involved and number of transformation required. The analogies, administered by adult examiners, included preteaching, teaching, and post-teaching phases. The preteaching score was taken as an indicator of the program’s effect on solving problems and the postteaching score as the mediators’ propensity to benefit from adult mediation and consequently improve their analogical performance. Repeated measures analysis of variance of treatment by time (2 3 2) was carried out on each of the analogies subscales. The findings showed significant interaction of treatment by time for the transfer subscale. The interaction portrayed in Figure 4 indicates that the experimental group not

FIGURE 4. Preteaching and postteaching scores of mediators (Grade 3) on the analogies subtest of the cognitive modifiability battery—(transfer problems) in the experimental and control groups. CMB 5 cognitive modifiability battery. From “The effects of Peer Mediation with Young Children (PMYC) on children’s cognitive modifiability,” by D. Tzuriel and A. Shamir, 2007, British Journal of Educational Psychology, 77(1), 143–165. Copyright 2007. Reprinted with permission.

0.5

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74 Tzuriel

only had higher preteaching scores (given after the intervention program) but also showed higher preteaching to postteaching improvement than did the control group. This finding supports the expectation of higher cognitive modifiability in the experimental group than in the control group. Group differences in the preteaching and postteaching phases of the analo-gies revealed that mediators in the experimental group scored higher than did mediators in the control group in both the preteaching (t[84] 5 2.41, p , .05) and postteaching (t[84] 5 3.25, p , .01) phases. These DA findings clearly indicate that mediators in the experimental group internalized the mediation principles and knew how to benefit from mediation given to them in a different context and consequently improved their performance more than children in the control group. Thus, children who learn how to mediate become not only better media-tors but also better learners, as reflected in their cognitive modifiability scores. In Vygotsky’s (1978) terms, the peer-mediation experience enabled the mediators to advance from a lower zone of proximal development (preintervention) to an upper zone of proximal development (postintervention). Later studies by Tzuriel and Caspi (2010) and Tzuriel and Shamir (2010) consistently support the earlier studies showing positive effects of participation in the PMYC on cognitive modifiability.

DISCUSSION AND CONCLUSIONS

The studies reported previously verify commonsense knowledge and theoretical concep-tualization about the role of MLE processes in enhancing cognitive modifiability. Early cognitive education, exemplified in the spontaneous family interactions, seems to affect the child’s ability to benefit from mediation offered within the family context and to gener-alize to other formal and nonformal situations. One of the intriguing findings consistently emerging in most studies is that mediation for transcendence (expanding) is the most powerful strategy predicting cognitive modifiability. This strategy has emerged as most powerful in predicting cognitive modifiability in spite of the fact that it was also found as the least frequent strategy and therefore with a limited score range. Mediation for tran-scendence reflects the mediator’s efforts to modify the abstract abilities of the child and to focus the child on concepts, generalizations, and principles. The DA measures used in all studies reflect also the ability of the child to solve problems requiring abstract concepts and rules.

The findings that distal factors in samples of children with learning difficulties ( Bettan & Tzuriel, 2010; Tzuriel & Shomron, 2009) directly predict cognitive modifiability might in-dicate a need to modify or refine the MLE theory, at least for children with learning dif-ficulties. In typically developing children, distal factors seem not to affect directly cognitive modifiability as suggested by the theory; they do affect, however, the MLE processes, which in turn affect cognitive modifiability. In samples of children experiencing severe learning dif-ficulties, the distal factors (adverse conditions) affect directly learning processes and cogni-tive modifiability. To cancel or overcome the adverse conditions effects, much more “robust” mediation efforts should be applied than the usual ones given within the typical parent–child interaction.

The refinement of MLE theory is related to the need to extend the concept of MLE to a more complex transactional–ecological model, taking into account the reciprocal nature of MLE and cognition as well as treating MLE as one component within a holistic frame-work. This is especially important because of the danger of overextending the presumed


influence of MLE and overly attributing many cognitive and noncognitive effects to MLE. Overgeneralization of MLE theory to explain too many phenomena may bring about only the devaluation of the theory. It is most important now that the effects of MLE are es-tablished so as to delineate the conceptual limits of the theory. The term “transactional” rather than “interactional” is meant to emphasize the idea of the mutual effects of MLE and cognitive functioning. Wachs and Plomin (1991) defined interaction as involving dif-ferent individuals differentially reacting to similar environments, whereas transaction implies effects that are differential both for individuals and environments. Tzuriel (1991) conceptualized interaction as characterized by relative simplicity and transience of ef-fects, whereas the transactional process is dialectically circular with a continual change and adjustment of factors. This dialectical circularity poses a real challenge for theory development and methodology, but with recent advances in technology and statistical analyses, it can be handled efficiently. We should be aware that there is a possibility that the children’s cognitive functioning might influence parental MLE strategies, and that the circular relation depends on broader family, social, and cultural contexts. Similar conceptions have been discussed in Bronfenbrenner’s (1979) ecological approach and by Super and Harkness (1986) who also proposed the concept of developmental niches. Some evidence for the effects of age, context, and severity of a child’s problems and cultural background has been reported as well (e.g., Klein, 1988; Klein & Aloni, 1993; Tzuriel & Eran, 1990; Tzuriel & Weiss, 1998; Tzuriel & Weitz, 1998). The affective and motivational processes of children and their parents are also very important as prerequisite factors in determining the nature of MLE processes, children’s cognitive modifiability, and the nature of their reciprocal effects.

The findings of peer-mediation studies indicate clearly that children in experimental groups participating in the PMYC program showed better mediational teaching style than children in control groups. An important implication of these studies is that children’s MLE strategies could qualitatively and quantitatively be improved beyond the spontaneous devel-opmental process of mediation skills. The enhancement of mediation skills was not only demonstrated with children who participated in the PYMC program but was also transferred to children who were taught by their qualified peers. The use of the MLE criteria allows us not only to design intervention for peer mediation but also to describe the nature of the mediat-ing behaviors used by children during social interactions such as peer learning or play.

The significant findings on the effects of the PMYC program on cognitive modifiability of mediators (Shamir, this issue; Shamir et al., 2006; Shamir et al., 2007; Tzuriel & Caspi, 2010; Tzuriel & Shamir, 2007, 2010) support our expectations that children who learn how to medi-ate become not only better mediators (tutors) but also better learners, as reflected in their pre-teaching to postteaching improvement on various DA measures (see Figure 4). In Vygotsky’s (1978) terms, the peer-mediation experience enabled the tutors to advance from a lower zone of proximal development to an upper zone of proximal development. It should be noted that the problems of the CMB analogies were novel to all children, so the improvement cannot be attributed to a familiarity factor. Furthermore, the PMYC program does not contain any com-ponents that are similar to the tasks used to assess the mediators’ cognitive modifiability. The significance of the greater gains of children in the experimental groups should be evaluated in relation to two facts: first, that the administered tests tap a different cognitive skill than those taught in the program, and second, that the standardized tests in most studies failed to reveal the effectiveness of the program. Application of DA as a central evaluation method

76 Tzuriel

reveals that the contribution of the cognitive education program was not simply supporting the development of a particular skill practiced during the program, it also involved teaching children how to benefit from mediation in a different setting and consequently improve their cognitive performance across other domains.

In further research, it will be important to investigate the contribution of the PMYC pro-gram or programs developed for enhancement of parents’ mediation style as compensatory programs with children coming from low-mediating families. It is conceptually important to establish the relative effects of cognitive education programs aimed at developing chil-dren’s and parents’ mediation skills on the children’s cognitive modifiability. Development of mediation programs is especially important for parents of children experiencing learning difficulties or parents who, for various reasons, lack mediation skills. Further research is also required to study the effects of mediating agents such as siblings, grandparents, and teachers on children’s cognitive level.

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Dynamic Testing and Individualized Instruction:

Helpful in Cognitive Education?

Wilma C. M. ResingDepartment of Developmental and Educational Psychology,

Leiden University, The Netherlands

An important theme in educational practice is to tailor instruction to the individual needs of children. Particular forms of group instruction may be effective for specific children; other children will profit most from a more individual approach. The contri-bution aims to focus on the question whether such tailored forms of instruction can be found in a dynamic assessment context and explores the potential usefulness of dynamic testing and instruction for cognitive education. The principal characteristic of dynamic testing or assessment is that children are explicitly provided with feedback, prompts, or training intended to enable them to show progress when solving cognitive tasks. Outcomes of dynamic testing and assessment could, in principle, provide educa-tional psychologists or teachers with information regarding learning outcomes during intervention. Although it has been claimed that such approaches may have more to offer to psychologists or educationists than traditional standardized test outputs, not all approaches are suitable for this aim. This article focuses on the potential usefulness of the outcomes of the graduated prompts approach in dynamic testing and instruction. It can be concluded that a combination of both dynamic procedures is a very promising one, which needs further exploration in the future.

Keywords: dynamic testing; cognitive education; cognitive training; dynamic instruction; inductive reasoning

COGNITIVE EDUCATION

An important theme in educational practice is to tailor instruction to the individual needs of children. Particular forms of group instruction may be effective for specific children; other children will profit most from a more individual approach (e.g., Caffrey

& Fuchs, 2007). The current contribution aims to focus on the question whether such tailored forms of instruction can be found in a dynamic assessment context and explores the potential usefulness of dynamic testing and instruction for cognitive education.

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Reigeluth and Moore (1999) define cognitive education as being “composed of a set of in-structional methods that assist students in learning knowledge to be recalled or recognized, as well as developing students’ understanding and intellectual abilities and skills” (p. 52). In these intellectual abilities and skills, they include metacognition. From this point of view, cognitive education could be seen to be equivalent to optimally child-centered (cognitive) in-struction or teaching from a learner-centered design (e.g., Quintana, Shin, Norris, & Soloway, 2006). Jeltova and colleagues (2011) describe this form of instruction as dynamic instruction, which “occurs when the teacher actively intervenes in the course of learning in order to give active feedback while the learning is taking place” (p. 382).

Active, mental exploration of the learner is required in cognitive education or dynamic instruction because methods and/or teachers are supposed to assist students in gathering information and in developing their understanding and intellectual abilities. According to, for example, Adey (2003), active thinking of the learner is a necessity for cognitive change. Before a teacher, however, is able to assist students in their learning processes in the class-room, she or he needs to know what a child is capable of and what is the child’s potential for learning. The teacher needs to learn to focus on the unique needs of learners (Quintana et al., 2006), whereby motivation, changes in cognitive and achievement skills, level of expertise, and responsiveness to certain aspects of intervention are core elements. This contribution focuses on cognitive change and individually based needs for instruction.

Given children’s unique and most of the time variable learning progression (Siegler, 1996), the provision of comparable educational opportunities for all children requires a lot from teachers (e.g., Brown-Chidsey & Andren, 2012; Glover & Vaughn, 2010). Cognitive education seems to be related to, or result from, several interwoven, complex concepts such as cognitive development, learning, efficiency of learning, assessment and testing, transfer, and teaching or training (the use of) cognitive and metacognitive abilities and skills. Cognitive education could, therefore, profit considerably from thorough understanding of the individual processes of change in children’s thinking (e.g., Siegler, 1996).

Dynamic Testing and Assessment

Criticisms of the traditional IQ test have helped to stimulate research on dynamic assess-ment and testing (for overviews, see Elliott, Grigorenko, & Resing, 2010; Grigorenko & Sternberg, 1998; Guthke, 1982; Haywood & Lidz, 2007; Lidz, 1987; Lidz & Elliott, 2000; Van der Aalsvoort, Resing, & Ruijssenaars, 2002; Wiedl, 2003). The principal characteristic of dynamic testing or assessment, in contrast to static testing or assessment, is that children are explicitly provided with feedback, prompts, or training intended to enable them to show progress when solving cognitive tasks (Elliott et al., 2010; Haywood & Lidz, 2007; Sternberg & Grigorenko, 2002).

The learning potential concept, lying behind dynamic testing and assessment, goes back to the ideas and definitions of intelligence by Binet (1908/1916) and Thorndike (in Thorndike et al.,1921) as “the ability to learn.” Recent researchers in the field of learning potential research and dynamic assessment have however been influenced more directly by either Feuerstein’s theory and subsequent development of the learning potential assessment device (LPAD) and instrumental enrichment (IE) or Vygotsky’s theory of the zone of proximal development (ZPD) including his statement that one should not just measure the level of intellectual function-ing but also detect the best instructional level for the child because “this measure gives a more

Cognitive Education: Dynamic Testing and Individualized Instruction 83

helpful clue than mental age does to the dynamics of intellectual progress” (Vygotsky, 1962, p. 103; see also Feuerstein, Rand, & Hoffman, 1979; Feuerstein, Rand, Hoffman, & Miller, 1980; Haywood & Lidz, 2007; Sternberg & Grigorenko, 2002; Vygotsky, 1978).

