Verbal and visual learning in a sample of Native Americanchildren: A study of the effects of practice on memory

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Authors Shah, Minoo Gunwant, 1964-

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VERBAL AND VISUAL LEARNING IN A SAMPLE OF NATIVE AMERICAN

CHILDREN; A STUDY OF THE EFFECTS OF PRACTICE ON MEMORY

by

Minoo Gunwant Shah

A Dissertation Submitted to the Faculty of the

DEPARTMENT OF EDUCATIONAL PSYCHOLOGY

In Partial Fulfillment of the Requirements For the Degree of

DOCTOR OF PHILOSOPHY

In the Graduate College

THE UNIVERSITY OF ARIZONA

19 9 8

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THE UNIVERSITY OF ARIZONA ® GRADUATE COLLEGE

As members of the Final Examination Committee, we certify that we have

Minoo Shah read the dissertation prepared by_

Verbal and Visual Learninq in a sample of Macive

American children: Astudv of the effects of oractice

o n M e m o r .

and recommend that it be accepted as fulfilling the dissertation

requirement for the Degree of Doctor of Philosonhv

r . Shit a J. a M i s h r a

Lawrence Aleamoni

A-Dr. Kristine Kaeminak

Date

Date

Date VAs/'?t>

Date

Date

Final approval and acceptance of this dissertation is contingent upon the candidate's submission of the final copy of the dissertation to the Graduate College.

I hereby certify that I have read this dissertation prepared under my direction and recommend that it be accepted as fulfilling the dissertation requirerfiilt)

Dissertation Director Date

3

STATEMENT BY AUTHOR

This dissertation has been submitted in partial fulfillment of requirements for a doctoral degree in Educational Psychology at The University of Arizona and is deposited in the University Library to be made available to borrowers under rules of the Library.

Brief quotations firom this dissertation are allowable without special permission, provided that accurate acknowledgment of source is made. Requests for permission for extended quotation from or reproduction of this manuscript in whole or in part may be granted by the head of the major department or the Dean of the Graduate College when in his or her judgment the proposed use of the material is in the interests of scholarship. In all other instances, however, permission must be obtained from the author.

4

ACKNOWLEDGMENTS

I would like, first of all, to extend my gratitude to the following members of my committee. Dr. Shitala Mishra, for his guidance and support. His pragmatic approach and positive outlook convinced me that this would actually happen! Dr. FCristine Kaemingk, for the intellectual stimulation that got me going and for providing me with a platform to air the most outlandish of my ideas while gently keeping me grounded in reality. Dr. Lawrence Aleamoni for his patience and for coming through at the shortest notice.

I would also like to thank Dr. Pat Jones for her time and her invaluable input regarding my analyses, and Dr. Peggy Douglas for helping me with financial aid in desperate times.

A special thank you to my friends Raghu, Ram, Preeti, Matt, Venkat, and the gang who made sure my social life kept me sane through this endeavor. My roommates, Farha and Priya, who pampered me through trying times. Aamer, for tactfully dealing with panic attacks. Trish, Gunny, and my other colleagues, for their belief in my abilities. Kamakshi Murti and Sujana Calasani who amazed me by their capacity to give even before I could ask. Anuradha Ruhil, for the tea sessions, the ready ear and constant support, and for helping me believe in myself

Finally, I would like to thank my family, for not only allowing me the fi-eedom to follow my dreams, but also providing me with the monetary means and emotional support to do so. 1 would particularly like to thank my brother Girish and sister-in-law Stephanie for providing me with a home away from home.

Dedicated to my parents:

Gunwant P. Shah and IMadhu G. Shah

6

TABLE OF CONTENTS

LIST OF FIGURES 8 LIST OF TABLES 9 ABSTRACT 10 CHAPTER OP^: INTRODUCflON 12 CHAPTER TWO; LITERATURE RE\^W 19

Neurological Correlates of Memory 19 Retrograde and Anterograde Amnesia 20 Short- and Long Term Memory 21 Explicit and Implicit Memory 22 Episodic and Semantic Memory 27 Learning and Memory 27

Memory and Information Processing in Native Americans 28 The Ecological View 35 The Socio-cultural View 37 Neuropsychological Research 38

Cultural Issues in Assessment 40 Summary 44

CHAPTER THME: I^THODS 45 Sample 45 Instrumentation 46

The Wide Range Assessment of Memory and Learning (WRAML) 47 Verbal Learning Subtest 47 Visual Learning Subtest 48 Norms 48 Reliability 48 Validity 49

The Wechsler Intelligence Scale for Children-Third Edition (WISC-HI) 53 The Differential Abilities Scales (DAS) 54

Procedures 55 Hypotheses Tested 56 Statistical Analyses 57

CHAPTER FOUR: RESULTS 58 Descriptive Statistics 58 Results Associated with Hypotheses I, 2 and 3 60 Results Associated with Hypotheses 4, 5 and 6 64 Results Associated with Hypothesis 7 67 Results Associated with Hypothesis 8 70 Results Associated with Hypothesis 9 70

CHAPTER FIVE: DISCUSSION 73 Descriptive Data 73

TABLE OF CONTENTS - Continued

Verbal Learning Subtest Data Analyses 74 Visual Learning Subtest Data Analyses 76 Correlational Data Analyses 77 Limitations and Implications for Future Research 78

APPENDIX: HUMAN SUBJECTS COMMITTEE LETTER 80 REFERENCES 81

8

LIST OF FIGURES

FIGURE I, Verbal learning subtest learning curve 60 FIGURE 2, Visual learning subtest learning curve 64

9

LIST OF TABLES

TABLE 1, Percentage of Individuals in Norm Sample by Racial Sub-Category 49 TABLE 2, Correlation Coefficients and SEMs for the Verbal Learning Subtest, the

Visual Learning Subtest and Index Scores 50 TABLE 3, Correlation of WRAML Index Scores with scores on the McCarthy

Memory Index, the SB-IV Short Term Memory and WMS-R Index Scores 51

TABLE 4, Descriptive Statistics 59 TABLE 5, Verbal Learning Subtest: Cell Means and Standard Deviations 61 TABLE 6, Verbal Learning Subtest: Test of Between-Subjects Effects 61 TABLE 7, Verbal Learning Subtest: Test of "Time" Within-Subject Effects 61 TABLE 8, Verbal Learning Subtest: Duimett's Test 63 TABLE 9, Visual Learning Subtest: Cell Means and Standard Deviations 65 TABLE 10, Visual Learning Subtest: Test of Between-Subjects Effects 65 TABLE 11, Visual Learning Subtest: Test of'Time" Within-Subject Effects 65 TABLE 12, Correlations between Scaled Scores of the Verbal Learning and Visual

