This article was downloaded by: [York University Libraries]On: 18 November 2014, At: 04:05Publisher: RoutledgeInforma Ltd Registered in England and Wales Registered Number: 1072954 Registered office: Mortimer House,37-41 Mortimer Street, London W1T 3JH, UK
Educational PsychologistPublication details, including instructions for authors and subscription information:http://www.tandfonline.com/loi/hedp20
Making Learning Meaningful: Lessons From Research onCognition and InstructionPenelope L. PetersonPublished online: 08 Jun 2010.
To cite this article: Penelope L. Peterson (1988) Making Learning Meaningful: Lessons From Research on Cognition andInstruction, Educational Psychologist, 23:4, 365-373, DOI: 10.1207/s15326985ep2304_4
To link to this article: http://dx.doi.org/10.1207/s15326985ep2304_4
PLEASE SCROLL DOWN FOR ARTICLE
Taylor & Francis makes every effort to ensure the accuracy of all the information (the “Content”) contained in thepublications on our platform. However, Taylor & Francis, our agents, and our licensors make no representationsor warranties whatsoever as to the accuracy, completeness, or suitability for any purpose of the Content. Anyopinions and views expressed in this publication are the opinions and views of the authors, and are not theviews of or endorsed by Taylor & Francis. The accuracy of the Content should not be relied upon and should beindependently verified with primary sources of information. Taylor and Francis shall not be liable for any losses,actions, claims, proceedings, demands, costs, expenses, damages, and other liabilities whatsoever or howsoevercaused arising directly or indirectly in connection with, in relation to or arising out of the use of the Content.
This article may be used for research, teaching, and private study purposes. Any substantial or systematicreproduction, redistribution, reselling, loan, sub-licensing, systematic supply, or distribution in anyform to anyone is expressly forbidden. Terms & Conditions of access and use can be found at http://www.tandfonline.com/page/terms-and-conditions
EDUCATIONAL PSYCHOLOGIST, 23(4), 365-373 Copyright Q 1988, Lawrence Erlbaum Associates, Inc.
Making Learning Meaningful: Lessons From Research on Cognition
and Instruction
Penelope L. Peterson Michigan State University
This response addresses the comments of Corno and Good concerning implications of educational research for making learning meaningful and motivating for all students.
Both Good and Corno have provided thoughtful, detailed critiques of my article. They have pointed out strengths and weaknesses of my review. In addition, they have drawn on their own scholarly work to offer new insights on how to improve compensatory education (CE).
THE CRUX OF THE ARGUMENT
In her commentary, Corno has extended and clarified my argument for how the aptitude-treatment interaction (ATI) perspective might be applied to planning and evaluating compensatory education programs. Her distinction between compensation and remediation is an important one that educators and researchers should keep in mind as they select objectives, plan services, design instruction, and evaluation outcomes of Chapter 1 programs.
In contrast, Good seems to have missed a major point that I was attempting to make in my article-namely, that to date, educators may have been misguided in the educational practices that they have used to teach low-achieving students in Chapter 1 programs. Good contends that "not enough emphasis was placed on a call for new observational research that examines what happens in compensatory education programs." Although
Requests for reprints should be sent to Penelope L. Peterson, College of Education, Michigan State University, East Lansing, MI 48824.
Dow
nloa
ded
by [
Yor
k U
nive
rsity
Lib
rari
es]
at 0
4:05
18
Nov
embe
r 20
14
observational research may play an important role in describing and documenting what is happening in classrooms and schools, observational research is only effective as long as something good is going on in classrooms and schools. My argument is that the instructional methods being used currently with Chapter 1 students tend to be less than ideal (see also Calfee, 1986, and Romberg, 1986, for further support of this argu- ment). Thus, if a researcher employed an observational strategy to attempt to improve CE, the researcher might have to observe CE programs in many schools in order to identify one effective CE program.