Binet (1908/1916) became convinced that the intelligence test he and his colleagues deve loped did not always give an appropriate picture of the child’s cognitive potential. He believed it should be possible to raise a child’s level of cognitive development depending on individually determined constraints to a higher level by means of training, particularly by teaching the child how to learn (e.g., Brown, 1985). Buckingham (as cited in Thorndike et al., 1921) pointed out that whatever intelligence is defined, “ . . . we are justified from an educational view in regarding it as ability to learn, and as measured by the extent to which learning has taken place or may take place” (p. 273). Selz (1935) concluded that it would be necessary to study the thinking process itself in detail to examine the actual intelligence of the person. Selz has described research in which children were given specific training in thinking where they were taught specific solution procedures for several problems accord-ing to the principle of the kleinstmögliche Hilfe (i.e., the smallest amount of help necessary to reach the solution).

Dynamic testing is based on the assumption that test outcomes derived after the provi-sion of some form of (individualized) intervention are more likely to provide a better indica-tion of a child’s potential level of intellectual functioning than conventional static test scores alone (e.g., Lidz & Elliott, 2000; Sternberg & Grigorenko, 2002; Wiedl, 2003). Although both learning potential tests and dynamic assessment procedures each show large differences in structure and content, they all have at least two elements in common: (a) They stress the same defining aspect of intelligence as “ability to learn”; and (b) they give children training, instruction, or individualized hints or prompts to improve their performance on problem-solving tasks. The concept of dynamic testing or assessment is generally used for describing various approaches all linked by “dynamically” providing feedback and instruction as part of an assessment procedure. This form of feedback is either fixed, that is, it is the same for all children tested, or individualized, that is, it is applied in a tailored fashion related to the child’s ongoing performance in the test situation (e.g., Elliott et al., 2010). This intervention component within the testing situation itself represents a significant departure from most conventional testing procedures, which usually prohibit any forms of (more or less individu-alized) assistance or feedback other than the strictly described test instructions, as decribed in the manual, such as task introduction and explanation, motivating the child in general, and so forth (e.g., Hessels-Schlatter & Hessels, 2009).

Intelligence

In my work on dynamic testing, Campione, Brown, and Ferrara’s (1982) definition of intelli-gence was very helpful in thinking over the dynamic testing construct: “Intelligence is the ef-ficiency of new learning, couched in terms of the ability to profit from incomplete instruction and of the intimately related ability to transfer old learning to new situations” (p. 398). This definition has close resemblance to “the ability to learn in the absence of direct or complete instruction” (Dearborn, as cited in Thorndike et al., 1921) and Binet’s (1908/1916) ability to learn. Let us assume that a child’s path of intellectual development can be defined in terms of the efficiency with which new learning occurs. This is not only a matter of the speed with which information is processed but, more importantly, is also the way in which cognitive

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activities are performed and the more or less efficient way in which the various process com-ponents are selected, sequenced, and modified. New information has to be linked to existing knowledge, and, in this whole intellectual process, self-regulatory, metacognitive skills—such as planning, monitoring the solution process, and controlling one’s own solution proce-dures—play a fundamental role (Campione et al., 1982; Resing, 1997, 2006; Sternberg, 1998). The flexibility with which these metacognitive skills can be applied must also be seen as an important aspect of intellectual functioning. Cognitive education aimed to enhance these processes of intellectual development in children must take into account and focus on these specific thinking abilities, including their large individual variability (e.g., Adey, 2003; Siegler, 2007). Outcomes of dynamic testing and assessment could, in principle, provide educational psychologists or teachers with information regarding learning outcomes during intervention. Teachers should be able to adapt their teaching processes parallel to the outcomes of dynamic testing, for example, by knowing if and how much children profit from specified forms of intervention during dynamic testing. Although it has been claimed that such approaches may have more to offer to psychologists or educationists than traditional standardized test outputs, finding ways to gather complex process-based information not only in a flexible, scientific fashion but also in a practical fashion has proven to be challenging (Bosma & Resing, 2010; Elliott, 2003; Grigorenko, 2009; Resing, Elliott, & Grigorenko, 2011).

Dynamic Assessment and Testing Related to Individual Learning Outcomes

Lidz and Elliott (2000) give in their introductory chapter of their book on dynamic assessment models an overview of several dynamic tests and assessment instruments, ranging from clin-ical and individualized intervention to very standardized, sometimes adaptive, instruction. Most dynamic assessment and testing systems aim to gauge the individual’s potential level of performance rather than what can be achieved independently (Resing & Elliott, 2011). Ongoing, individualized mediation, mostly grounded on the work of Feuerstein and col-leagues (e.g., Feuerstein et al., 1979; Feuerstein et al., 1980) often yield interesting qualitative information, assumed to be indicative of the cognitive modifiability of a child. This use of nonstandardized interventions, however, prevents solid interpretation of the results of the empirical studies that have been employed (e.g., Sternberg & Grigorenko, 2002). Further-more, both the test–retest reliability and the reliability of progress (change) measures remain questionable (Büchel & Scharnhorst, 1993) if test users do not have a protocol of how to act. Using such a form of dynamic assessment makes it, therefore, rather difficult to provide parents or teachers with transparent and objective information regarding a child’s potential for learning.

However, not every form of standardized dynamic testing is helpful in the objective search for on-the-spot learning processes during assessment as well. Budoff, for example, trained older learning disabled pupils in how to solve Koh’s Block Design Test (e.g., Budoff, 1987; Budoff & Corman, 1974). Pupils were trained in relatively large groups, with instruction on paper, and all got exactly the same, short, standardized training procedure including very strict task-specific hints. Although the trained pupils did show more progression in their solv-ing behavior than untrained pupils, the test scores after training do not fully provide us with information regarding the individual learning steps and processes of the group members. Participants in the dynamic test could, based on their learning progression, be categorized in groups as learners, nonlearners, and high scorers, but it is questionable if this labeling will


give teachers enough information to build their cognitive education upon. Besides, progres-sion in skills as a consequence of training tells us that some learning has taken place but does not give insight in the learning process and progression itself.

In other formats of dynamic testing, children are typically provided with feedback, prompts, or training geared to enable them to show individual differences in their progress when solving cognitive tasks. The Adaptive Computer Assisted Learning Test Battery (Guthke & Beckmann, 2000), for example, makes use of standardized sets of prompts and indicates learning progress during the test, provides information regarding to five typical types of learners, and ends with an indication of the child’s potential to learn from the prompts pro-vided. Swanson’s (2000) Cognitive Processing Test makes use of standardized sets of prompts focusing on sequential processing strategies related to working memory (WM). The dynamic test provides an index of processing potential, which can be used to more accurately identify learning disabled pupils (related to reading and math).

The information delivered by dynamic tests as described previously would seem valuable as a first input for cognitive education because it might provide insights for teachers regar-ding not only the level at which the individual, or groups of children, are functioning but also the process about how children come to the right conclusions and information regarding which forms of feedback are helpful or not. Gaining information during the assessment ses-sion about how children respond to structured assistance and how their strategy use changes as a result of feedback has the potential to be considerably helpful for educators confronted by a child having difficulties in learning. However, finding ways to gather and tap this informa-tion in a scientific, standardized fashion and then provide this in a meaningful way to teach-ers to date continues to be challenging and is certainly not possible for all forms of dynamic testing or assessment (Bosma & Resing, 2008, 2010; Elliott et al., 2010; Grigorenko, 2009).

Process-Oriented Dynamic Testing

In my own research on dynamic testing, the graduated prompts approach has a central posi-tion. Graduated prompting may be seen as a dynamic testing method that is as adaptive as possible, by different forms of prompting and scaffolding, but at the same time using stan-dardized protocols for instruction. Grigorenko and Sternberg (1998) described this form of dynamic testing as primarily focused on the child’s actions rather than on task features; but of course, both elements could be combined. The standardized approach of giving prompts depending on the needs of the child is assumed to give more information on how the child solves the task problems. Research with this form of dynamic testing has shown that both the number of prompts children need and their posttest scores are good individual predictors of future school success (e.g., Caffrey, Fuchs, & Fuchs, 2008; Sternberg & Grigorenko, 2002). In line with the pioneering work of Campione, Brown, Ferrara, Jones, and Steinberg (1985), we defined the child’s potential for learning, in part, in terms of a learning criterion, for example, the minimum number of prompts needed for independently solving the test items after training. Scaffolding involves structuring all aspects of the task situation in such a way as to enable a test taker to solve task elements that could not be solved without any assistance and provided as necessary. Assistance is then subsequently reduced, at least if the child’s abil-ity to solve tasks independently increases.

The graduated prompts approach has a firm tradition in dynamic testing studies (e.g., Campione & Brown, 1987; Fabio, 2005; Ferrara, Brown, & Campione, 1986; Resing,

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1997; Resing & Elliott, 2011; Resing, Tunteler, De Jong, & Bosma, 2009). Often, these authors in their dynamic tests have included tasks that have to be solved by inductive reasoning, which can be defined as a rule-finding process that can be achieved by searching for both similarities and differences between objects being compared. Inductive reasoning is consi-dered to play a core role in cognitive development and in learning and instruction in gen-eral ( Goswami, 1996; Kolodner, 1997). It therefore seems a very important general cognitive ability to be trained in dynamic testing. In the next paragraphs, three short summaries of studies we performed in dynamic testing, including graduated prompts techniques (and scaf-folding), present our recent findings.

Dynamic Testing and Fine-Tuned Measuring of Solving Processes

In a recent study, employing the graduated prompts approach (Resing et al., 2009), we aimed to explore whether dynamic testing of indigenous and ethnic minority children could provide information concerning changes in their strategy use while solving seriation tasks (Seria-Think; Tzuriel, 2000). It was hypothesized that dynamic testing with graduated prompts and trial-by-trial-assessment could aid understanding of the development of chil-dren’s strategy use. Participants were 54 indigenous Dutch and 55 ethnic minority children with a mean age of 7.5 years. A stepwise graduated prompts training was designed in which the experimenter observed and recorded all the steps and strategies the child showed, either spontaneously or elicited during training, to solve the seriation problems. If the child could not independently solve the task, the experimenter provided the minimally needed number of prompts chosen from a predetermined standardized set of metacognitive and cognitive prompts. Trial-by-trial testing provided information of how strategy use developed during training. Children in the experimental group showed significant progression toward the employment of more advanced solving strategies. Ethnic minority children showed most strategy change during training, initially needing more prompting but progressively requir-ing less. The study provided insight into strategy use during and after training for children from the two conditions.

In a second study of inductive reasoning (Resing & Elliott, 2011), our key objective was to examine strategy use in more detail. Specifically, we sought to examine how a form of process-oriented computerized dynamic testing, using electronic tangible materials and incorporating a series of graduated prompts and scaffolding techniques, could provide insights into children’s potential for learning. Potential for learning was defined in terms of successful outcomes and strategies employed by individual children while solving com-plex inductive reasoning tasks (figural series completion). It was hypothesized that our graduated prompts approach would reveal differential changes in strategy patterns of sev-enty seven 7- to 9-year-old children and in their need for differing prompts to help them solve the problems. These two elements—it was anticipated—could identify differential potential for learning on the part of the participants. Children in the experimental group received a series of inputs consisting of a pretest, two training sessions, and a posttest, all involving series completion tasks; the controls were administered all tests but received no training. All test sessions were undertaken individually using a specially designed program incorporating an electronic console and tangible materials with sensors inside. As a conse-quence of training, children significantly outperformed controls on the series completion task. Significant individual differences were noted in terms of the children’s response to


assistance. Furthermore, dynamic testing increased analytical and reduced trial-and-error solution strategies. After training, a significant proportion of the children employed strate-gies that had been identified as optimal, although a sizeable minority still demonstrated rather idiosyncratic approaches.

In a third study (Resing, Xenidou-Dervou, Steijn, & Elliott, 2011), we again examined whether children would show different change patterns in their strategy use when adminis-tered several series completion tasks presented within a dynamic testing format using a grad-uated prompts approach with scaffolds. The same electronic console using tangible objects with sensors enabled the detailed recording of children’s responses and solution times. It was hypothesized that children who received training (i.e., who were involved in dynamic testing) would progress to more advanced strategy use than nontrained children, and that this would be evident for both verbal and behavioral measures of strategy use. We also sought to exam-ine whether more advanced strategies would be employed by children with higher levels of WM capacity. It was found that the group of dynamically tested children tended to shift their verbal strategic behavior to a more advanced level. When examining the behavioral measures, it was found that some children showed the same pattern of progression; but others, who already had performed at an advanced level in the pretest, shifted their strategy to a heuristic form. WM capacity did not appear to play an important role in differentiating between trained groups. Dynamic testing, using electronic console and tangibles with sensors, enabled us to identify strengths and weaknesses in the children’s approach to learning.