Learning subtests and the Index Scores of the WRAML 68 TABLE 13, Correlation between Raw Scores on the Verbal and Visual Learning

subtests and the Index Scores of the WRAML 69 TABLE 14, Correlations between Verbal, Performance and Full Scale IQs on the

WISC-EH, Scaled Scores on the Verbal and Visual Learning subtests of the WRAML, and Index Scores on the WRAML 71

TABLE 15, Correlations between Standard Scores on the DAS, Scaled Scores on the Verbal and Visual Learning subtests of the WRAML, Index Scores on the WRAML, and WISC-IH IQs 72

TABLE 16, IQs obtained by various Native American groups in previous studies 73

10

ABSTRACT

The purpose of this study was to investigate the effect of learning and rehearsal on

verbal and visual memory in 15 Native American students ranging in age from 9 to 16

years. Subjects were administered the Verbal Learning (VL) and Visual Learning (VIL)

subtests of the WRAML. These subtests assess the ability to retain verbal (list of words)

and visual (location of designs) information presented over 4 trials. A 5* trial assesses

retention after a short delay. The study additionally aimed to relate scores on these tasks

with overall scores on the WRAML, the WISC-III and the DAS.

A description of mean standard/scaled scores for each of these measures is

provided. Concurrent with previous research, mean Verbal IQ on the WISC-III was

significantly below the normative mean while the Performance IQ was in the average

range. Mean Verbal and Visual Memory Indexes on the WRAML reflected this pattern.

Performance on all three subtests of the DAS (Arithnietic, Spelling, Word Reading) were

significantly below average.

Results of one-way repeated measures ANOVA based on z scores indicate no

significant difference from the norm in overall performance on both learning subtests.

However, z scores on the VL subtest showed a significant difference across trials. While

performance on the VL subtest was slightly below the normative average on trial I, this

difference appears to have been erased by trial 2. Performance on delayed recall trials for

both subtests were comparable to the norm group. Correlation coefficients show a

significant relation between the learning subtests and the Visual, Learning and General-

11

Memory Index scores on the WRAML. They also show a significant relation between the

VL subtest and the Verbal and Full Scale IQs on the WISC-HI. Neither of the learning

subtests shows a significant correlation with subtests on the DAS.

Results argue against a verbal learning "weakness" in Native American children.

Findings also suggest that instead of focusing on teaching to the Native Americans'

"visual strength," the use of a multi-trial approach when presenting Native American

children with verbal material in English would enhance learning and retention.

12

CHAPTER ONE

INTRODUCTION

The ubiquitous nature of memory in daily life has been addressed frequently in

psychological literature (Reynolds & Bigler, 1997). Memory, or the ability to recall

previously learned material (McLoughlin & Lewis, 1990), is critical to the acquisition

and application of new skills and knowledge. It not only reflects our experience of the

past, but also allows us to adapt ourselves to the present and plan for the future (Sohlberg

& Mateer, 1989). Memory enables us to recognize loved ones, tie our shoelaces, solve a

math problem and plan the next move in a game of chess.

Memory impairments are frequently reported sequelae of various disorders (such

as depression or schizophrenia), neurological disturbances (e.g., alcoholism, head trauma,

strokes or tumors), and negative emotional and environmental factors (Delis, 1989).

Deficits in learning and memory have also been linked with learning disabilities and

attention deficits (Brainerd & Reyna, 1991; Talley, 1993). Some states (Georgia)

explicitly include memory deficits as a disturbance of basic learning in defining learning

disabilities. In fact, researchers have associated modality specific deficits (i.e., visual,

verbal, numerical) within memory to learning disability subtypes (Rourke & Strang,

1978; Swanson, Cochran, & Ewers, 1990). The relationship between memory,

intelligence, and school achievement has been explored and established by various

researchers studying both normal and handicapped subjects (Cornwall, 1992; Stankov &

Myors, 1990). Significant correlations have been found between performance on memory

13

tasks and achievement in reading comprehension, math, writing, and foreign language

acquisition (Lehto, 1995; Swanson, 1994; Swanson, 1996). In a meta-analysis of 225

hypothesis tests relating measures of memory for order (e.g., digit span, sentence span)

with performance on standardized tests of aptitude and achievement, Mukunda (1992)

found that the relationship between memory for order and standardized test scores was

significant. Despite the relationship between memory and learning and school

performance, standardized measures of learning and memory are rarely included in our

current practice of evaluating "learning problems" and planning intervention strategies

(Zurcher, 1995).

Because of its pivotal role in the intellectual, emotional and physical aspects of

daily life and due to its obvious and implied connections to neurological integrity (Delis,

1989; Kolb & Whishaw, 1996), memory has been described as "the cornerstone of

cognition" (Reynolds & Bigler, 1996; p. 29). Since the beginning of scientific research in

psychology, memory evaluation has been a vital component of cognitive assessment

(Ebbinghaus, 1885; Wundt, 1906). Intelligence tests throughout this century have

included subtests of memory in one form or another (Binet, 1907; Wechsler scales, 1949,

1974, 1991; McCarthy scales, 1972). However, the format used is often simplistic (rote

recall) and uni-modal (information is usually presented in an auditory mode), even

though memory is clearly more than a unitary concept (Lezak, 1995).

It has been suggested that different aspects or "types" of memory involve different

systems and structures in the brain (Kolb & Whishaw, 1996) and that the type and

14

severity of memory loss will depend on the locus and extent of injury (Sohlberg &

Mateer, 1989). The idea of material specificity (verbal vs. nonverbal/visual) in cognitive

tests in general and memory tasks in particular has been related to different neural

systems. The verbal/non-verbal dichotomy in the field of memory was exemplified by

Brenda Milner at the Montreal Neurological Institute (Mihier, 1971). The author and her

colleagues found that patients who underwent left temporal lobectomy had difficulty with

memory for words or letters but not designs. The opposite was true for patients who had

right temporal lobectomies. They had trouble with memory for designs but not with

memory for words or letters. However, it should be noted that the experiment was

conducted on patients with very discrete lesions. Additionally, while the differences on

psychometric tests were statistically significant, the degree to which they were manifested

in everyday life was unclear. In fact, the issue of hemispheric specialization remains open

to debate even today (Kolb & Whishaw, 1996). Also, as Sohlberg and Mateer (1989)

point out, when it comes to interpreting performance on behavioral/psychometric

measures of verbal and nonverbal/visual memory, caution must be observed as

performance may reflect deficiency in the testee's underlying capacity for language

comprehension and production rather than memory per se. It would be logical to conclude

then that lack of familiarity with a language would affect performance on such a task. It

would also follow that examination of the underlying learning processes involved in

memory tasks could provide a clearer picture of the individual's abilities. However, the

I

narrow band memory tasks included in cognitive batteries rarely allow for such an

examination.