Arising From Dust-Bowl Empiricism
By advocating observational research to improve CE, Good is relying on inductive reasoning or the scientific method in which the scientist makes observations, discovers regularities, and formulates general laws of nature. Although inductive reasoning has been used effectively in the physical and biological sciences as well as in education, most notably by "process-product" researchers who have discovered some significant rela- tionships between teachers' behaviors and students' achievement, inductive reasoning does have limitations. In their attempts to improve education by emulating the physical sciences, educational researchers may have relied excessively on "dust-bowl empiricism." By attempting to discover relation- ships between existing classroom practices and student achievement, they have unwittingly accepted and maintained the status quo in educational practice. As Levin (1987) pointed out, such an approach may not lead to the reforms needed in CE.
Perhaps the time has come for educators and researchers to be more theory-based as they think about selecting, planning, and evaluating practices for CE. In the remainder of this article, I argue that in thinking about selecting services and planning instruction for Chapter 1 students, educators and researchers need to build on knowledge derived from AT1 theory as well as on theoretical notions derived from recent research and theory on cognition and instruction. It is to a discussion of the latter that I now turn.
Back to the Basics: Turning an Old Notion on Its Head
A major lesson that might be derived from recent theory and research on cognition and instruction has to do with learning and teaching the "basics" in reading and mathematics. In the past, most teaching of the basics in reading and mathematics has rested on the assumption, derived primarily from task analyses and behavioral psychology, that students must learn the
Dow
nloa
ded
by [
Yor
k U
nive
rsity
Lib
rari
es]
at 0
4:05
18
Nov
embe
r 20
14
MEANINGFUL LEARNING 367
lower order facts and skills before being able to master higher order problem-solving and application skills. A common metaphor is that the learner is like an "empty vessel" into which knowledge should be poured. In contrast, recent theory and research from cognitive psychology suggest that a better metaphor is that knowledge is stored in the learner's head as a network of concepts or constructs. Learning involves the making of connections between the learner's existing network of knowledge and the new information to be learned. Instruction should facilitate these connec- tions, and the process of education might be defined as the construction of knowledge by the learner.
In a network theory of cognition and learning, the concepts of lower and higher order learning may not make sense. For example, computational skills may not exist as "lower-order" prerequisites for "higher-order" mathematical problem solving, but rather are learned in relation to, and as part of, the problem solving activity (see, e.g., Resnick, 1985). Similarly, as Resnick (1985) pointed out, ample evidence exists that both ''top-down" and "bottom-up" processes are involved in reading. The important point is that new information to be learned and taught needs to be related in a meaningful way to knowledge and information that the learner already has. Ginsburg and Yamamoto (1986) summarized the implications for mathe- matics education:
Yet, much of mathematics education, particularly teaching the "basics" usually takes a much different form, namely drilling students in calculational routines or number facts, or devising clever techniques, perhaps based on task analysis, to teach these topics. Teaching the basics usually deals in an isolated way with formal procedures and concepts separately, and ignores informa- tional knowledge . . . this is a misguided approach based on empty vessel theory that children know nothing of mathematics when they begin its formal study. But this is not true. Even before the onset of schooling, children possess abundant "natural resources" in this area. . . . The educational paradox and dilemma are that children often fail to connect what they already know with what is taught in school. Hence, teaching the basics should involve tapping children's informal knowledge and encouraging its connection with various aspects of formal mathematics. We think that most children failing in school could succeed if only they were encouraged to use their natural "intelligence" (i.e., their informal knowledge) to deal with material that is, after all, not highly complex. (p. 364)
Although Ginsburg and Yamamoto (1986) applied their argument to mathematics education, such an argument applies equally well to teaching the basics in reading (see, e.g., Anderson, Hiebert, Scott, & Wilkinson, 1985; Applebee, Langer, & Mullis, 1988). The notion is particularly apropos to the teaching and learning of Chapter 1 students in CE. Most
Dow
nloa
ded
by [
Yor
k U
nive
rsity
Lib
rari
es]
at 0
4:05
18
Nov
embe
r 20
14
instructional services for Chapter I students have been based on the notion that they are low-achieving students who need more drill and practice because they have not yet mastered the basics. Recent theory and research from cognitive psychology suggests just the opposite notion. Low-achieving students, perhaps even more than high-achieving students, need instruc- tional practices that relate new knowledge in a meaningful way to the knowledge that they have already developed. This means, for example, that reading should always be taught with a basis in meaning and that mathematics computation should be taught in the context of real-world problem solving (e.g., Anderson et al., 1985; Carpenter, Fennema, & Peterson, 1984; Resnick, 1985).