Process-oriented dynamic testing, such as that illustrated by the three studies described previously, is a challenging and complex enterprise in part because both interindividual and intraindividual differences become salient when using such a method (e.g., Siegler, 2007). Cognitive education could be built on and fine-tuned along these measures derived from pro-cess-oriented dynamic testing. These test outcomes give insight in the quantity and quality of the prompts and scaffolds children need or repeatedly need. Two children with equal static baseline scores (e.g., IQs of 85) can show differences in the number of prompts needed, in the slope with which these needs for prompts diminish, in the quality of the prompts (do they need metacognitive instruction or modeling), in their solving behavior (do they show trial-and-error solving patterns or do they analyze the task before they start; are they able to verbal-ize what they have done during problem solving), and so forth. Process-oriented instruction cannot stand alone; assessment and instruction components should be integrated, and it is important to ascertain which, individually based, forms of help children need to be able to progress beyond a certain level of learning (e.g., Ashman, 1985).

Cognitive Education: An Example of Dynamic Instruction

The goal of process-oriented assessment of the potential for learning of the child is not to close the gap permanently between the child’s current and potential functioning. This only becomes, at least partially, possible when the child participates in a much longer and much more intensive cognitive training program, for instance, one of the various “teaching-to-think” training programs such as described by, for example, Moseley et al. (2005) and Hu et al. (2011). A second approach, therefore, may involve the combination of dynamic testing with educational programs based on dynamic instruction. A study combining such results, both with a strong emphasis on standardized but dynamic instruction, is briefly described in the next section.

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Resing and Roth-Van der Werf (2002) designed a study in which dynamic testing and dynamic cognitive instruction in the classroom were combined. The relationship between assessing and training inductive reasoning skills was explored by the use of two instruments: the learning potential test for inductive reasoning (LIR; Resing, 1993, 2000) and a Dutch adapted version of the Cognitive Training Program for Children (Klauer, Resing, & Slenders, 1996). The ideas behind both instruments were similar: Both strongly emphasized the use of a graduated prompts training method with metacognitive (and transfer) aspects of training across multiple contexts, both in format and in content. The study aimed to go beyond mea-suring the latent cognitive abilities of the child. Often, one wishes to instruct teachers how to build upon these to develop the children’s potential (e.g., Grigorenko & Sternberg, 1998). Research using a combined dynamic testing and cognitive education approach appeared to offer the opportunity to gain insight into the possibilities of training children to become more advanced users of general inductive reasoning processes.

An adapted version of Klauer’s program (Klauer et al., 1996) was used, including a very detailed prescribed and standardized way of dynamic instruction. Transfer was trained with the help of paradigms. Paradigmatic transfer was supposed to occur if certain reason-ing structures, which had been taught and learned on the basis of prototypic or exemplary rules (“paradigms”), were successfully applied to other tasks. This form of transfer, how-ever, seldom occurs spontaneously (Detterman & Sternberg, 1993). Many problems related to the measurement of transfer concern the process of recognizing “problem isomorphs” (e.g., Bassok & Holyoak, 1993; Brown, 1982). Even if all training and transfer conditions are fulfilled, it often remains difficult for children to independently relate that what already has been learned to new tasks. They are particularly interested in solving new tasks, and it gener-ally does not occur to them to search for relational similarities between new and previously learned tasks, although in principle, they would be able to do so (e.g., Opfer & Thompson, 2008). To realize transfer effects, it thus seems necessary to practice paradigmatic transfer actively. The problem solver not only needs to “learn how to learn” but also to “learn how to generalize” or “to come to transfer” (Klauer & Phye, 2008).

The study, among others, examined whether children’s inductive reasoning skills be-came more advanced as a consequence of a dynamic instruction program aiming at the enhancement of inductive reasoning processes, whether they paralleled the way children profited from the dynamic testing procedure, whether the dynamic test measures were good predictors of the later outcomes of the cognitive training program, and whether thorough training of a whole variety of inductive reasoning programs lead to better trans-fer. Participants were 155 second graders (aged 7–9 years old) split into four conditions: dynamic testing plus cognitive training, cognitive training, dynamic testing, or merely completing all pretests and posttests. The LIR, consisting of two inductive reasoning tests (visual exclusion and verbal analogies), has a sandwich format, meaning that interven-tion is given between a pretest and a posttest, and the training follows graduated prompts procedures emphasizing the teaching of both metacognitive and task-specific (cognitive) strategies (see, for detailed information, e.g., Resing, 2000). The sequences of prompts were based on task analyses and structured according to the principle of “kleinstmögliche Hilfe” (Selz, 1935).

Whereas instructors in the original cognitive training program were given global advice about how to proceed, in the version we developed, trainers followed standardized scripts. The cognitive training material consisted of 120 inductive reasoning problems divided over


6 inductive reasoning classes including problems that could be solved by six corresponding strategies or paradigms: general reasoning structures, which are applicable in different content domains. Based on prescribed solution and prompts schemes used by the teachers, children learned (a) to acquire knowledge regarding a range of concepts such as similar-ity, difference, attributes, and relationships; (b) to identify the six problem types and (c) to classify the various problems into one of these classes; (d) the prototypical solution rules by using paradigms; (e) how to solve the problems using these rules and control their answers; and (f) to generalize their solution and control processes to new problems. The instructional method can best be described as based on guided discovery learning, requir-ing an active learning orientation on the part of the child. The training script paralleled that of dynamic testing. At the beginning of the training, the children were given the opportu-nity to discover the conceptually different types of basic problems, problem characteristics, problem solutions, and monitoring strategies on their own. Then, the trainer guided the problem-solving behavior of the child using schemes and standardized prompts. These prompts and helpful suggestions were specified and ordered from general, abstract, meta-cognitive to specific, concrete, cognitive ones. The intention of these training procedures was to let children make use of the smallest number of prompts possible to go through the solution procedure. Pretransfer and posttransfer tests were selected on the basis of their varying degrees of superficial similarity to the training tasks. Tasks could look like the trained tasks, for example, both containing geometric analogies; tasks could also be unlike the trained task but having the same underlying solving processes, for example, includ-ing visual versus verbal analogies. The term superficial refers here mainly to the way tasks are presented and the context from which they are derived. In the version of the program that was used, tasks were mostly presented as pictures of concrete objects and situations from the children’s world. Transfer tests including the same kind of material and deriving from similar contexts were considered superficially equivalent when the format was equal and superficially similar when the format differed. Tests consisting of symbolic or abstract geometric materials were considered superficially dissimilar. Dynamic testing comprised six 15-min training sessions within a period of 2 weeks. During the cognitive training program, children were trained in pairs twice a week. The training comprised 11 sessions lasting 30–45 min each.

After cognitive training and dynamic testing, children became more advanced in visual inclusion, verbal exclusion, and even scored more highly on a noninductive but superficially similar reasoning task, that is, the most concrete inductive transfer tests, which had the least challenging solution components. Children seemed to notice that the principles with their relatively simple component structure, such as those which were learned in the dynamic test-ing procedure, could be applied when solving the new transfer tasks. Children who followed both training procedures also performed significantly better on transfer tests, which were superficially dissimilar, such as seriation, visual analogies, and matrices, consisting of abstract material; the inductive reasoning rules are more difficult. It was concluded that a relatively intensive training program in which inductive reasoning had been taught along different lines and with different aims—a combination of a dynamic learning potential test and a cognitive training in inductive reasoning—resulted in positive training effects. Children also learned to slow down, to reduce their errors, and to evaluate their answers and monitor their performance. They worked more systematically and analytically, and thus improved their task performance (Resing & Roth-Van de Werf, 2002).

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Both instruments and procedures—dynamic testing versus dynamic cognitive training—provided valuable information regarding inductive learning processes. Such information could be used to inform teachers about the learning possibilities of their pupils and to provide them with concrete suggestions on how to awake and develop their inductive rea-soning potential—a central aspect of cognitive development necessary in solving school tasks such as categorization, concept formation, arithmetic, grammar, and spelling learning (Goswami, 1996).

Dynamic Testing With Graduated Prompts Techniques in Special Education

In a recent study (Resing, Bosma, & Stevenson, 2012), we evaluated the use of dynamic testing based on graduated prompts techniques in a clinical educational setting. We studied whether it would be possible to administer a dynamic test based on graduated prompting to a small, atypical group of children with complex behavioral and psychiatric problems, developmental disabilities, and, mostly, very weak school performances. We examined differentiation in in-dividual change patterns in children’s use of solving strategies when presented with a figural analogies task and explored the relation between existing academic measures (intelligence, school achievement) and dynamic testing outcomes. Data revealed that these children were able to solve figural analogies and showed differentiated progression lines in their accuracy in solving the task after training. Trained children employed more sophisticated problem solving after graduated prompts training, and individual differences in progression paths from pretest to posttest were apparent. Groups of children differing in the number and type of instruction needed during training could be identified. IQ scores and teacher ratings of school performance were highly correlated, although IQ scores showed no relationship with objectively measured school achievement scores. Dynamic test scores revealed lower cor-relations with teacher ratings of school performance but were the best predictors of school achievement. Although our sample of children was quite small, we concluded that dynamic test measures gave the best indication of the children’s scholastic achievement and in their potential for learning.

Cognitive Education: Dynamic Testing and Individualized Dynamic Instruction

Before successful, effective learning and problem solving can optimally take place, edu-cational psychologists and teachers would have to become aware that individual children have specific repertoires of strategy activities that can be addressed by cognitive education. According to Ashman and Conway (2002), Brown (1982), and many others, this repertoire of strategic activities appears to be an important variable in cognitive education. Children vary a lot in what they know, which strategies they choose and use in solving tasks, and how they generalize that what has been learned to other related tasks (e.g., Opfer & Thompson, 2008; Siegler, 2007). Children show much, or some, or hardly any learning during the train-ing part of dynamic testing. They sometimes need only metacognitive, self-regulatory skills if they need a starting point for solving; at other times, they need modeling over and over again. They show a lot of variability while solving tasks, or they show hardly any variability, and this behavior might be task specific as well. Our studies in dynamic testing, cognitive training, and dynamic instruction result by their dynamic character in better knowledge about learner characteristics and learning activities of the child. Although this is not an easy step, these learning outcomes most probably could be used as input for further dynamic


teaching to individual children or groups of children in the classroom. Before this can hap-pen, educational psychologists will need to bridge the gap between the knowledge derived from controlled dynamic testing and training in standardized situations at one hand and classroom teaching.

Ashman (1992) already studied process-based instruction that was constructed on the basis of an integrated assessment-teaching procedure with the aim to enhance informa-tion processing abilities in children. Other steps in that direction are made by Delclos, Vye, Burns, Bransford, and Hasselbring (1992) as well. Bosma (2011) discussed outcomes of dynamic testing with the teachers of the children involved in the dynamic assessment pro-cedure, but most teachers did not change their teaching based on the information provided, although they found these outcomes very interesting. Our study in special education shows that teachers sometimes have a picture of children that is based on static measures, such as intelligence test outcomes, and have less eye for the, sometimes even small, learning progressions of the child (Resing et al., 2012). Evaluation of the assessment results with teachers of the children involved in the assessment procedure could provide teachers with findings of dynamic testing that can be helpful in the development of further classroom instruction.

D. Fuchs et al. (2007) propose the use of dynamic testing instead of static response to intervention (RTI) measurements. They describe RTI as a method providing both identifica-tion of children with learning disabilities and early intervention to at-risk children. After a first study, they conclude that practitioners, using dynamic testing measures that include rather detailed information about the child, might identify young at-risk children for early intervention more easily than by using traditional RTI measures. According to D. Fuchs and his colleagues (2007), “DA seemed to tap into aspects of young children’s reading per-formances that the other [RTI] measures did not” (p. 62). Grigorenko (2009) also discusses the relationship between both concepts. L. S. Fuchs and colleagues (2012) report the extra predictive value of dynamic testing in comparison to a math word problem screener: The high numbers of false positives resulting from the static screener were practically reduced to zero when dynamic testing outcomes were included in the prediction. They plead for a two-stage screening for math problem-solving difficulties in children, including dynamic testing. The next step in such identification of children at-risk procedures could be the intro-duction of learning measures—derived from dynamic testing—in the cognitive education for these children.

In the context of cognitive education, a conclusion may be that to attain a lasting effect of education and for the possibility of occurrence of transfer effects, it is necessary to design a cognitive education program, which takes into account that both cognitive and metacognitive strategies should be taught in good harmony with each other, preferably by using a graduated prompts or guided discovery approach; that children should not only learn how to learn but also “learn how to reach transfer”; that children need to practice actively also with transfer problems; and that these forms of dynamic instruction in the classroom have to be flexible, multiple situated, and with a variety of materials. Dynamic instruction methods would be based on outcomes of individual or group dynamic testing procedures. In conclusion, we can say that the combination of dynamic testing and instruction procedures is a very promising one not only to teach children general inductive reasoning skills for problem solving but also in a subject area as math. This combination, in particular, needs further exploration in future.

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Acknowledgments. I would like to thank Julian Elliott for his thoughtful comments on the first draft of this text.