The need to include measures of memory and learning in educational evaluation

and planning is evident. At the same time, certain pragmatic concerns limit our ability to

do this. These issues revolve around the significant effect of demographic variables on

test performance (Reynolds, 1997). There has been a great deal of debate and

investigation around the effect of these variables on performance on general tests of

cognitive ability (Jensen, 1980; Reynolds, 1995). These studies have involved a number

of minority cultures including various groups of Native Americans. Consistent reference

has been made in psychological literature to the differential performance of Native

Americans on standardized tests of intelligence such as the Wechsler Intelligence Scale

for Children-Revised (WTSC-R) and the Kaufinan Assessment Battery for Children (K-

ABC). Most studies involving the Wechsler scales (for example, Browne, 1984;

McCuIIough, Walker & Diessner, 1985) have found a large discrepancy between the

Verbal and Performance Scale scores with a significantly Higher Performance- Lower

Verbal profile. The Performance Scale is purported to measure visual and spatial ability

while the Verbal Scale is said to reflect verbal/auditory abilities (Sattler, 1988).

Davidson's (1992) study on the performance of a Native American group on the K.-ABC

demonstrated that Native American subjects scored significantly higher on Simultaneous

Processing than White subjects. The reverse was true on tasks measuring Sequential

Processing where White subjects significantly outperformed the Native American

16

subjects. The Simultaneous Processing mode is thought to involve "the arrangement or

mental manipulation of stimuli in a simultaneous, holistic maimer," while the Sequential

Processing mode is thought to involve the successive/sequential arrangement of stimuli

(Davidson, 1992).

Consequently, these findings have been linked to distinct cognitive or information

processing styles among Native Americans (Browne, 1984) and further to possible

differences in hemispheric lateralization (Scott, Hynd, Hunt, & Weed, 1979) giving rise

to the concept of "cultural hemisphericity" (TenHouten, 1985) and the "Right-brained

Native American" (Chrisjohn & Peters, 1986). Parallel discussions abound in educational

literature emphasizing the need to adapt school curriculum and teaching strategies to

reflect these cultxirally unique "learning styles" and "cognitive strengths" (Gardner, 1980;

Kaulback, 1984). There have been vehement argxmients against the notion that Native

Americans are more visual/right-brained as opposed to verbal/left-brained learners

(Chrisjohn & Peters, 1986) and against the efficacy of tailoring instructional techniques

to "suit" this style (Cohen, 1985; Davidson, 1992; Kleinfeld & Nelson, 1991). However,

the controversy continues. School drop-out rates for Native Americans are reportedly

significantly higher dian not only White students but also other minority cultures

(Ledlow, 1992). Research surrounding this phenomena continues to cite "cultural

discontinuity" in the classroom as the primary cause for this pattern though empirical

evidence for this hypothesis is inconclusive (Ledlow, 1992).

While literature debating cultural determinants of general ability is abundant,

there is a surprising dearth of information with regard to effects of demographic/ethnic

issues on tests of memory. According to Mayfields and Reynolds (1997) "the question of

the influence of ethnicity on multiple forms of memory remains largely unanswered" and

must be considered when interpreting test performance of minority group members

(p. 113). The burgeoning interest in the inclusion of a more detailed assessment of

memory functioning in the diagnostic and planning process in schools underscores the

need to address this question (Zurcher, 1995). At the time of this study the author could

locate only one study on the performance of any Native American group on a test of

learning and memory.

MacAvoy and Sidles (1991) administered equivalent forms of Navajo-English

free recall word lists using a multi-trial format to 80 Navajo children ranging in age from

8 to 10 years. The authors found that while the 40 children receiving Navajo words

recalled a higher number in Trials 1 and 2 than their counterparts presented with English

words, the groups were evenly matched by Trial 3, and this pattern continued through

Trial 5. The authors concluded that auditory memory assessment could be conducted in

the primary or secondary language for Navajo students provided a multi-trial format is

used. However, the absence of a corresponding visual learning task precludes comparison

of relative verbal vs. visual strengths in this study.

If tests of memory are subject to cultural/demographic influences, are the profiles

exhibited by Native Americans on general tests of ability reflected on tests of memory? In

18

Other words, do they demonstrate relative strengths in visual memory or corresponding

weaknesses in verbal memory? Would opportunities for rehearsal via multiple trials

affect performance on these tasks? How does performance on these tasks relate to

academic achievement? These are some of the questions this study aims to explore.

In summary, the purpose of this study was to compare the performance of a group

of pre-adolescent and adolescent Native Americans on tests of visual and verbal memory,

to investigate the effect that learning and rehearsal may have on their performance, and to

relate performance on these tasks with academic achievement.

19

CHAPTER TWO

LITERATURE REVIEW

This chapter provides an overview of Uterature relevant to the proposed study

including research on the neural systems involved in memory, memory and information

processing among Native Americans, and cultural issues involved in the assessment of

memory.

Neurological Correlates of Memory

Human learning and memory are a function of numerous cognitive operations

mediated by diverse cerebral regions (Delis, 1989) and multiple neural

structures/substrates (Kolb & Whishaw, 1996). Deliberations by neuropsychologists and

neurologists about the neuro-anatomical correlates of this cognitive domain reflect this

complex view of memory. Stemming from the conceptualization of memory as a

multidimensional phenomenon are a number of dichotomous or two-factor theories of

"types" of memory; implicit vs. explicit memory (Kolb & Whishaw, 1996; Schacter,

1992), declarative vs. non-declarative memory (Squire, 1993), short-term vs. long-term

memory (or primary vs. secondary memory; Atkinson & Schiffrin, 1971; Baddely, 1986;

James, 1890) among others. It should be noted however that these labels are neither

necessarily exclusive of each other nor are they always interchangeable. They only denote

differing theoretical and experimental approaches to the study of memory. For example,

short- and long-term memory are generally thought of as being part of the declarative

memory system (Squire, 1987).