Theory and research in cognitive psychology has now reached a point that it can be used profitably to "formulate the principles that can guide interventions designed to help people learn" (Resnick, 1985, p. 180). To illustrate how principles derived from cognitive theory and research might be used to develop and change actual classroom instructional practices, I turn to the example of our research on cognitively guided instruction.
Using Principles Derived From Cognitive Theory to Improve Instructional Practice: The Example of Cognitively Guided Information
With my colleagues Thomas Carpenter and Elizabeth Fennema, I have been involved in a comprehensive attempt to apply findings from cognitive research on children's learning to improve classroom instruction in first- grade mathematics and to facilitate children's mathematics learning over a school year (Carpenter, Fennema, Peterson, Chiang, & Loef, 1988; Fennema, Carpenter, & Peterson, in press). Cognitive research on children's learning of addition and subtraction has shown that before receiving formal instruction, most young children invent informal modeling and counting strategies for successfully solving addition and subtraction word problems (Carpenter, Hiebert, & Moser, 1983; Carpenter & Moser, 1983; Riley, Greeno, & Heller, 1983). This informal knowledge might provide a basis for the student to develop mathematics concepts and computational skills and to develop understanding of mathematics. However, neither traditional first-grade mathematics curriculum nor traditional teaching of addition and subtraction builds systematically on children's informal knowledge or supports its development.
In our research, we derived several principles from the previous research and used them as a basis for working with first-grade teachers to modify their classroom instruction in mathematics (Carpenter, Fennema, & Peterson, 1984). First, teachers need to learn to classify word problems and to identify the processes that children usually use to solve different
Dow
nloa
ded
by [
Yor
k U
nive
rsity
Lib
rari
es]
at 0
4:05
18
Nov
embe
r 20
14
MEANINGFUL LEARNING 369
problems. Second, teachers need to assess not only whether a child can solve a particular problem, but also how the child solves the problem. Teachers need to analyze children's thinking by asking appropriate questions and listening to children's responses. Research on children's thinking provides a framework for this analysis and a model for questioning. Third, teachers need to use the knowledge that they derive from assessment and diagnosis of the children to design appropriate instruction. Teachers should organize instruction to involve children so that children can actively construct their own knowledge with understanding. Finally, teachers should ensure that elementary mathematics instructions stresses relationships between con- cepts, skills, and problem solving. We defined an approach based on these principles as cognitively guided instruction (CGI).
We have conducted a year-long study in which we used these principles to work with teachers and asked them to change their first-grade instruction of addition and subtraction in accordance with these principles. Forty first- grade teachers agreed to participate in our study. Half of the teachers were assigned randomly to the CGI group and half to a control group. Control teachers participated in a half-day workshop on problem solving. CGI teachers participated in a 4-week summer workshop led by Fennema and Carpenter. We provided teachers with information, resources, and mate- rials that built on the CGI principles just mentioned. Teachers were not trained in specific techniques for altering their classrooms and curriculum. Thus, the researchers employed a "constructivist" approach to educating the teachers and working with them as thoughtful professionals, who construct their own knowledge and understanding.
Effects on Classroom Instruction of Addition and Subtraction
Teachers and their students were observed for four I-week periods throughout the school year. Our observations showed that the CGI teachers changed their instructional practices and curricula in addition and subtrac- tion. Both systematic observations and anecdotal observations documented significant differences between CGI and control teachers in their instruction of addition and subtraction. Observations indicated that CGI teachers organized their instruction around solving addition and subtraction word problems. They often began the lesson by telling a story and then posing word problems to the children based on the story. Similarly, the observation data showed that CGI teachers spent more time interacting with students about word problems than did control teachers. In contrast, control teachers' interactions concerned computations and number facts. Students were more often engaged in number fact and computation learning in control classes than in CGI classes. In contrast to control teachers, CGI
Dow
nloa
ded
by [
Yor
k U
nive
rsity
Lib
rari
es]
at 0
4:05
18
Nov
embe
r 20
14
370 PETERSON
teachers posed problems more often and expected students to use multiple strategies more often than a single strategy to solve a problem.