Correspondence regarding this article should be directed to Wilma C. M. Resing, Faculty of Social Sciences, Department of Psychology, Section Developmental and Educational Psychology, Leiden University, P.O. Box 9555, 2300 RB, Leiden, the Netherlands. E-mail: [email protected]



Cognitive Education in the Digital Age: Bridging the

Gap Between Theory and Practice

Adina ShamirSchool of Education, Bar-Ilan University, Israel

Today’s children are living in a digital age, surrounded by computers as sources of in-formation even before they reach school. In response to this reality, scholars and edu-cators are being asked to rethink the role of cognitive education in preparing children for this technological world. The first half of this article, written for this special issue, examines some of the attendant issues within the context of learning for the future. It discusses the need to turn to cognitive theories as the wellsprings for programs capable of training children for a reality where new digital platforms appear daily. The article’s second part focuses on cognitive theories that may provide appropriate foundations for educational programs promoting self-regulated learning (SRL) in the digital age. This article closes by presenting an intervention for peer-mediated learning with computers—a program that emerged from integration of the theories mentioned. Research-based findings indicating the program’s effectiveness are presented.

Keywords: cognitive education; metacognition; digital age; peer-assisted learning

Research on early computer use conducted in the United States during the last decade provides data that is highly relevant for the future of cognitive education (Calvert, Rideout, Woolard, Barr, & Strouse, 2005). The research findings indicate that 21%

of all children aged 2 years and younger, 58% of 3- to 4-year-olds, and 77% of 5- to 6-year-olds have had some experience with computers, often on a daily basis. Most strikingly, a more recent survey found that children aged 2–5 years are often more adept at playing video games and downloading computer applications than at tying their shoelaces or riding a bike (Roberts, 2011). These findings are reflected in the marketplace, with iPhones, iPods, and iPads increasingly being sold as gifts for children aged 6–12 years; fake plastic cellphones are sought for toddlers aged about 2 years. Blogs are also mushrooming for the purpose of counseling parents on how to cope with the phenomenon.

These somewhat piquant details hint at the growing possibility that today’s children are being born into a technological environment that requires subjecting the theories, models, and tools applied in the schools to review their structure and content. If children know, even before entering first grade, what their elders had to learn much later in life, what does this

Cognitive Education in the Digital Age 97

imply about the timeliness, the appropriateness of the education delivered in school? What theories should support early childhood curricula, and what tools should be used to translate those theories into practice? How can we adapt the educational programs implemented in the classroom for today’s digital natives, children who will be completing their studies in 2024? What can we, as educators and researchers, do to adjust cognitive education to this techno-logical revolution’s cognitive demands? Moreover, are there any successful programs directed at cognitive education for the future currently available? This article is aimed at dealing with some of these issues within the framework of this special issue.

These questions directly relate to the goals attributed to education in the past but especially today, as we prepare our children to enter the 21st century. Philosophers, scholars, and educa-tors have long struggled to define education’s goals. For Aristotle and other ancient Greeks, edu-cation was meant to develop every man’s (but not every woman’s) mental and physical potential, especially regarding the living of a virtuous life as an individual and as a citizen. This could be done only by training men in the use of reason—one of the major attributes of cognition. A more current description, such as that offered by Adele Gregory (2009), stresses the transmis-sion of “information that will help our offspring survive and thrive . . . [in the] hope that this investment will eventually return a productive member of our group or society . . . [and, lastly, creation of a] ‘legacy’—we hand knowledge down from one generation to the next to preserve it” (para. 1). One last addition to her list might be the provision of the kind of an environment and tools enabling each child to fulfill his or her individual potential. The two definitions are quite similar when it comes to the student’s relationship to his or her self as well as to society. None-theless, the absence in the second definition of reason as a tool for achieving education’s more conceptual or ethical goals connects digital learning with the subject of this special issue: What is cognitive education, where does it rest on a contemporary society’s educational agenda, and how should it be transmitted inside as well as outside the classroom during the digital age?

Cognition itself involves thinking (process) and knowledge (content), which can be further broken down into “storing, retrieving, transforming and manipulating information” (Ashman & Conway, 1997, p. 41). With its penetration into all aspects of the daily environment, the new technologies have introduced new ways of thinking that often dramatically deviate from traditional thought patterns. A plethora of opportunities for the innovative concatenation of different types of stimuli directed at obtaining information as well as stimulating motivation are constantly appearing, and at a very rapid pace, with the help of multimedia platforms. The classroom, by submission as well as by design, has accepted the appearance of calculators, then computers, smartphones, and iPads (and who knows what next)—the tools that mark our entry into the digital age in the most fundamental areas of everyday life.

As educators and researchers, we all agree that these core goals will continue to be relevant in the rapidly changing technological future. We may also agree that such preparation rests on translating the innovative theories formulated by our colleagues into practical programs meant to supplement traditional ways of teaching and learning—such as reliance on straight-forward memorization—with technologically advanced tools. This implies that educators can no longer be satisfied with instilling basic cognitive skills rooted in bounded wells of infor-mation. To be good thinkers, good citizens, and productive people, greater stress should be placed on teaching children how to synthesize their skills for the purpose of gathering infor-mation, analyzing their ideas, and creating new ideas (Sternberg, 2010).

Research on the implications of this technological revolution for education has indicated that although the technological environment appears to inherently promote active engagement

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in learning, little has been done in the schools to prepare students to take efficient advantage of what this environment offers them (e.g., Azevedo & Cromley, 2004; Kramarski, 2011). Students find it difficult to coordinate the wide range of information representations, to plan by means of effective strategies, and to monitor their own progress. These findings suggest that techno-logically attuned learning environments should incorporate programs to support self-regulated learning (SRL) or learning how to learn. Although cognitive processes may operate subcon-sciously during learning, our goal in enhancing children’s SRL is to promote the conscious use of metacognitive processes, which activate the cognitive tools needed to learning and thinking. SRL is itself characterized by the extent to which the students are active participants in their own learning processes, that is, how much they consciously set goals; take part in strategic thinking; plan, monitor, and evaluate solutions (metacognition); invest effort to enhance motivation and a sense of self-efficacy; as well as seek help (Pintrich, 2000; Zimmerman, 2000).

The practical aspects of these issues reflect the basic dilemmas implicit in program development geared to cognitive education. As our opening indicated, information has become readily available, even to infants. The critical difference in terms of education is that access to knowledge banks and content-oriented information no longer rests on educa-tional institutions but on digital networks. The consequences are twofold. First, ubiquitous exposure to digital media requires individuals to make autonomous choices regarding what portion of the constantly created wealth of information is relevant. How are individuals to make such decisions? Second, and a direct consequence of the first, because we are no lon-ger certain about what knowledge is available to individual students or how they will use it, the education system has lost control over the content, amounts, or forms of information to which children are exposed. It can therefore no longer content itself with the theories or tools of instruction appropriate to a bygone low-tech age. With these expanding cognitive horizons, educators in the digital age will apparently be required to spend greater effort in inculcating tools that promote the use of metacognitive processes by self-regulated l earners.

Before continuing, a bit of conceptual clarification is in order. The interest in cognitive education and metacognitive processes has fed much research and thinking, although de-lineation of the two domains still lacks coherence (Veenman, Van Hout-Wolters, & Affler-bach, 2006). Some analytic features relate to more general knowledge and skills, whereas others are more age specific or task specific. The same relates to process, with learning strate-gies sometimes associated with cognition, metacognition, or both. Moreover, definitions of each term often lack agreement. Veenman (2006) succinctly summarizes this situation: “ . . . [W]hile there is consistent acknowledgement of the importance of metacognition, inconsis-tency marks the conceptualization of the construct” (p. 4).

My purpose here is not to unravel these quandaries. In my own work, I have adopted a definition of metacognition that stresses its divergence from cognition in being a conscious, task-oriented process in which learners take an active part in the organization and control of their thinking, that is, knowing what (metacognitive knowledge ) and knowing how which in-volves planning, monitoring, and evaluation of cognitive processes (Brown, 1987; Flavell, 1979). Conscious student activation of metacognitive processes has crucial implications for teaching because the responsibility for learning is shifting from the teacher, as the chief mediating fig-ure, to that of the student. Stated differently, instruction in metacognition trains students how to learn autonomously, self-directedly, and independently of some external fi gure. Flavell himself defined metacognition as “any knowledge or cognitive activity that takes as its cognitive object, or that regulates, any aspect of any cognitive activity” (Flavell, Miller, & Miller, 1993, p. 150). The


current and most commonly used definition of metacognition is “cognition about cognition” or “thinking about thinking” (e.g., Veenman et al., 2006). These definitions help us understand why metacognitive processes are characterized as “learning how to learn” or, alternatively, “self-regulated learning.” As a process demanding the learner’s active participation, metacognition not only requires but also reinforces autonomy—a f actor crucial for a person’s (whether a child or an adult) adjustment to and learning about the increasingly digital environments.

VYGOTSKY, FEUERSTEIN, AND SELF-REGULATED LEARNING

Historically, it was Piaget (1970) who took the first major steps beyond the original stimulus-response model of learning introduced by Pavlov and further developed by Skinner. He understood that the human environment mediated between the original stimulus and its final response by allowing other factors to come into play, even among young children. This meant that as long as the descriptive, behaviorist S-R model remained closed to examina-tion, the black box that held the secrets of just how a stimulus could arouse one or another response could not be opened. The previous model also left no room for other tools, especially human mediators, who might add culturally motivated nuances, complexity, and behavioral depth—in the form of introspective self-criticism and self-regulation—to the cognitive pro-cesses that brought forth the identified responses (Ashman & Conway, 1997, p. 41). Cognitive development going beyond the initial learned response thus remained inexplicable. The S-R model was thus incapable of generating theories of human learning and teaching.

In the wake of Piaget’s theoretical breakthrough, Lev Vygotsky (1978) would focus on the fundamental role played by interaction among people in the acquisition of the tools necessary to develop higher cognitive functions (p. 57). His social cognition theory, which combines educational and developmental psychology, describes how learning takes “place within the context of a child’s social development and culture.” For Vygotsky, tools are means to un-derstand the world. Material tools, whether hammers, bulldozers, or computers, particular to each culture, are developed to enable people to accomplish tasks. Another set of tools are psychological in character. Language and mathematics belong to this category, as do symbolic systems and social conventions. Among the class of cultural tools, Vygotsky includes sci-entific concepts. These he considers especially important because children’s assimilation of these tools can induce profound changes in their thinking.

Another component of Vygotsky’s theory, the zone of proximal development (ZPD), is a powerful metaphor that captures the distance between what students can achieve alone and what they can achieve with the help provided by a mediator (adults/peers). Direct instruction or collaboration with a mediator supports the student’s trial-and-error progression through the zone. The subsequent scaffolding of cognitive skills guides students’ efforts and—it follows—their learning, which will gradually become more accurate, efficient, broad based, and flex-ible. Computers, like teachers, can inculcate scaffolding skills because according to Vygotsky’s theory, both are mediating tools in that they teach the child how to link one stage of thinking to another. Computer functions thus often exhibit the qualities of hierarchical networks. Networks are important for children’s cognitive education because once internalized, their structure con-siderably extends the conceptual horizon by training them for autonomous thinking.

Reuven Feuerstein (Feuerstein, Rand, & Hoffman, 1979) continues Vygotsky’s line of rea-soning when delving into the precise impacts on cognition introduced by specific aspects of mediation between adults and children. In his theory of cognitive modifiability, he states

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that the child’s mediated learning experience (MLE) with an adult is the major determinant of individual cognitive change (Feuerstein et al., 1979; Feuerstein, Rand, Hoffman, & Miller, 1980). Put briefly, Feuerstein argues that as children internalize the behavioral patterns learned during interaction with more knowledgeable adults who serve as mediators between the initial stimulus (the learning task) and the required response, they learn how to control the cognitive processes being taught. That is, MLE enhances cognition as well as metacogni-tion. He characterizes this process by means of 12 criteria.

Several educators and researchers (e.g., Dignath, Buettner, & Langfeldt, 2008; Kramarski, 2011; Mevarech, 1999) have suggested that programs for enhancing the academic achieve-ments of young children, including children with diverse educational needs, should incor-porate training in SRL. They argue that SRL practices help children internalize the skills required to understand on what foundations the required knowledge is based, which strate-gies to choose in each learning situation, why these practices should be implemented when exposed to new information, and how to reflect on their actions in a purposeful, cognitively controlled way (Sternberg & Grigorenko, 2001, p. 10). In the process, these intervention programs also support motivational (i.e., self-efficacious investment of effort) and behavioral (i.e., help seeking) processes (Pintrich, 2000; Zimmerman, 2000).

We can therefore summarize this theoretical introduction by stating that effective tools for enhancing children’s SRL are needed for children in the digital age. For educational programs to be most effective for today’s children, they need to focus on enhancing students’ ability to be independent, self-regulated learners able to make efficient use of metacognitive processes in the technology-saturated environments that require continuous autonomous decision making regarding the acquisition of information. Doing so requires the construction of programs targeted for use in the contemporary heterogeneous, diversified classroom. One of our roles as researchers and educators in the area of cognitive education is just that: the pro-vision of research-based intervention programs and tools that have been empirically tested regarding their effectiveness for all types of children.