20

It has been suggested that different "types" of memory involve different structural

bases as do different memory "tasks." According to Kolb and Whishaw (1996) for

example, long-term (LTM) and short-term memory (STM) are mediated differently. They

also point out that within the domain of STM, mechanisms for auditory and visual

abilities are not the same though they may overlap. It has been recommended therefore

that "evaluators should not interpret tests of short-term auditory memory and short-term

visual memory as measures of the same construct" (McGhee, 1994, p.297). The first

section of this chapter enumerates some of the types of memory described in literature

and also provides a brief overview of their neurological correlates.

Retrograde and Anterograde Amnesia

Amnesia (memory loss) for information acquired prior to injury or neural insult is

called retrograde amnesia. Amnesia for new information (information presented for

learning after the injury) is called anterograde amnesia. Retrograde amnesia may be

assessed by asking the patient to recall autobiographical information (Barbizet, 1970) or

by testing his/her general information such as naming famous celebrities or television

shows from various years (Squire & Slater, 1975). Anterograde memory is assessed by

asking a patient to leam new material. Measures therefore overlap with those used to

evaluate explicit or declarative memory. A distinction between recent vs. remote memory

is made within the temporal dimension of retrograde amnesia. Remote memory refers to

events in the individual's distant past while recent memory refers to knowledge acquired

just prior to insult/injury.

21

Short- and Long-Term Memory

In 1890 William James proposed a distinction between what he called "primary"

and "secondary" memory. This dichotomy, now generally referred to as Short term and

Long term memory (STM and LTM, respectively) (Atkinson & Schiffrin, 1971;

Broadbent, 1958), is one of the earliest and most lasting concepts in the field of memory.

STM usually refers to maintenance of information presented a brief period before

recall or recognition. It is thought to be limited in capacity (about 7 + 2 units of

information) and to undergo rapid decay in the absence of rehearsal (Peterson & Peterson,

1959). It is sometimes also called "working memory" a concept proposed by Baddeley &

Hitch (1974). Working memory allows information to be held in temporary storage while

mental operations are performed or while attention is temporarily shifted to other stimuli.

Baddeley suggests that there are two kinds of working memory, a visual-spatial one (to

spatially locate objects) and a phonological one (that holds verbal information). LTM

implies storage and subsequent retrieval (through recall or recognition) of information

"sometime" after the initial presentation. It involves a period of delay or a degree of

distraction in that the examinee's attention is focused away ft-om the target items and on

to other information before recall or recognition is requested.

Since there seems to be a lack of consensus among psychologists regarding the

time frame involved in both these concepts, Kramer and Delis (1998) recommend the use

of task-specific terms such as "immediate recall" and "30-minute delayed recall" in

assessing memory performance.

Explicit and Implicit Memory

Explicit Memory or Declarative memory, is described as memory that involves

conscious or intentional acquisition, retention, and recollection of previous experiences

(Gabrieli, 1998; Kolb & Whishaw, 1996). It is measured by direct tests of memory (such

as, free recall, cued recall, recognition) that explicitly refer to a prior experience. Brian

regions implicated in explicit memory include diencephalic and medial-temporal systems,

neocortical systems, the frontal lobe, and fronto-striatal systems.

Diencephalic lesions that produce amnesia (such as in patients with Korsakoff s

syndrome) seem to involve the medial-thalamus and sometimes the mamillary bodies of

the hypothalamus (Press et al., 1989). Evidence suggests that it is damage to the medial

thalamic region (not the mamillary bodies) that affects explicit memory (Gabrieli, 1998;

Kolb & Whishaw, 1996). The medial-temporal lobe memory system consists of multiple

structiu^es including the perihippocampal and perihinal cortices, the hippocampal region

(composed of the subiculum, the CA fields, and the dentate gyrus), and the amygdala.

There is convergent evidence for the participation of medial-temporal regions in

explicit memory. Mibier (1971) has demonstrated that unilateral left or right lesions

produce material-specific memory deficits for verbal and non-verbal material,

respectively. Medial-temporal activations (in neuroimaging studies) are observed during

intentional memory retrieval (Schacter et al., 1996; Squire et al., 1992). Post-mortem

analysis of amnesic patients with medial-temporal damage suggests that injury restricted

to the CAl field is sufficient to produce clinically significant anterograde amnesia while

23

damage encompassing additional medial-temporal structures exacerbates both the

severity of the anterograde amnesia and the temporal extent of the retrograde amnesia

(Gabrieli, 1998). Since structures in the medial-temporal lobe receive inputs from the

adjacent cortex it might be expected that neocortical lesions could also produce explicit

memory deficits.

Explicit memory is considered to be a function of an interaction between medial-

temporal/diencephalic and neocortical brain regions. Cortical injuries in the parietal,

posterior temporal, and possibly occipital cortex sometimes produce specific long-term

memory difficulties (Kolb & Whishaw, 1996). This together with the fact that medial-

temporal or diencephalic lesions spare remote memories has encouraged the view that

long-term memory is primarily stored in the neocortex. Left frontal activations have been

found for verbal (Demb et al., 1995) and nonverbal stimuli (Haxby et al., 1996).

However, it seems that the activation is most closely linked to semantic processes

associated with language (Gabrieli, 1998). Patients with frontal lobe lesions have

increased impairments on tasks that have greater strategic demands such as tests of free

recall (Janowsky et al., 1989) or recency or temporal order judgments (Milner, 1971).

Patients with degenerative or developmental diseases of the basal ganglia (such as

Paridnson's Disease or Huntington's Disease) show selective deficits of strategic

declarative memory (Gabrieli, 1996). Striatal diseases also impair reasoning (Lees &

Smith, 1983) and reduce working memory capacity. Further, dopamine treatment appears

to enhance working memory performance in Parkinson's Disease patients (Cooper et al..

24

1992). It has therefore been hypothesized that lesions to the dopaminergic fronto-striatai

system reduce working memory capacity which limits reasoning ability and consequently

impairs strategic memory performance (Gabrieii, 1997).

The basal forebrain (which is just anterior to the hypothalamus) is the source of a

number of pathways to the forebrain, including cholinergic fibers. Serotonergic cells in

the midbrain and noradrenergic cells in the hindbrain also project to the limbic system

and cortex. While these cholinergic and serotonergic cells are not believed to be involved

in the storage of memory per se they are thought to play a role in maintaining activation

in the cortical and limbic areas. Animal studies suggest that removal of any one of these

cell groups by itself does not result in significant memory loss. However, if the

serotonergic cells in the midbrain and tlie cholinergic cells in the basal forebrain are

damaged together profound amnesia can be produced (Kolb & Whishaw, 1996).