Effects on Students' Problem Solving and Computational Skills
In September and again in May, students in the CGI and control teachers' classes completed the Iowa Test of Basic Skills (ITBS) and an experimenter- constructed work problem solving test. The results of regression analyses on students' posttest scores, adjusting for pretest achievement scores, showed that when compared to students in control teachers'classes, students in CGI teachers' classes showed significantly greater ability to solve addition and subtraction word problems, particularly complex word problems. Further, a significant AT1 with prior achievement showed that when control classes and CGI classes were compared, low-achieving CGI classes benefitted particularly from the CGI approach as shown by their achievement on solve simple word problems and their achievement on number facts and compu- tation. In addition, students in CGI classes were more confident of their abilities to solve word problems than students in control teachers' classes, perhaps reflecting CGI students greater abilities to solve such problem. Finally, although the observational data indicated that control teachers spent significantly more time on addition and subtraction number facts than did CGI teachers, the students in CGI teachers' classes were at least as good as those in the control teachers' classes. Indeed, low-ability CGI classes exceeded low-ability control classes in their learning of number facts and computational skills. Low-ability classes learned significantly more number facts in the CGI approach than in the control group.
Implications of CGI for Compensatory Education
Although the CGI approach was not designed specifically for intervention with low-achieving Chapter 1 students, the results suggest some important implications for compensatory education. First, actual classroom instruc- tion might be improved by using principles derived from recent theory and research in cognitive psychology. Specifically, our results support the notion that instruction in a specific content area, such as addition and subtraction, might be designed to build on students' informal knowledge- the knowledge that students bring to the classroom. Thus, basing addition and subtraction instruction on students' informal knowledge of word problems proved to be an effective technique both for facilitating students' problem solving and for improving number fact learning and learning of computational skills.
Second, and most importantly for compensatory education, our CGl
Dow
nloa
ded
by [
Yor
k U
nive
rsity
Lib
rari
es]
at 0
4:05
18
Nov
embe
r 20
14
MEANINGFUL LEARNING 371
findings suggest that such an approach might be particularly beneficial for low-ability students. Thus, in contrast to previous approaches that have relied on providing more drill and practice on number facts for low- achieving students, our results suggest that low-achieving students, even more than high-achieving students, benefit from a meaning-based approach to mathematics learning that builds on students' informal knowledge of mathematics.
Thus, if taken seriously, the results of our CGI study might be used to rethink the meaning of teaching the basics in CE and to develop new instructional practices for low-achieving students that differ from current instructional practices in Chapter I programs. The outcome might be that learning mathematics and reading will be more meaningful and more motivating for low-achieving students.
CONCLUSION
Although I agree with Good's sentiments that more basic research in education is needed and should be funded, I argue that although such research is being conducted, educators and policymakers will continue to design and implement instructional programs for Chapter 1 students. Rather than to continue some of the approaches used in the past that have been shown to be less than effective, we should design new instructional interventions following from theory-based principles derived from recent theory and research. Obviously, these new approaches should be examined systematically by gathering observational data on instructional practices and processes and also by gathering information on student achievement and other outcomes. Such as action approach has been taken by Levin (1987) and his colleagues who have created accelerated schools for disad- vantaged students. Although his approach to changing the schools has been a broad based one, Levin incorporated some basic principles from recent cognitive research and theory in his design of the curriculum. He stated that, "The curriculum emphasizes language-reading and writing for meaning-in all disciplines, even in mathematics. The curriculum also applies learning to everyday problems and events" (Levin, 1987, p. 20).