As the other articles in this issue testify, theoretical achievements and research findings are just beginning to bridge the wide gap between theory and educational practice in the classroom. In my attempt to contribute to this effort, I devote the remainder of this article to illustrating the feasibility of this effort by means of a program already implemented in the field: the Peer Mediation with Young Children (PMYC) model and intervention program. PMYC helps promote SRL through an intervention that can be applied in regular as well as computerized environments among children having diverse educational needs. The PMYC program may thus provide an example of how to generate change in classroom practice while improving students’ capacity to respond to the challenges posed by the digital age.

PEER MEDIATION FOR YOUNG CHILDREN: A RESEARCH-BASED INTERVENTION PROGRAM FOR PROMOTING SELF-REGULATED

LEARNING WITH COMPUTERS

PMYC, originally developed for youngsters in their first years of elementary school (Shamir & Tzuriel, 2002, 2004; Tzuriel & Shamir, 2007), is a model and intervention program built on the peer-assisted learning (PAL) method commonly used in today’s classroom. As a teaching tool, PAL is theoretically grounded in Vygotsky’s (1929, 1962, 1978, 1981) sociocultural learning theory while assigning the role of mediator to a child, a peer, and usually a more experienced


student. It was Vygotsky himself who initially posited that participation in mediated learning situations fostered the acquisition of the semiotic tools required for self-regulation (see also Karpov & Haywood, 1998). In the course of the PMYC intervention, pairs of children practice PAL according to a program that also incorporates 5 of Feuerstein’s original 12 MLE criteria (Feuerstein et al., 1979; Feuerstein, et al., 1980). The 5 criteria were selected for their predic-tive power regarding cognitive modifiability (Tzuriel, 1999, 2000a, 2000b, 2001; for a detailed description of all the MLE criteria, see Feuerstein et al., 1979; Feuerstein et al., 1980). This intervention likewise incorporates insights gained from Flavell’s (1979) research into metacog-nition, a term he himself coined (Brown, 1987). The PMYC program thus attempts to e nhance SRL among young students by training them to control their own cognitive processes while acting as mediators in a peer-learning setup intentionally situated in a computerized environ-ment. Participation in peer learning following training with PMYC has been shown to help tutors and tutees acquire the cognitive and behavioral foundations for SRL.

The PMYC intervention thus operationalizes the fundamental principles of the two inter-actional learning theories that apply to young children in different settings, at various ages, and in different nations (e.g., see Shamir & Van der Aalsvoort, 2004 for the intervention’s use among Dutch children). Both theories require the participation of a more knowledgeable and experienced peer who acts as an intermediary between external stimuli (the substance of the cognitive task) and the child. These behaviors, performed through application of mediation principles when interacting with a tutee, allow the tutor/peer to influence the tutee’s learning. In the course of doing so, tutors simultaneously become aware of their own cognitive pro-cesses. Tutors thus learn to apply the selected MLE criteria to their own learning while being trained to apply those skills when tutoring their peers (Shamir, 2005; Shamir & Tzuriel, 2002, 2004). That is, training for metacognitive thinking is an inherent part of the program.

The selected MLE criteria are, as stated, operationalized in the form of task-oriented ques-tions, each stressing a different type of skill, which the children learn to ask themselves as tutors and as learners: (a) focusing on the problem (e.g., “What is the problem? What have we been asked to do?”), a fundamental criterion that initiates and maintains the entire media-tion process; (b) attaching meaning to the stimulus and its characteristics accomplished by means of labeling (e.g., “The name of this icon is smiley because it represents giving positive feedback with a smile”; “This flower is a rose”); (c) transcendence or the application of learned procedures and cognitive principles to new domains (e.g., “Here we use the same rule as in the previous task”; “Every time you want to find a rule, use this icon”); (d) regulation of behavior or the control of responses prior to, during, and following task performance (e.g., “Stop and think of what you have to do before moving to the next screen on the monitor”; “Do you remember what we do after solving a problem?”); and (e) mediation of feelings of competence, a criterion that involves the transmission of positive feedback together with explanations for successful (e.g., “Wow! You succeeded in solving the problem because you followed the rules step by step!”) and unsuccessful (e.g., “Its worthwhile checking your steps before you con-tinue on to the next screen in order to correct mistakes”) task performance.

Experience with the first four MLE criteria (focusing, attaching meaning, transcendence, and regulation of behavior) during the PMYC intervention entails practice of the three main components of SRL: (a) metacognitive knowledge, (b) metacognitive experience, and (c) metacog-nitive control of mental processes (Brown, 1987; Flavell, 1971, 1976, 1979). The fifth MLE crite-rion (mediation of feelings of competence) parallels reflection and behavior in response to the

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success and failure. This form of feedback supports development of a positive self-evaluation and belief in one’s ability to improve—an essential characteristic of the reflexivity underly-ing metacognitive thinking. Recent research has identified two learning-impeding behaviors, activation and antimediation, which may be considered nonmediation behavior within the peer-learning context (Shamir & Tzuriel, 2004). These behaviors are observed, for example, when the tutor—rather than the tutee—points to the task to be completed (activation) or when the tutor displays impatience or goes so far as to insult the tutee (antimediation).

As a learning model, the PMYC program supports acquisition of cognitive and metacog-nitive education by helping children learn a network of skills that, separately or together, can be carried over to any situation, inside or outside the classroom, in standard but especially digital environments. Once learned, these skills help students become their own cognitive mediators (they learn to self-mediate), intermediaries, or managers and, by doing so, upgrade their performance (Shamir & Lazerovitz, 2007).

The literature points to the power of computerized environments for supporting PAL (Crook, 1998). Although computer environments can provide a boundless wealth of multi-media sources of information, digital platforms are themselves highly structured in their in-ternal logic and their users’ manipulation of its software. It is this structure that helps young tutors transmit cognitive and metacognitive rules during peer mediation.

The very process of students sharing ideas during peer learning can promote SRL be-cause “it forces the subjects to bring to consciousness the idea that they are just beginning to grasp intuitively” (Hoyles, 1985, p. 152). It, thus, increases students’ reflection on their own thinking while exposing them to other ways of learning and alternative points of view. But more, unlike human teachers and peers, computers consistently provide relatively neu-tral learning environments. The presence of computers in the classroom therefore creates the relatively emotion-free environment—even if adult and peer mediators participate at the outset—which many children, especially children with diverse educational needs, require for learning to be a positive experience. Computers were therefore incorporated into the PMYC intervention because in addition to becoming one of the dominant sources of information in contemporary life, they support cognitive and metacognitive development.

Expectations regarding the usefulness of the PMYC program have been tested in several contexts while keeping its core structure intact. The intervention itself is composed of three main components: (a) direct training in MLE (mediation) principles, (b) observation and discussion of a didactic video that demonstrates these principles in a computerized setting, and (c) practice of peer mediation with the aid of multimedia and conventional materials, a stage stressing per-formance-oriented reflexivity. During the training sessions, future tutors participate in activities requiring activation of metacognitive processes—such as planning their approach to a learning task, monitoring and control of the process comprehension, and evaluating progress toward task completion—to enhance SRL. The didactic videotape is designed to promote internalization of mediation principles in coordination with other learning tools: computer programs, games, posters, work sheets, and stickers with the visual symbols that represent the MLE criterion. For example, regulation of behavior is represented by a “stop” sign, the symbol’s name is stop, and the verbal slogan is “stop and think, before and after you drill” (given in Hebrew). Training for peer mediation, which is delivered in seven sessions over a period of 3 weeks, thus involves nu-merous activities that expose the children to the roles of mediator (tutor) and learner (tutee).

To demonstrate the PMYC program’s adaptability to different problem-based learning (PBL) contexts, I would like to cite some findings obtained in several recent studies. The


first compared the program’s effect in a standard versus a digital environment (Shamir, Tzuriel, & Guy, 2007). A random sample of 108 pupils drawn from 3 fourth-grade classes ( tutors, aged 9–10 years) and 3 first-grade classes (tutees, aged 6–7 years) was first randomly assigned to 54 tutor–tutee dyads, with the older child given the task of tutoring the younger child to solve a cognitive learning problem. The dyads were divided, again randomly, into an experimental (n 5 27) and a control (n 5 27) group, each of which was randomly subdivided into two additional subgroups: one with and the other without computers. All the children participating were tested for their cognitive performance level both before and after adminis-tration of the i ntervention. The experimental tutors received the PMYC program, whereas the control tutors received a general preparation for peer tutoring. Hence, half the tutors in each group taught their peers with computers and half without. The findings indicated that the tutors who had experienced a computer-supported collaborative learning environment were better able to teach their tutees to complete different learning tasks, the first being a seriation thinking task, the second an analogies task. Addition of a computer tool therefore upgraded the power of the PMYC program to inculcate metacognitive capacities. In Vygotsky’s terms, this meant that the peer mediation experience enabled the tutors to progress from a lower (the results obtained immediately after the intervention) to a higher zone of proximal development (their ability to benefit from mediation in later, more advanced learning contexts). These join the positive findings obtained in previous research regarding children’s exposure to MLE with adults (Klein, 1996; Tzuriel, 2001) as well as the effect of metacognitive ability on academic performance (see, e.g., Kramarski & Mevarech, 2003; Zimmerman, 1990).

In another study, the effects of the PMYC program on improvement in SRL and math prob-lem solving was tested among second and third graders, with the younger children again in the role of the tutees/learners and the older children in the role of the tutors/mediators (Shamir, Tzuriel, & Rozen, 2006). A sample of 108 pupils (54 mediator—learner dyads composed of tutors aged 9–10 years and tutees aged 6–7 years) was equally divided between an experimen-tal and a control group. The experimental children received the PMYC program, whereas the control children received general preparation for PAL only. Following the intervention, all the mediators taught their younger peers how to solve math problems with the help of computers. The interaction was videotaped and analyzed with the Observation of Mediation Instrument. The results showed that training young children in PMYC enhanced both the tutor’s and the tutee’s (metacognitive) learning-how-to-learn skills and thus their math performance.

In a different study, children with learning disabilities (LD) were trained in SRL by means of the PMYC program (Shamir & Lazerovitz, 2007). The sample was composed of 162 pupils, 81 from Grade 5 (tutors, aged 10–11 years) and 81 from Grade 2 (tutees, aged 7–8 years). In contrast to the studies already mentioned, the tutors in this case were chosen from classes of children with LD (as defined by the National Joint Committee on Learning Disabilities [NJCLD], 2006), whereas the tutees were randomly selected from regular classes. Each tutor–tutee pair was randomly assigned to an experimental or control group. During the final tutoring session, the children’s interactions were videotaped and later assessed with the Observation of Mediation Instrument. The tutors also completed a dynamic assessment analogies test (Tzuriel, 2000a) preintervention and postintervention. The research findings once more indicated that experimental tutors, once ex-posed to the PMYC intervention, exhibit higher SRL capacities as compared with the tutors in the control group, expressed in their improved mediation skills and analogies scores.

One of the most striking differences exhibited by the two groups of tutors appeared in their mediation of regulation of behavior. Previous studies with regular children have shown

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that this MLE criterion is an efficient predictor of SRL (see Shamir & Tzuriel, 2002; Tzuriel & Shamir, 2007). Regulation of behavior was observed in the tutors’ requests that the tutees slow their task execution (“stop and think”), that they identify stages of task completion (“What comes first?”), and that they check solutions for errors—behaviors suggesting that they had internalized the need to plan prior to executing an operation. These findings suggest that the PMYC program, by enhancing the capacity of children with LD to self-mediate and thus reduce their tendency to act impulsively in learning contexts (Swanson, Harris, & Graham, 2003), can be effectively applied in heterogeneous classes (Shamir, 2005).

The last study I mention here most directly demonstrates the PMYC program’s applica-bility to cognitive and metacognitive education in digital environments because it focuses on critical thinking—a skill required for maneuvering among the numerous and often simultaneous sources of information characterizing the digital age. The research in question, conducted with 45 pairs composed of 90 first- and third-grade pupils, aged 6–7 years and 8–9 years, respectively, investigated whether mediation training could improve the critical thinking capacities of the age group in question (Shamir, Zion, & Spector, 2008).

After the participants in the research were randomly assigned to the experimental or con-trol group, the PMYC intervention was administered to the experimental tutors, whereas general preparation for PAL was given to the control tutors. Following their preparation, all the children participated in a peer-tutoring condition. They were videotaped for 25 min, with their conversations subsequently analyzed with an adaptation of the Newman, Webb, and Cochrane’s (1995) Content Analysis Instrument. Analysis of the session indicated that the tutors and tutees in the experimental groups exhibited a greater depth of critical thinking, demonstrated in their higher quality of discourse ratio scores when compared with the tutors and tutees in the control group.