Functional neuroimaging and lesion studies illuminate the importance of the

amygdala in declarative memory. However, it's role appears to be limited to the

emotional aspects of memory (Cahill et al., 1996; Fink et al., 1996).

"Implicit Memory" is described as an unconscious or nonintentional form of

memory (Kolb and Whishaw, 1996) and involves the "acquisition, retention, and retrieval

of knowledge expressed through experience-induced changes in performance" (Gabrieii,

1998, p.88). It is typically assessed by "non-declarative" or indirect tests where no

reference is made to that experience. Skill learning (or procedural memory), repetition

priming, and conditioning are classes of implicit memory tests. Skills may be

25

sensorimotor (e.g., mirror tracing or rotary pursuit), perceptual (e.g., mirror reading), or

cognitive (e.g., tower tasks) in nature. Both mirror tracing and rotary-pursuit skill

learning have been shown to be intact in patients with explicit or declarative memory

problems due to amnesia (Corkin, 1968) or Alzheimer's Disease (Gabrieli et al., 1993;

Heindel et al., 1989).

Petri and Mishkin (1994) have suggested a neural-curcuit structure for implicit

memory with the basal ganglia (BG) structures (caudate nucleus and putamen) at its

center. The BG receive projections from the neocortex and send projections via the

ventral thalamus to the premotor cortex. These circuits are said to be involved in

charmeling sensory information received from the sensory cortex to the cortical motor

areas. Cells in the substantia nigra also project to the BG. These latter projections contain

the neurotransmitter dopamine, which therefore may be indirectly involved in memory

formation. While patients with BG diseases demonstrate impaired performance on

sensorimotor skill learning, the effects are not uniform. Gabrieli et al. (1997) found that

patients with Huntington's Disease showed a dissociation between impaired rotary-

pursuit and intact mirror-tracing skill learning. Cerebellar lesions have also been found to

impair mirror-tracing skill learning (Sanes et al., 1990). Functional neuroimaging studies

have supported the role of the BG and the cerebellum in sensory motor skill learning. In

addition they have revealed the importance of the motor neocortex in such learning. For

example, rotary-pursuit skill learning is associated with increases in activation of the

primary and secondary motor cortices (Grafton et al. as cited in Gabrieli, 1998).

26

In addition to sensory motor skills, acquisition and retrieval of perceptual and

cognitive skills has also been examined in memory study paradigms. Learning to read

mirror-reversed text is one such perceptual skill. In one study Martone et al. (1984) found

that patients with Huntington's Disease had impaired performance on this task despite

relatively good explicit memory for words read and recollection of reading experiences.

In contrast, patients with Korsakoff s Syndrome acquired the skill at a normal rate,

despite poor explicit memory for the words read or the episodes in which they gained

their skill. Huntington's Disease and Parkinson's Disease patients (both diseases

involving the BG) have exhibited impaired performance on tower tasks (Saint-Cyr et al.,

1988), while amnesic patients appear to exhibit normal learning on this task under some

circumstances. The basal ganglia therefore seem to be critical in a variety of motor,

perceptual and cognitive skills.

Priming refers to a change in the processing of stimulus material, usually words or

pictures due to prior exposure to the same material (Gabrieli, 1997). In a typical

experiment the subject may be shovm a list of words and later be given a word fragment

and asked to identify what the word might be. For example, one word on the list may be

"tablet" and the word-fragment may be "tab." It has been shown that amnesic patients

who show no conscious recollection of the previous list exhibit normal magnitudes of

priming on many tasks including word-fragment completion (Vaidya et al., 1995).

Similar dissociations between priming and explicit memory have been obtained even with

normal subjects (Roediger & McDermott, as cited in Gabrieli, 1998).

27

Episodic and Semantic Memory

Tulving (1983) further subdivided declarative memory into episodic and

semantic memory. Episodic memory refers to memory for specific events that can be

assigned to a particular time and place in one's life. Semantic memory refers to one's

general knowledge of the world and is not temporally linked. Thus, asking an individual

to define breakfast would assess an aspect of semantic memory while asking an

individual to recall what he/she ate for breakfast that particular morning would constitute

an assessment of episodic memory.

Learning and Memory

Learning and memory are closely related concepts and the assessment of both is

considered to be of vital importance in differential diagnosis of disorders involving

memory problems. "Learning is the process of acquiring new information, while memory

refers to the persistence of learning in a state that can be revealed at a later time" (p.3)

(Squire, as cited in Delis, 1989).

Most tests evaluate amount of information recalled on an immediate or delayed

trial thereby assessing amount of learning that persists or is retained. However, tests

providing for multiple presentations of the same material afford a means of evaluating the

process of learning or acquiring new information. In other words, they allow for an

examination of the occurrence and rate (increase or decrease) of learning over successive

trials. Many of these tests assess recall after a delay and thus provide a measure of

memory "decay" or forgetting. Some examples include the Rey Auditory Verbal

28

Learning Test (Lezak, 1983), the Paired-Associate subtest of the Wechsler Memory Scale

(Wechsler, 1987), and the California Verbal Learning Test (Delis et al., 1987). There is

some evidence that patients with differing CNS dysfunction vary significantly in their

pattern of performance on multiple trial tests (Lezak, 1983). Therefore, assessment of

both learning and memory variables could provide valuable diagnostic information.

Memory and Information Processing in Native Americans

Of related interest to this study is the literature on hemispheric lateralization in

Native Americans. It is generally accepted that in most right-handed humans, language-

related processes are for the most part left-lateralized as are processes for recall or

recognition of sequential information. The right hemisphere on the other hand appears to

specialize in certain spatial-relational processes particularly in the visual modality and in

the processing of emotional information (Kinsboume, 1997). Further, in the right handed

majority, damage to the left temporal lobe and adjacent structures has a tendency to affect

verbal and sequential memory while damage to the corresponding area of the right

hemisphere affects visual and spatial memory more adversely (Kolb & Whishaw, 1996;

Reynolds & Bigler, 1997). The idea that Native Americans may deviate from this dextral

norm took root when a number of studies demonstrated the "superior" performance of

Native American groups on tests of visual-spatial skills (Berry, 1966; Kaulback, 1984).

Subsequent research aimed at supporting the claim that distinct cognitive styles may be

linked to cultural differences on the one hand and information processing differences

between hemispheres on the other, thus building on the notion of "cultural

29

hemisphericity." This section presents literature relevant to the notion of distinct

information processing styles in Native Americans.