In sum, although researchers need to continue studying and theorizing about learning and teaching to improve the understanding of how to make learning meaningful and motivating, experiments and innovations to im- prove compensatory education for low-achieving students should not await the final answer of educational researchers. Indeed, educators, researchers, and policymakers should view the process as one in which there is no final answer, but rather, a continuous transformation and reconstruction of knowledge. We do know some things now. We have some hunches that
Dow
nloa
ded
by [
Yor
k U
nive
rsity
Lib
rari
es]
at 0
4:05
18
Nov
embe
r 20
14
372 PETERSON
have been derived from theory and research. We can use these hunches to design some interventions that can be tried and tested. The message is not that "policy direction can be obtained from poor or nonexistent research evidence," but rather that there are lessons to be learned from recent research and theory on cognition, instruction, and ATI. Such lessons may guide educators, researchers, and policymakers in rethinking CE.
ACKNOWLEDGMENT
The research reported in this article was funded in part by a grant from the National Science Foundation (Grant No. MDR-8550236). The opinions expressed herein do not necessarily reflect the position, policy, or endorse- ment of the National Science Foundation.
REFERENCES
Applebee, A. N., Langer, J. A., & Mullis, I. V. S. (1988). The nation's report card (NAEP): Who reads best? (Report No. 12-R-01). Princeton, NJ: Educational Testing Service.
Anderson, R. C., Hiebert, E. H., Scott, J. A., & Wilkinson, I. A. G. (1985). Becoming a nation of readers: The report of the commission on reading. Washington, DC: The National Institute of Education, U.S. Department of Education.
Calfee, R. C. (1986, June). Curriculum and instruction: Reading. Paper presented at the Conference on Effects of Alternative Designs in Compensatory Education, Washington, DC.
Carpenter, T. P., Fennema, E., & Peterson, P. L. (1984). Cognitively-guided instruction: Studies of the application of cognitive and instructional science to mathematics curriculum (proposal funded by the National Science Foundation, Washington, DC). Madison, WI: Wisconsin Center for Education Research.
Carpenter, T. P., Fennema, E., Peterson, P. L., Chiang, C., & Loef, M. (1988, April). Using knowledge of children's mathematics thinking in classroom teaching: An experimental study. Paper presented at the annual meeting of the American Educational Research Association, New Orleans, LA.
Carpenter, T. P., Hiebert, J., & Moser, J. M. (1983). The effect of instruction on children's solutions of addition and subtraction problems. Educafional Studies in Mathemafics, 14, 55-72.
Carpenter, T. P., & Moser, J. M. (1983). The acquisition of addition and subtraction concepts. In R. Lesh & M. Landau (Eds.), The acquisition of mathematics concepts and processes (pp. 7-44). New York: Academic.
Fennema, E., Carpenter, T. P., & Peterson, P. L. (in press). Learning mathematics with understanding. In J. Brophy (Ed.), Advances in research on teaching (Vol. 1 ) . Greenwich, CT: JAI.
Ginsburg, H. P., & Yamamoto, T. (1986). Understanding, motivation, and teaching: Comment on Lampert's "Knowing, Doing, and Teaching Multiplication." Cognition and Instruction, 3, 357-370.
Dow
nloa
ded
by [
Yor
k U
nive
rsity
Lib
rari
es]
at 0
4:05
18
Nov
embe
r 20
14
MEANINGFUL LEARNING 373
Levin, H. M. (1987, March). Accelerated schools for disadvantaged students. Educational Leadership, 44(6), 19-2 1 .
Resnick, L. B. (1985). Cognition and instruction: Recent theories of human competence. In B. L. Hammonds (Ed.), Master lecture series: Vol. 4. Psychology and learning (pp. 123-186). Washington, DC: American Psychological Association.
Riley, M. S., Greeno, J. G., & Heller, J. I. (1983). Development of children's problem-solving ability in arithmetic. In H. Ginsburg (Ed.), The development of mathematical thinking (pp. 153-200). New York: Academic.
Romberg, T. A. (1986, June). Mathematics for compensatory education programs. Paper presented at the Conference on Effects of Alternative Designs in Compensatory Education, Washington, DC.
Dow
nloa
ded
by [
Yor
k U
nive
rsity
Lib
rari
es]
at 0
4:05
18
Nov
embe
r 20
14
Recommended