COGNITIVE AND METACOGNITIVE EDUCATION FOR A DIGITAL FUTURE

Metacognitive knowledge, planning, monitoring, and control are all aspects of self- regulating learning, which are powerful tools for promoting learning (Brown, 1987; Flavell, 1979). Metacognition can be practiced in situations of peer tutoring and reflexivity as the cited studies on the PMYC model indicate. In addition to the results obtained with older children, Haywood (2010, p. 32), on the basis of his own and other research, has noted that programs targeted at metacognitive or SRL “ability building” produce significant gains in cognitive development and intrinsic motivation (for program evaluation criteria, see Brooks & Haywood, 2003). The PMYC program’s benefits include the use of computers to support the subjects to be learned and the skills to be acquired. Another benefit is its flexibility: Its structure allows its application with children in broad age groups ranging from kindergarten through middle school. Yet, PMYC is but one tool for implementing the cognitive and metacognitive education necessary for adjust-ment to the digital age. Teachers in the field are waiting for additional instruments to be devel-oped, such as educational electronic books and other devices that can capture the essence and process of the higher order thinking processes children will need to navigate in the digital age.

But what exactly are we dealing with when speaking of the digital age? The most obvious feature of this environment is the fact that even very young children are constantly bom-barded with computerized information transmitted by tools, often packaged as toys, which have become part of the standard baggage of daily life. Are traditional pedagogic methods


based on book reading still adequate in a period when children can instantaneously locate answers to knowledge questions (thanks to the computers and iPads they carry in their back-packs)? Does this profusion of technology blur the line between thinking and responding, or does it create new linkages that require greater stress on cognitive and metacognitive educa-tion in the curriculum? Will the theoretical frameworks formulated by Piaget, Vygotsky, and Feuerstein become more salient just because the intensity of the digital conversations car-ried on by children with virtual partners is increasing (for a detailed discussion, see Shamir, 2009)? Will the skills transmitted through interaction remain unchanged? And how will the teaching of content, reading, math, music, and art be affected?

The answers to all these questions not only lead us in the direction of developing a model of SRL appropriate for our increasingly digital environment but also raise a fundamental question that goes beyond the boundaries of the current debate: When we speak of cognitive education, are we speaking of ability building or, as Haywood (2010, p. 32) suggests, of habit building? Might the difference between the two rest on another comment that Haywood (2010, p. 31) makes in the same article, that the construction of appropriate programs of cog-nitive education are based, at the least, on the “appropriate developmental expectations” we have of young children?

Just what are these expectations in an age when, as mentioned at the opening of this article, very young children become so quickly habituated to accessing information in ways their parents never dreamed of? Robert Sternberg (2010) has proposed that schools apply his wisdom, intelligence, creativity, synthesized (WICS) model to go beyond the habits created by traditional memory-oriented education and on to the creativity-oriented education that encourages the analytic, knowledge-based synthesis of ideas needed to cope with new envi-ronments. I would add that the practical challenge posed to educators and researchers is to explore how to incorporate tools capable of making metacognitive thinking habitual within the school. Doing so—I suggest—will support our children’s leap to creative thinking in a digital age.

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Correspondence regarding this article should be directed to Dr. Adina Shamir, 23, Yoav St, Tel- Aviv, 69081, Israel. E-mail: [email protected]



Current Views on Cognitive Education: A Critical Discussion and

Future Perspectives

Marco G. P. HesselsChristine Hessels-Schlatter

University of Geneva, Switzerland

This article is, first of all, a synthesis of the various views on cognitive education (CE) as presented by the guest authors of this issue, and it is also a critical discussion of the field. We discuss how Sternberg’s initial 5 questions were addressed by the authors, and we place these within the larger framework of the scientific literature on CE, metacognition, and dynamic assessment (DA). We try to unveil the strong and weak points of the various approaches, and we discuss some perspectives for the future.

Keywords: cognitive education; self-regulation; metacognition; dynamic assessment; learning test

In this article, we will make a synthesis of the various views on cognitive education (CE) as presented in this issue. We will discuss how Sternberg’s initial five questions were addressed by the six authors; we will try to place these within the larger framework of the scientific

literature on both CE and metacognition; and we will discuss some perspectives for the future.

WHAT IS COGNITIVE EDUCATION?

Cognitive education (CE), a term introduced by Carl Haywood1 in the late 1970s (e.g., Arbitman-Smith & Haywood, 1980; Haywood, 1977) has a long history. Its underlying notions go back to the beginning of the 20th century when Alfred Binet (1909) first spoke of mental orthopedics, André Rey elaborated the concept of educability (Rey, 1934; translated into English by Hay-wood, 2012), Lev Vygotsky (1934/1986) introduced the zone of proximal development, and Otto Selz (1935) experimented on the raising of intelligence. Now, CE has arrived in the 21st century’s computerized digital age (Shamir).

We can conclude that there is a fairly large consensus about certain characteristics of CE. All authors consider that the general aim of CE is learning to learn or learning to think, that is, developing the cognitive and metacognitive processes as well as motivational aspects im-plied in thinking and learning. This is different from a more traditional perspective of educa-tion as the transmission of knowledge. As a first consequence, CE is more focused on learning

Current Views on Cognitive Education 109

processes than on the content of learning. Second, the learning processes that are developed should be utile whatever the domain or content, that is, they should be transferable.

In spite of this large consensus, the broadness of definitions, scopes, and frameworks have brought about very different operationalizations of Sternberg’s first question. According to the various authors, the aim of CE is (a) to foster the cognitive (mental) skills, which are thinking creatively, analytically, practically, wisely, and ethically (Sternberg); (b) to foster pro-cesses of systematic logical thinking (Haywood); (c) to foster self-regulated learning (Shamir); (d) to foster cognitive modifiability and mediated learning experience (MLE) strategies (Tzuriel); and (e) to rehabilitate cognitive functioning (Carlson & Wiedl).

To our knowledge, the term CE is not much used outside the circle of those who worked closely with Reuven Feuerstein in Israel or were trained in this tradition. In the scientific lit-erature, we find terms such as cognitive strategy instruction, cognitive skills instruction, thinking skills training, teaching thinking skills, or self-regulation training (Costa, 1991; Hacker, Dunlosky, & Graesser, 1998; Hamers & Overtoom, 1997; Klauer, 2002; McGuinness & Nisbet, 1991; Nickerson, Perkins, & Smith, 1985; Segal, Chipman, & Glaser, 1985). When we compare the two traditions, CE on the one side and teaching thinking skills/self-regulation on the other, we see different names of concepts, but essentially, the two have the same general aim: de-veloping metacognitive, cognitive, and motivational processes. In reviews or meta-analyses of training programs (e.g., Dignath & Büttner, 2008; Dignath, Büttner, & Langfeldt, 2008; Hat-tie, Biggs, & Purdie, 1996; Higgins, Hall, Baumfield, & Moseley, 2005), we generally find both CE programs and self-regulation or teaching thinking skills training. Haywood, as well as Carlson and Wiedl, in their reply to Robert Sternberg’s initial question, also make reference to training programs from both approaches.

However, the two research traditions also show some clear differences. CE is more explicitly focused on cognitive functions and processes, and the term metacognitive was included only much later when research on metacognition became established in the sci-entific literature. The other approaches (strategy instruction, self-regulation) were based on sociocognitive and metacognitive theory (e.g., Pintrich & De Groot, 1990; Zimmerman & Schunk, 1989) from the beginning and this can, for instance, be seen in the evaluation of these interventions. Although metacognitive approaches always include assessments of progress in metacognitive and strategic behaviors, CE is primarily focused on the effects of the intervention on (perceptive) reasoning or intelligence but rarely on strategic behavior and metaknowledge.

It can also be seen in the implementation of the training programs. Although strategy instruction and metacognitive/self-regulation training generally focus on processes and strategies that are specific to academic domains (mathematics, science, reading, writing), or on the integration of these processes in everyday teaching (infused models), CE training mostly intents to develop general thinking processes by using, what are called, content-free (i.e., curriculum-unrelated) tasks.

Regrettably, the literature shows that both communities of researchers have shown lit-tle interchange: Cognitive educationalists largely remain among themselves and use their own terminology, generally derived from Feuerstein’s work (Feuerstein, Rand, & Hoffman, 1979; Feuerstein, Rand, Hoffman, & Miller, 1980), and the same is true for advocates of self- regulated learning or thinking skills.

Dynamic assessment (DA) is also considered an integral part of the tradition of the CE approach; we rarely find this type of assessment together with other approaches. According

110 Hessels and Hessels-Schlatter

to Haywood, we need DAs to evaluate the effects of our interventions. Resing focuses on the DAs of learning capacity to provide directions for intervention in school learning. For Carlson and Wiedl, fostering and evaluating developing abilities is important for accurate assessment of cognitive capacity and learning potential and to be able to tailor intervention to the rehabili-tation needs of the client. Feuerstein’s combination of the Learning Potential Assessment De-vice (LPAD; Feuerstein et al., 1979) and Instrumental Enrichment (IE; Feuerstein et al., 1980) is a good example of how DA, used to evaluate impaired cognitive processes, can directly lead to remediation. In this approach, DA is seen as an integral part of the intervention.

The development of DA procedures emanated from a large dissatisfaction with traditional intelligence measures (see Hessels & Hessels-Schlatter, 2010). The first criticism concerns the fact that intelligence is seen as a fixed entity, although it is well known that behaviors that are considered indications of intelligence can be trained (are modifiable). Furthermore, intelligence tests have been shown to be unreliable and, especially, to lack predictive validity in special populations such as ethnic minority children, children with learning difficulties, or people with intellectual disability. Other important criticisms regarding traditional IQ tests are that they neither provide any information about reasoning or problem-solving processes nor about what kind of pedagogical intervention would be appropriate.

The fact that IQ tests have limited reliability and validity is mainly attributed to the fact that intelligence tests measure the product of previous learning and not what may be learned. Carlson and Wiedl argue that performance does not necessarily accurately reflect the cogni-tive competence of the individual or as Haywood (2008) formulates it: “They [intelligence tests] rely on the assumption that typical performance is the best indication of ability (does 5 can; does not 5 cannot)” (p. 427). André Rey’s (1934; Haywood, 2012) illustration of the trained dog that can do certain tricks and the nontrained dog that does not do these tricks is exemplary. Everyone would agree that it would be ridiculous to infer that the nontrained dog is less intelligent. We cannot know whether the nontrained dog could or could not learn the same tricks because we have never tried to train it. However, in intelligence assessment, this practice seems quite normal and accepted because such an evaluation is based on what a child can do at one particular moment. This practice is based on the (implicit) assumption that all children have had the same learning opportunities and have had the same learning experiences; in fact, an assumption of which we all know that it is false (see Hessels-Schlatter & Hessels, 2009). Therefore, we agree with Beckmann (2006) that “the orientation towards a learning product as a potential indicator for a learning process could lead to an underestima-tion of someone’s ‘true’ ability to learn” (p. 37).

In DA, some form of learning is included in the test and the test administrator and child in-teract in this learning process. The way in which learning is operationalized in DA can be quite different from one procedure to the other. Rules and procedures may be taught before testing or in a pretest-training-posttest design, and the tests may also be accompanied by graduated (hi-erarchic) prompts procedures or by simple right/wrong feedback. We make here a distinction between learning tests that include standardized assessment and training (for a definition of a test; see, e.g., Anastasi, 1988) and more clinical procedures that are individualized, such as we find in the work of Feuerstein et al. (1979) and Feuerstein, Feuerstein, Falik, and Rand (2002).

Depending on the goals of the test administrator and the theoretical framework used, the type of teaching or training provided and the type of information collected will be different. A first aim of DA is diagnostic/prognostic, for example, to provide better estimates of a person’s intelligence (defined as the ability to learn) than traditional intelligence tests, which requires


standardized testing. Several standardized dynamic tests that meet with generally accepted psy-chometric standards such as objectivity, reliability, and validity have been developed during the last decades. These tests, employing different procedures, have proved to be highly reliable and valid measures in situations where traditional tests generally failed (see Hessels & Hessels-Schlat-ter, 2010). The approach presented by Carlson and Wiedl, whose objective is the assessment of executive and memory functions in adults with psychosis, is an example of such a dynamic test.

A second aim of DA is clinical or guided toward intervention and pursues insight in the person’s current cognitive processing to uncover strengths and weaknesses or specific deficits. Such interventions are entirely adapted to the needs of the child to obtain as much as information possible. As a consequence, they will usually be nonstandardized. However, such an approach has been criticized because it may jeopardize objectivity and reliability of the assessments (Büchel & Scharnhorst, 1993).

Resing’s work, like that of Guthke and Beckmann (2000), can be positioned in between the two approaches. These authors try to provide better estimates of cognitive ability, using standard-ized procedures, while also providing information about learning profiles and strategies used.

HOW SHOULD COGNITIVE EDUCATION BE DONE?

Regarding this second question, we see that different practices are described by the authors. Resing, in her work, uses graduated prompts and guided discovery learning. Tzuriel and Shamir base their work on Feuerstein’s MLE criteria. Like Haywood, their mediation tech-nique includes what we would call metacognitive questioning (Bosson et al., 2010; Hessels, Hessels-Schlatter, Bosson, & Balli, 2009; Hessels-Schlatter, 2010). Haywood formulates “me-diating questions as well as metacognitive questions,” focusing learners’ attention on their own thought processes and cognitive resources, for example, “Have you seen something like this before? What should you do first? What do you think would happen if . . . ?” Shamir and Tzuriel have operationalized MLE criteria in the form of task-oriented questions, for example, “What is the problem? Do you remember what we do after solving a problem?” Sternberg’s approach is basically the same, but he directly includes metacognitive questioning in the task instructions given: “Compare and contrast the respective natures of the American and French revolutions; assess the strategy used by . . . ; predict changes that are likely to occur in . . .”