In 1942, Dennis administered the Draw-A-Man (DAM; Goodenough, 1926) to

Hopi NA boys and attributed their remarkably high scores to the emphasis the culture

places on male art skills. Cundick (1970) tested Southwest Native American

schoolchildren using the DAM and the WISC (Wechsler, 1949) and surmised that their

relatively normal scores on the Performance Scale of the WISC as well as the DAM

deemed these instruments reliable measures for collecting normative data from children

in the Southwest United States. In the National Study of American Indian Education,

17,000 Native American primary school children representing 14 tribal groups living in

12 states were surveyed (Levensky, 1970). Subjects were entire classrooms of children in

grades I through 6 who were pupils in Bureau of Indian Affairs' public and private day

and boarding schools. Protocols were analyzed by sex, age, reservation, urban and tribal

group, and geographic area. Levensky concluded that compared to "Euroamerican"

children the performance of these children was superior between the ages of 6 and 8 years

but inferior between the ages of 8 and 13.

The findings of the DAM studies had a tremendous impact in the field of Native

American Education in that they shattered the notion that Native Americans were inferior

in intellect to the White majority. They also seem to have set the precedence for the

notion of the "Visual" Native American who was better able to respond to visual stimuli

than "to tests which emphasized verbal and auditory skills" (Kaulback, 1984; p. 28).

30

The ITPA or the lUinois Test of Psycholinguistic AbiUties, is comprised of a

series of subtests designed to probe the receptive, associative, and expressive processes

both auditory and visual, used by each learner. It has been used by a number of

researchers to study the psycholinguistic abilities of Native American children. Garber

(1968) assessed 110 Navajo and Pueblo first grade children using the ITPA. He found

them highly competent at processing visual information, which involved memory for

visual designs, manipulating pictures and designs and understanding visual associations.

They were not however as adept at tests measuring auditory skills. Lombardi (1970)

tested 80 first grade Papago children from integrated and segregated schools. Like Garber

(1968) he found that Native American children from both types of schools achieved

unusually high scores (as compared to normative data) on subtests measuring visual

sequencing memory while scoring significantly below noraiative standards on tests

measuring auditory processing (such as auditory reception, auditory association and

grammatic closure).

Similar results were obtained in another testing program (Kuske, 1969), involving

a group of mentally handicapped Sioux children and 50 comparable non-Native

American handicapped children. In a review of these studies Kirk (1972) compared

Native American group averages with means for African American children and the

original non-Native American standardization samples. He deduced that Native

Americans possess superior ability in visual sequential memory ability compared to

African American and White children. He further concluded that these visual memory

31

abilities were better developed in the Native American samples than the other abilities

tested by the battery.

Studies using the Wechsler Scales (Wechsler, 1949, 1974, 1991), arguably the

most widely used instrument in the field of psychology, have played a large part in

substantiating the "visual learner" stereotype of the Native American. Based on the use of

Baimatyne's (1974) recategorization of the WISC, a number of researchers have proposed

that Native Americans have a "typical cognitive pattern" (Diessner & Walker, 1986;

McShane & Plas, 1982). Bannatyne suggested that the WTSC subtests be recategorized to

yield the following ability scores: (1) Spatial, based on Picture Completion, Block

Design, and Object Assembly; (2) Conceptual, based on Comprehension, Similarities,

and Vocabulary; (3) Sequential, based on Arithmetic, Digit Span, and Coding; and (4)

Acquired Knowledge, based on Information, Arithmetic and Vocabulary. McShane and

Plas (1982) applied this factor scheme to WISC scores of Ojibwa and Sioux children with

school difficulties and noticed a pattem of performance different from that associated

with samples of learning disabled children. They found that Spatial scores were

significantly greater than Sequential scores, which in turn exceeded Conceptual and

Acquired Knowledge scores. This profile was most evident in the subgroup of children

identified as experiencing a more traditional Native American cultural heritage (as

assessed by the Traditional Experience Scale of McShane, 1980). Connelly (1983)

demonstrated this pattem for Tlingit Native American children while Zarske and Moore

(1982) did so with Navajo children. A similar profile with the WISC-R was later evident

for Yakima children (Diessner & Walker, 1986).

A number of other studies utilizing the WISC have reported normative

Performance IQs with corresponding low Verbal IQs (Dorsch, 1980; Guilliams, 1975; St.

John et al., 1976). Relatively fewer studies have been reported using the WISC-R with

Native American groups. In one such study Hynd, Kramer, Quackenbush, Conner. &

Weed (1979), assessed 44 primary schoolchildren attending a reservation boarding

school. All children had Navajo rather than English as their primary language. Test

means for the Verbal, Performance and Full Scales were 64, 95, and 77 respectively. The

lowest scores occurred on Verbal subtests measuring receptive and expressive English

skills. The authors proposed that Performance subtests appeared to present an adequate

and relatively non-biased estimate of potential.

Browne (1984) analyzed the performance of 197 Native American children on the

WISC-R. The 90 girls and 107 boys ranged in age from six to sixteen and were residents

at a boarding school in South Dakota. They represented all nine tribes in South Dakota,

one tribe in North Dakota and one in Nebraska. The purpose of the study was to explore

and identify "characteristic cognitive processing strengths" of Native Americans. As with

all previous studies of the WISC-R on Native American children (e.g., Dorsch, 1980),

Browne (1984) found a Higher Performance- Lower Verbal (P-V) pattern for this group.

Factor analysis indicated that Picture Completion (PC) and Coding played a different role

for these subjects as compared to the WISC-R standardization population. Coding did not

33

contribute to the Freedom from Distractibility factor and PC showed a high degree of

specificity rather than contributing to the Perceptual Organization factor. Both subtests

loaded on a fourth factor in an inverse relationship for males in all groups and the older

group in general.

Native American students of the Columbia River Basin in Washington State were

the subjects of McCullough, Walker, and Diessner's (1985) study. A sample of 75

students in grades 7 through 12 were divided into two age groups and administered the

WISC-R and the WAIS. Forty two subjects (21 males and 21 females) aged 12 to 16 were

assessed on the WISC-R and 33 subjects (9 females, 24 males) aged 16-19 were assessed

on the WAIS. All of the students attended a private tribally operated school. Mean scaled

scores for the younger group were 79.92 and 99.19 on the Verbal and Performance

Scales, respectively. Mean scaled scores for the older group were 90.64 on the Verbal

Scale and 106.21 on the Performance Scale. The correlation between the two scales was

insignificant at the .05 level of probability. The researchers concluded that the findings

supported their hypotheses, mainly that there would be a significant difference between

scores on the two scales and that the correlation between the scales would be so low as to

preclude the Full Scale from being an accurate representation of the "g" factor indicating

that the two scales measure independent abilities.

The Kaufman Assessment Battery for Children (K-ABC; Kaufman & Kaufrnan,

1983) was developed around Luria's simultaneous/successive processing model and was

the instrument of choice in Davidson's (1992) study. Davidson aimed at comparing the

34

relative cognitive strengths of Native American and White students based on their

performance on this test. Subjects were 57 American Indian and 60 White students

ranging in age from 7 years to 12 Vx years. All subjects attended schools within a single

school district in South Central Montana. They had been referred for testing for possible

placement in an enrichment program for students of high ability. The two groups did not

differ significantly on the Mental Processing Composite (a measure of general

intelligence). Native American subjects as a group scored significantly higher than White

subjects in Simultaneous Processing, and White students as a group scored significantly

higher than Indian subjects in Sequential Processing. However, the researchers also

reported that while 47% of Native American subjects showed a pattern favoring

Simultaneous over Sequential Processing, 49% showed no significant discrepancy

between the two processing modes. Similarly, 73% of White children showed no

significant discrepancy between the two processing scales. The authors therefore caution

against overly simplistic generalizations to the effect that all Native American students

process information in a simultaneous/ holistic manner or that all White students do so in

a sequential manner.

Numerous explanations have been advanced to account for the Native American

child's relative strengths on visual tests of ability and memory. These broadly represent

three schools of thought - ecological, socio-cultural, and neuropsychological.

35

The Ecological View

Berry (1966, 1971) presents a convincing argument for the role of ecology in the

development of visuo-spatial skills among some Native American groups. His original

argument (Berry, 1966) was that the ecological demands placed on a people together with

their cultural adaptation to this ecology (via cultural "aids" such as language, arts and

crafts, and socialization), would lead to the development of certain perceptual skills. To

this extent he compared the performance of a group of Canadian Inuit Eskimos to that of

the Temne of the Sierra Leone (an African agricultural society) and found that the former

group scored significantly higher on various spatial and visual discrimination tests. In

fact, the results were so divergent that author doubted the "functional equivalence" of the

tasks. He then proceeded (Berry, 1971; McShane & Berry, 1988) to rank a niunber of

samples from various cultural groups on the "ecology dimension" (from

hunting/gathering to agricultural/pastoral) and to examine the relationship between the

ecological and behavioral/perceptual factors. Eight samples of "subsistence-level" people

were studied including the Inuit, Temne and Scots (the last used as a western comparison

group). These were divided into two groups, traditional and transitional, to allow for an

assessment of the impact of acculturation. Results indicated that the Inuit subjects far

surpassed the comparison groups on all measures. Berry concluded that people attain

levels of visual discrimination and spatial ability appropriate to ecological demands

placed on them.

36

Kleinfeld (1971) compared the performance of village Inuit and urban White

children on "image memory" tests, which required the ability to recall complex visual

patterns. She proposed that this perceptual task was closely related to those ecological

demands made by hunting in an arctic environment. She found Inuit children in all age

groups siu^jassed the urban White children in their ability to recall the images. In the

same study Kleinfeld also reported numerous references to the highly acute visual skills

of the Inuit in historical and ethnographic research including their ability to draw accurate

detailed maps and comprehend images regardless of spatial orientation.

The work of these researchers presents compelling evidence for the role of

ecology in the development of percepmal skills. However, as BCaulback (1984) notes,

there are many more Native American children "unexposed to the harsh realities of

hunting and trapping and a subsistence way of life" (p. 31) who appear to have superior

visual-spatial skills. In fact Berry himself (1971) reported that Inuit children from an

urban center outperformed Inuit children from a more traditional setting on the test of

visual discrimination though hunting activity among them had diminished greatly. Also,

as McShane and Berry (1988) point out. Native American have been undergoing a

process of acculturation to outside (mainly of European origin) groups for hundreds of

years and their way of life has altered dramatically with changing ecological conditions.

Investigators looked for reasons beyond the ecological domain and two groups of

explanations emerged, socio-cultural and neuropsychological.

37

The Socio-cultural View

Berry (1971) listed socialization as one of the mediating factors affecting the

ecology-individual interaction. He proposed a distinction between content of

socialization, which emphasizes developing personality characteristics appropriate for the

group's economic pursuit, and techniques of socialization that would encourage either

"field-independence" (and consequently an "analytic" approach to the perceptual field) or

"field-dependence" (leading to a "global" approach to a perceptual field). Based on the

self-report of the subjects he concluded that the Inuit did in fact employ lenient forms of

discipline and encouraged independence and responsibility (field-independence) while

the Temne employed harsh techniques and emphasized social conformity (field-

dependence).

Besides Berry (1971) there have been a number of references in ethnographic

literature to the child-rearing practices and consequent "cognitive style" of the Native

American. Reports about the structure of the Native American family suggested that

adults based their instruction upon modeling and children learned mainly through

imitation, thus rendering verbal instructions redundant and resulting in social interactions

that were primarily non-verbal in nature (Kroeber, 1970). Cazden and John (1969)

referred to this as "observation learning" and the concept of a distinct "cognitive style"

among Native Americans continues to be popular in the field of education and

psychology (Gardner, 1980; Kaulback, 1984)

38

A natural consequence of these investigations was the search for a physiological

explanation for these findings. Extremely high rates of hearing loss after ear infections

have been noted among some Native American children aged 0 to 2 years. This is a

critical period for language development and many researchers have linked these

incidents to reductions in language ability, lower academic achievement in reading, math,

and language areas and to other weaknesses in psycholinguistic skills (Gottlieb & Green,

1984; McShane & Plas, 1982). The idea of distinct cognitive styles was taken further by

the field of neuropsychology in its attempt to establish the notion of "cultural

hemisphericity."