Other techniques that are mentioned are thinking aloud and verbalization as a tool for self-guidance (Carlson & Wiedl) as well as modeling (Sternberg, Shamir, Tzuriel). Carlson and Wiedl (e.g., 1978, 1992), as others (Berardi-Coletta, Buyer, Dominowski, & Rellinger, 1995; Dominowski, 1998; Rojas-Drummond, Pérez, Vélez, Gómez, & Mendoza, 2003; Short et al., 1991), have shown the positive effects on learning and transfer of having students ver-balize their reasoning processes while solving a task. According to several authors (Borkowski & Muthukrishna, 1992; Brown & Palinscar, 1987; Cèbe & Goigoux, 2009; Ellis, 1993; Graham & Harris, 2005; Paris & Jacobs, 1984; Pintrich, 2002; Scruggs & Mastropieri, 1993; Veen-man, Van Hout-Wolters, & Afflerbach, 2006), teaching should be explicit, that is, inform the student of why, how, and when to apply a strategy. Pressley, Graham, and Harris (2006) and Schraw (1998) report that the most efficient programs start with explicit teaching and mod-eling, followed by independent work accompanied by feedback—this method being more efficient than a discovery-oriented approach. This is particularly true for students with severe learning difficulties or intellectual disability. Carlson and Wiedl, working with quite different groups (i.e., adults with psychiatric disorders such as psychoses), also underline the necessity


to match instruction to the learner’s cognitive level. In addition, they propose to train com-pensation strategies in case of insufficient modifiability of the impaired functions.

Still, other instruction methods are peer-mediated learning, as proposed by Shamir and Tzuriel, or encouraging teachers to infuse CE also in the way they assess their students’ achievements and not only in the way they teach them (Sternberg). Furthermore, instruc-tional procedures should emphasize self-monitoring and self-assessment (Carlson & Wiedl). We thus see that metacognition is at the same time an aim for CE and a tool to achieve it.

Finally, all authors report the need to address motivational factors. Indeed, being an ac-tive and strategic learner is subject to motivational conditions (Hessels-Schlatter, 2010); the learner must acknowledge the use of the trained strategies, be convinced of the benefits of applying these strategies, feel able to succeed, and perceive some controllability in learn-ing (perceived use, self-efficacy, attributional style). Interventions that include motivational variables have been shown to be more successful than interventions that do not (Borkowski, Weyhing, & Carr, 1988; Dignath & Büttner, 2008; Dignath et al., 2008).

The type of tasks used and the associated question of generality versus specificity of the targeted processes and strategies are object of continuous debate (Haywood, 2010; this issue). Already 30 years ago, Sternberg (1987) commented that “the never-ending story of the thinking skills business seems to be whether thinking skills should be separated from or in-fused into existing curricula” (p. 254). It is probably one of the aspects that differentiate most between the authors’ approaches. Whereas Sternberg directly applies his program to curricu-lum-related activities using the argument that teaching must relate to the real practical needs of students, Shamir and Tzuriel make use of curriculum-unrelated tasks. Carlson and Wiedl also stress that content and process must be combined. Some interventions, for example, Hay-wood’s Bright Start program (Haywood, Brooks, & Burns, 1992), as well as our own interven-tion model (Bosson et al., 2010; Hessels et al., 2009; Hessels-Schlatter, 2010), alternate between the two kinds of tasks. Thinking processes and strategies are first trained with curriculum-un-related tasks. Next, these sessions are followed by curriculum-related tasks so that the students can directly practice the application of the trained processes and strategies in regular school activities and, most importantly, experience that these are useful for their everyday learning. Starting with curriculum-unrelated tasks has the following advantages: (a) Because those tasks require little specific knowledge, the students can entirely focus their attention on processes, that is, reflect on the way to address the task, discover strategies, and evaluate them; (b) this reflection is neither hindered by a lack of content knowledge nor do difficulties related to task content generate a working memory overload, which would hinder the student’s reflection; and especially (c) students with repeated school failure will show less resistance or mental block and engage more easily in these kind of tasks. Indeed, contrary to their experiences in curriculum-related activities, they have no negative experiences with such tasks. Moreover, these tasks are not threatening (no negative connotation regarding performance) and provide the opportunity to regain confidence in oneself and one’s cognitive capacities.

An often exposed argument (e.g., Klauer, 1990) is that content-free tasks will favor transfer because the taught skills are not anchored to a specific content. However, as several of the au-thors acknowledge, thinking is always content loaded: We think about something in a certain context. There is no reason to believe that the probability that the trained processes remain attached to the specificities of the task or the task situation will be different for curriculum-related and curriculum-unrelated tasks. Students show difficulties in applying and adapt-ing strategies or thinking processes to different situations. For instance, meta-analyses and


empirical studies (Blagg, 1991; Higgins et al., 2005; Loarer, Chartier, Huteau, & Lautrey, 1995; Romney & Samuels, 2001; Sanz de Acedo Lizarraga, Sanz de Acedo Baquedano, Mangado, & Cardelle-Elawar, 2009; Shiell, 2002) show that the IE program brings about rather mod-est gains in general aptitudes (especially considering the investment needed) and extremely low effects on academic achievement. This means that the participants do not transfer the acquired skills from one situation to the other.

Most researchers in the field now agree that teaching thinking skills or strategies should not be separated from the school context, which implies either using curriculum-related tasks or integrating the intervention within the regular school activities (Adey & Shayer, 1994; Ash-man & Conway, 1993; Bransford, Vye, Kinser, & Risko, 1990; Brown & Campione, 1990; Con-way & Hopton, 2000; Dignath & Büttner, 2008; Ellis, 1993; Hattie et al., 1996; Leat & Lin, 2003; Palinscar & Brown, 1984; Perkins & Salomon, 1989; Perkins, Simmons, & Tishman, 1990; Pintrich, 2002; Pressley, 1995; Vauras, Lehtinen, Olkinuora, & Salonen, 1993; Veenman et al., 2006; Wong, 1993; Wong, Harris, Graham, & Butler, 2003; Zimmerman, Bonner, & Kovach, 1996). However, whatever the materials or instructional methods used, transfer remains chal-lenging and should be prepared explicitly. The various authors address this issue in different ways. The most obvious is to have the students practice the application of the learned processes, cognitive functions, and strategies in various contexts and situations. To support this, Haywood suggests establishing a “cognitive function of the day” so that students focus on it during the whole school day—whatever the tasks at hand. He also suggests posting it in the classroom in clear view. Several researchers (Andreassen & Bråten, 2011; Cornoldi, 2009; Hessels et al., 2009; Sutherland, 2002) have used such aids (memory aids or visual support) to assist learners: posters on the wall, individual stickers, or reminders directly integrated in task’s instructions. These may function as an external memory that allows students to reactivate the strategy when needed. They also foster autonomy, leading the student from teacher-regulated to self-regulated behavior. This continuous reminder of the strategies also sustains implicit learning.

Another way to promote transfer is to regularly ask the students to give examples of other situations in which the taught strategies could be applied (Haywood). This exercise proves to be very difficult for children with special educational needs or intellectual and developmental dis-abilities—reason for which we prefer hands-on experiences. Other principles to bring students to “learn-how-to-reach-transfer” (Resing) are careful development of metaknowledge (knowing why a strategy is useful, how and when to apply it, as well as knowing which characteristics of the tasks call on which strategy), systematic comparison of current activities with previous or new ones, and reformulation of the strategies on a more general level (also called deconcretiza-tion; Perkins & Salomon, 1989) so they may fit whatever kind of task (Hessels-Schlatter, 2010).

HOW SHOULD THE EFFECTS OF COGNITIVE EDUCATION BE MEASURED?

The first thing to verify, of course, is whether the intervention has led to improved performance in the ability trained (learning effect). The second, and probably more important aspect, is whether the intervention has had any transfer effects, for example, on school learning or bet-ter working capabilities, depending on the population. Associated with this second aspect are the questions of referral to special education (Haywood) and inclusion in social and profes-sional environments (Carlson & Wiedl). A third aspect is maintenance over time of what has been learned, which can be evaluated by means of delayed posttests. These can be used not


only to assure that the acquired skills are maintained over time but also allow scrutinizing a possible usage deficiency (Miller, 1990; see also Bjorklund, 2005). Strategies and processes that are newly learned and that are not yet applied automatically require cognitive resources, next to those needed for the task at hand, and may lead to a working memory overload (Perkins et al., 1990). This means that the learner may have progressed regarding thinking processes and strategies but does not yet show improved performance because of this work-ing memory overload. For instance, Bosson et al. (2010) observed that significant progress in strategy use during the first posttest was not accompanied by improved task performance, but significant performance gains were found on the delayed posttest 4 months later.

Of course, the choice of instruments to evaluate the efficacy of a particular program is important. That is why several authors (e.g., Boekaerts & Corno, 2005; Pressley et al., 2006) suggest combining different measures (triangulation), especially when assessing metacog-nitive processes or strategies and metaknowledge to enhance reliability and validity of the measures. Indeed, these components can be captured by questionnaires, interviews, thinking aloud protocols, or direct observations, but all of these procedures present some method-ological disadvantages, which can be counterbalanced when triangulated.

Next to the effects of interventions, we also need to address the supposedly increased validity of DA. We have argued earlier that dynamic tests are more representative of learn-ing behaviors than traditional intelligence tests because they try to provide optimized learning conditions to the examinee. Thus, the procedural aspect, that is, the way in which performance is achieved, is important (Guthke, Beckmann, & Stein, 1995). This concern is related to the ecological validity of the DA (see, e.g., Wiedl, 1984; Wiedl & Herrig, 1978). It implies that to estimate the predictive validity of a dynamic test, one should not so much employ school grades or standard measures of school learning as criterion measures but rather measure learning under equally optimized learning circumstances as the dynamic test (Hessels, 2009). Only under such circumstances can dynamic tests show higher correlations with measures of school learning than traditional IQ tests. Such dynamic measures of school learning should also take into account motivational factors because students with learning difficulties who are repeatedly confronted with failure in important school domains such as language and mathematics are likely to exhibit low self-esteem and low educational motiva-tion. Examples of motivating and optimized (school) learning programs can be found in the work of Budoff, Meskin, and Harrison (1971) who elaborated a learning program on elec-tricity; Beckmann (2001) who designed a computer-guided learning program on managing an agricultural terrain in the Sahel; and Hessels (2009; Hessels & Tiekstra, 2010; Tiekstra, Hessels, & Minnaert, 2009) who designed various dynamic measures of chemistry and geography for different types of students. The studies with these dynamic measures of school learning not only showed that the DA procedures largely outperformed traditional IQ test regarding the prediction of school-related learning of students with learning difficulties or intellectual disability but also showed that the traditional IQ scores did not hold any unique information, thus rendering them redundant.

WHAT, IF ANY, EXAMPLES EXIST OF SUCCESSFUL PROGRAMS?

Haywood and Carlson and Wiedl describe several elements that characterize a good pro-gram, such as a sound theoretical basis and empirical evidence of its efficacy. Although these authors inform us briefly about a large variety of programs, the other authors inform us in


extent about their own intervention and assessment tools. Here, we will not make a complete listing of successful programs. The reader is referred to the articles of Haywood and Carlson and Wiedl in this issue and to the meta-analyses discussed in the following text. We do want to mention that it is encouraging to see that the authors dedicate their work to very diverse populations: children; adolescents; adults; typically developing individuals; individuals at risk or with special educational needs (ethnic minorities, learning difficulties, attention deficit/hyperactivity disorder (ADHD), intellectual and developmental disabilities, psychiatric disor-ders), as well as parents, siblings, and peers.

Various CE and metacognitive programs have been evaluated for their efficacy. The meta-analyses of these evaluations conducted by Dignath and Büttner (2008) and Dignath et al. (2008) as well as Higgins et al. (2005) on thinking skills (self-regulation training) programs executed in primary and secondary schools demonstrated that these approaches are effec-tive because they found strong effects both on cognitive abilities and academic performance. Table 1 presents the mean effect sizes found in the three meta-analyses. In the Higgins et al. (2005) study, primary and secondary schools are taken together. The Dignath et al. (2008) study concerns only primary education. In the Dignath and Büttner (2008) study, the effect sizes are specified for respectively primary and secondary education.

Table 1 shows that the mean effect size on cognitive performance found by Higgins et al. (2005) is 0.62. The effect sizes for academic performance vary from 0.54 to 0.82. Effect sizes for strategy use vary from 0.72 to 0.88, and those for motivational/affective variables vary from 0.17 in secondary education in the study by Dignath and Büttner (2008) to 1.44 in the study by Higgins et al. The low effect found for motivational variables in secondary education should be interpreted with caution because this result is based on only 6 effect sizes (against 48 for primary education). More detailed information in the studies of Higgins et al. (all grades) and Dignath et al. (2008; pri-mary education) shows that larger effect sizes exist for mathematics than for reading and writing, whereas the study by Dignath and Büttner ( secondary education) shows the inverse.

The role of some moderating variables on the effect size variability that Dignath and col-leagues analyzed are worth to be summarized here. That is, larger training effect sizes were found for interventions that (a) focused on metacognitive processing and metaknowledge and not only on cognitive strategies; (b) that tackled also motivational aspects of learning; and (c) that did not train students by means of collaborative or group work for primary school level, but that did so for the secondary school level. For the latter effect, the authors hypoth-esized that the young students might not have been used to working in groups and might not have received enough instruction about cooperative learning, whereas the cooperative skills of the older students were much more developed. Higgins et al. (2005) analyzed the effects

TABLE 1. Mean Effect Sizes of Intervention Programs

Higgins et al. (2005)

Dignath et al. (2008)

Dignath & Büttner (2008)

Cognitive performance 0.62 — —Academic performance 0.62 0.82 0.61; 0.54Strategy use — 0.77 0.72; 0.88Motivational/affective outcomes

1.44 1.04 0.75; 0.17


according to the kind of thinking skills intervention. They found that interventions that ex-plicitly focused on metacognitive strategies yielded a higher effect size (.96) than the studies involving the IE (.58) or Adey and Shayer’s (2005) cognitive acceleration program (.61). The greater impact of interventions centered on metacognitive aspects has also been reported by Marzano (1998) and the already mentioned studies of Dignath and colleagues.

The approaches considered in these meta-analyses vary considerably regarding content, teaching methods, targeted populations, and theoretical background. Thus, these meta-analyses do not prove the efficacy of one particular intervention but demonstrate the overall positive im-pact of thinking skills programs or approaches on learning and thinking. According to Higgins et al. (2005), “their effect is relatively greater than most other researched educational interven-tions” (p. 4), and this observation should encourage their use in schools. Because there is varia-tion in the interventions’ impact according to certain variables (e.g., subject, age), the authors underline the need to take into account the particular teaching contexts in which the programs should be applied.

WHAT RECOMMENDATIONS DO YOU HAVE FOR COGNITIVE EDUCATION?

What is probably the most important issue on which we have to spend more effort is teacher training (Haywood; Carlson & Wiedl). Indeed, as Haywood (1997) already underlined, the mere application of a thinking skills program is not enough to assure the generalizability and transfer of the processes and strategies learned. Teachers should exhibit a general metacog-nitive style in all domains and throughout the entire school day. Research (e.g., Carr, Kurtz, Schneider, Turner, & Borkowski, 1989; Coffman, Ornstein, McCall, & Curran, 2008; Kistner et al., 2010; Ornstein, Grammer, & Coffman, 2010; Perry, 1998; Rozendaal, Minnaert, & Boe-kaerts, 2005) shows that there is a strong link between the teachers’ teaching style (more or less metacognitive; that promotes self-regulation or not) and the self-regulation skills in their students. However, research (Kistner et al., 2010; Pressley et al., 2006; Veenman et al., 2006; Waeytens, Lens, & Vandenberghe, 2002) also shows that most teachers have poor knowledge about concepts such as metacognition, self-regulation, learning to learn and learning strate-gies, and do not exhibit the competences to develop these skills in their students. For instance, Kistner et al. (2010) observed that teachers generally taught very few learning strategies and that if they did, these were mostly cognitive strategies but not metacognitive ones (planning, monitoring, evaluation). Moreover, when taught, strategies were mostly taught implicitly, and the teachers rarely constituted learning environments that would favor self-regulation.

Even teachers that are trained in thinking skills or self-regulation programs encounter problems in being really efficient, and their teaching style as well as their attitudes and beliefs systems appear difficult to change. The aforementioned meta-analyses by Dignath and Büttner (2008) and Dignath et al. (2008), as well as Hattie et al. (1996), showed that training effects were significantly higher if the interventions were conducted by researchers than by the regu-lar (trained) classroom teachers. Ellis (1993) reported that teachers who were applying think-ing skills programs did not really feel concerned by the teaching of strategies. For many of them, the aim of teaching strategies was only to lead the students to achieve the expected per-formance level but not to generally render them “smarter,” more strategic, and more efficient. Strategies were often taught in isolation: one set of strategies for one kind of task. Conway and Hopton (2000) recognized that the application of their program in classrooms during


6 months was not long enough to modify teachers’ behaviors and teaching style. In a study conducted by Leat and Lin (2003), the trained teachers reported that they encountered many difficulties in generating analogies, linking information, and summoning transfer contexts or situations in which the children could apply the taught strategies: These demands sur-passed their competences. Andreassen and Bråten (2011) also reported a range of difficulties their trained teachers showed in putting several principles of the program to practice.

Even when teachers already show positive attitudes toward “learning to learn” methods, teachers need intensive training, systematic support, and supervision to become good stra-tegic teachers (Vauras et al., 1993). Actually, thinking skills, self-regulation, and metacogni-tive skills should already be part of teachers’ initial training. Already 15 years ago, Haywood (1997) stated,

By virtually restricting our teacher training efforts to teacher re-training, that is, to short-term workshops designed to re-tread teachers who have already been trained to teach according to different methods, we have seriously underestimated the magnitude and se-riousness of the changes that cognitive approaches require in the role of teachers. (p. 5)

As we mentioned in our editorial in 2009, the master students in special education at the University of Geneva receive an extensive training, both theoretical and applied, in CE. A re-cent study showed that most graduates apply CE methods in their practice (Delessert, 2012). Unfortunately, the students who are in regular teacher training do not follow these courses.

On a more general level, policy makers should be encouraged to integrate thinking skills approaches in schools. In England and Wales, these approaches are an explicit part of the na-tional curriculum (Higgins et al., 2005) as a means to raise standards. However, according to Leat and Lin (2003), “There is little direct relationship between research activity and support for teachers in meeting these demands” (p. 383). In other words, teachers are left on their own, receiving little practical assistance to “make these concepts a reality in the classroom.”

Researchers themselves should also pay more attention to the teachers, examine their needs, their beliefs and values, and how strategic teaching could be implemented in the classroom and have teachers more regularly and fully integrated in their research projects ( Boekaerts & Corno, 2005; De Corte, 2000; Dignath & Büttner, 2008; Pressley et al., 2006). On an even more general level, organizations committed to CE, such as the International Association for Cognitive Education and Psychology (IACEP), could work as a mediator with professional organizations, as suggested by Carlson and Wiedl.

Efforts should also be directed to the way we assess the efficacy of our intervention pro-grams. Most of the authors continue to use traditional IQ or aptitude tests to measure train-ing effects. This is a rather paradoxical observation considering the fact that the authors are advocates of DA or dynamic testing. This contradiction is even more striking when the research samples consist of special populations such as young children, ethnic minor-ity groups, low socioeconomic status (SES), or intellectual and developmental disabilities. As discussed previously, sufficient reliability and validity of these cognitive measures are gen-erally not guaranteed with special populations.

Training effects are expected to be different according to the learning capacity of the stu-dents, which implies that a small training effect does not necessarily mean that the program is not effective. For instance, people with moderate-to-severe intellectual deficiency will gen-erally need much more training and will show a much slower learning rate than typically


developing individuals. Regarding transfer effects, often perceptive reasoning tasks that are very close to the trained tasks are used as measures of transfer. Furthermore, the approaches in CE, contrary to self-regulation training approaches, rarely developed specific and effective instruments to assess metacognitive and strategic behavior or motivational variables. Finally, Higgins et al. (2005) deplore the fact that studies often report little about the programs and the way they were implemented. We also observed empirical studies designated to asses pro-gram effects that display methodological flaws, such as lack of control of the contrast groups’ capabilities before training. Further research is also needed to gain insight in “what works,” and more research should be done in natural contexts (Davidson & Sternberg, 1998; Pressley et al., 2006).

Concerning DA, the authors and advocates of dynamic tests regularly complain that these are not or hardly used in practice by school or educational psychologists (e.g., Karpov & Tzuriel, 2009; Lidz & Elliott, 2000; Sternberg, 2000). However, we have to acknowledge the fact that, regarding standardized learning tests, the chance of finding such a test in one’s own language, normed for the particular individual to assess, and that is available on the regular market is close to zero. In this context, we cannot help thinking about an article that Wiedl wrote in 1984 (and that still seems appropriate) that carried the title “Lerntests: Nur Forschungsmittel und Forschungsgegenstand? (Learning Tests: Only Means and Object of Research?).” It is true that some clinical assessment procedures are more easily obtainable, but without specific training, they cannot be used in an effective way either or, at least, used in the way they were meant to be used.

Also, as discussed earlier, we ascertained that the validity is not always evaluated in an appropriate manner. Dynamic tests are still often validated with static criteria that suffer from the same fallacies as the traditional IQ tests. We have argued that dynamic criteria of school learning should be used to warrant the ecological validity. Research in which such criteria were actually used also confirmed the inferiority of the static measures (e.g., Hessels, 2009).

As was the case for CE, if we wish to enlarge the use of DA by school psychologists and teachers, these techniques should at least be included in the initial curriculum of educational psychologists and special class teachers.

DA is seen as a means to inform intervention. However, until now, the relationship between evaluation and intervention has been far from satisfying. In a clinical situation, knowing the child’s learning capacity is not very relevant. Whatever the learning capacity of the individual, we must do all we can to promote the development of the cognitive functions of the individual. Another challenge is the communication of results from DA by psycholo-gists to teachers who are rarely informed or knowledgeable about the concepts used. This implies that teachers cannot do much with the information derived from a DA procedure, even though they are interested in having certain results (Bosma & Resing, 2008, 2010; Bosma, Hessels, & Resing, 2012). For referral or diagnostic purposes, the aim of dynamic tests is to help avoiding false negatives (Carlson & Wiedl), that is, avoiding underestimat-ing the real capacities of certain individuals, which might lead to their referral to a special class, a lowering of the demands in their learning curriculum, as well as lowering learning objectives, which may all be detrimental to the individuals’ cognitive development (Hessels-Schlatter & Hessels, 2010). Yet, a higher estimate of an individuals’ potential for learning and a better prediction of future curriculum-related learning will be useless when the indi-vidual remains in unfavorable conditions. If the student does not receive the stimulation or support needed to develop the cognitive variables that limit his or her functioning, little


will change (Hessels-Schlatter & Hessels, 2010). Or as Elliott (2000) formulates it, “Unless the child’s current environment can be transformed, there is little likelihood that any ‘po-tential’ can actually be realized” (p. 718). It is exactly in this area that more works needs to be done.

Finally, a continuous problem is the fact that scientific journals keep requiring IQs of par-ticipants before they will publish a research article. The scientific community is, apparently, still convinced of the infallible value of IQ. Again, for special populations, it has been shown that IQ scores are far from reliable and valid, whereas dynamic tests do provide reliable and valid measures. We have shown, for instance, that the outcomes of research in individuals with mild intellectual disabilities based on matching by IQ or matching on learning capac-ity does not lead to the same conclusions (Hessels, 2012; Hessels & Gassner, 2010). These results indicate that conclusions based on research using IQs may not be valid.

To conclude, we are convinced that DA and CE make valuable contributions to the field of cognitive development and learning. However, on a theoretical as well as on a practical level, we think that CE could profit from a stronger exchange with the field of metacognition and self-regulation. We find it therefore very satisfying to know that upcoming issues of the Journal of Cognitive Education and Psychology will be dedicated to self-regulated learning, related to both assessment and intervention.

NOTE

1. H. Carl Haywood is one of the founding fathers of the IAECP, and for many years has served on the editorial board of the Journal of Cognitive Education and Psychology.

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Correspondence regarding this article should be directed to Marco G. P. Hessels, University of Geneva, Faculty of Psychology and Educational Sciences, Boulevard du Pont d’Arve 40, CH-1205 Geneva, Switzerland. E-mail: [email protected]


Editor

Marco G. P. Hessels, University of Geneva

AssociAtE Editor

Laura Berk, Illinois State University

EditoriAl BoArd

Fredi Büchel, University of Geneva

Sylvie Cèbe, University Blaise Pascal

Julian Elliott, Durham University

Douglas Fuchs, Vanderbilt University

Elena L. Grigorenko, Yale University

Yuriy V. Karpov, Touro College

Alex Kozulin, The International Center for Enhancement of Learning Potential

Zmira Mevarech, Bar Ilan University

Santiago Molina, University of Zaragoza

Jean-Louis Paour, University of Provence

Juan Pascual-Leone, York University

Wilma Resing, Leiden University

Carol Robinson-Zañartu, San Diego State University

Ursula Scharnhorst, Swiss Federal Institute for Vocational Education and Training

Robert Sternberg, Oklahoma State University

David Tzuriel, Bar-Ilan University

Karl H. Wiedl, University of Osnabrück

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