Neuropsychological Research

Based on Luria's (1974) proposition that language and thinking are influenced by

a dynamic interaction between the brain and it's environment, Rogers, TenHouton,

Kaplan and Gardiner (1977) suggested that different languages may be more suited to

some cognitive processes than others. They hypothesized that Hopi and English

languages differ in the degree to which they serve as instruments of thought in a left

hemisphere "prepositional" mode or in a right hemisphere "appositional" mode. They

further hypothesized that the extent of right hemisphere participation in processing

speech should be greater for Hopi than for English. They assessed 16 bilingual children

in the fourth, fifth and sixth grade classes. The children were right-handed, spoke Hopi at

home and learned English as a second language "to some extent" after they started

school. EEG data was collected from electrode placements over the left and right frontal

39

and parietal lobes of the children as they listened to tape recorded children's stories in

Hopi and English. Alpha desynchronization was greater for the right hemisphere parietal

leads during the Hopi story as compared to the English story. A similar lateralization

effect was found when comparing EEGs during the Streets Gestalt Completion Test

(1931; considered a measure of right hemisphere performance) and the WTSC Similarities

test (1952; considered a measure of left hemisphere functioning). Rogers and his

colleagues concluded that the results directly supported their hypotheses implying that

"linguistic relativity may exist on a neuro-linguistic level (p.l)."

In a later study, TenHouton (1985) reported that Australian Aboriginal children

performed better than White children on the Gestalt Completion test while doing worse

on the WISC-R Similarities test. Subjects were urban children selected from two Greater

Sydney areas having substantial Aboriginal subpopulations.

Scott, Hynd, Hunt and Weed (1979) studied the performance of Navajo adult

students on a dichotic listening task. Thirty pairs of dichotically presented CV

(consonant-vowel) syllables were presented to 20 (10 male, 10 female) Navajo college

students ages 18-27 identified as right-handed. Each subject was matched to an Anglo

college student according to age, sex and handedness. The researchers reported that while

the Anglo students showed the traditional right-ear advantage, Navajo students

demonstrated a left-ear advantage. They suggest that different ethnic groups may be

predisposed toward developmental variations in neuropsychological asymmetries and that

these may be attributed to environmental differences including language characteristics.

40

To further test the hypothesis that Native American Navajo possess a reverse

(right hemisphere) language function dominance, McKeever (1981), administered the

Lateralized Object Naming Latency task. Outline drawings of five objects (clock, apple,

lamp, moose and shoe) were presented at 100 ms exposures in either left or right visual

half-fields and subjects were required to identify the object as quickly as possible. In an

earlier experiment (McKeever & Jackson, 1979), the author had reported that 19 of 20

Anglo subjects showed a strong right visual field (RVF) superiority on the task. Results

of the Navajo study were similar in that 19 of the 20 subjects demonstrated RVF

superiority. The author concluded that both the direction and magnitude of language

laterality appear to be identical in Anglo and Navajo persons. Since 13 of the 20 subjects

described themselves as bilingual and seven as essentially monolingual (English), the

author surmised that there was no evidence to suggest that differences in the degree of

competent bilingualism were associated with differing degrees of RVF superiority.

McKeever suggested that strategy differences of some kind might be responsible for

Navajo-Anglo differences found in the Scott et al study (1979).

Culhiral Issues in Assessment

A great deal of empirical research and evidence has accumulated around the issue

of potential cultural biases and other effects of racial and other demographic variables on

tests of intelligence and personality (e.g., Atkins, 1995; Reynolds, 1995). Reynolds

(1997) has argued that demographic variables have a significant influence on test

performance. He delineates a number of reasons why performance on various tasks may

41

be biased by cultural factors. These include, a lack of equivalence of testing conditions,

functional inequivalence across groups, linguistic inequivalence, different latent

structures of tests across groups, different affective responses to the examination and/or

examiner, differences in the reliability of measurement, validity of interpretations of

performance, and content validity of items among others.

Whenever the pursuit of equivalence is neglected the fundamental requisite of

construct validity is at stake and this issue is encountered whenever communication

involves the use of one language or another (McShane & Berry, 1988). In light of these

concerns, do lower verbal scores relative to visual-spatial skills mean much when verbal

abilities are assessed in a second language? In the one report of an attempt to assess

verbal ability in the native language, Mawhinney (1983) found a small but significant

(+.28) correlation between a Cree Picture Vocabulary Test and Kohs Blocks among

James Bay Cree. However, in the absence of a wider normative context it is difficult to

extrapolate any evidence of the relative levels of achievement on visual and performance

tasks.

In a study mentioned earlier, St. John et al. (1976) found the higher (normal

range) Performance, lower Verbal profile on the WISC for 100 Cree and Ojibwa children

in all age ranges (7 through 15). However, the authors also found that these differences

decreased with age and that familiarity with the English language increased the Verbal IQ

but had little impact on Performance IQ.

42

McAreavey (1975) administered the WTSC and WRAT to handicapped South

Dakota Sioux children to determine the extent of "fairness" or "bias" exhibited by these

tests when used with a selective sample such as this. Results suggested significant PIQ-

VTQ differences but when second language norms were used 5 subtests demonstrated

ordering discrepancies in the scaling of items, suggesting item bias. In another study on

item bias Mishra (1982) investigated cultural bias in the WISC-R. While the entire test

was administered to 40 Anglo and 40 Navajo children (matched for grade level)

performance on only three verbal subtests - Information, Similarities and Vocabulary

were analyzed. Of the 79 items comprising these subtests 15 (19%) were found to be

biased against the Navajo sample. Five of these were fi-om Information, 4 from

Similarities, and 6 from the Vocabulary subtest.

In a scathing attack on the "science fiction" nature of the myth of the "right-

brained Native American", Chrisjohn and Peters (1986) dismiss the body of literature on

Wechsler Scale profiles and the neuropsychological studies on two accounts. First they

argue that the findings of the neuropsychological smdies are worthless due to one

methodological oversight, namely, that the investigators were not "blind" to the race of

the subject. Second, they argue that any cultural biases come to bear more heavily on the

Verbal than Performance categories of the test. To substantiate their view they cite the

work of Taylor, Zigler and Pertino (1984; in Chrisjohn & Peters, 1986). These authors

demonstrated Verbal-Performance discrepancies among non-Native Americans who lived

in subcultures different from the surrounding American middle-class culture.

43

Does "less biased" then mean only "less different" from majority Anglo norms?

And while the higher Performance- lower Verbal profiles within Native American groups

may be an artifact of depressed second language performance, are findings of

significantly elevated scores (compared to normative standards) on visuo-spatial tasks by

certain Native American groups to be ignored? Further, if differences are a function of

familiarity with the second language would opportunities for rehearsal and learning affect

this gap? Finally, how do these issues come into play on tests other than those measuring

intelligence, on tests of memory for example?

Memory assessment is crucial in the fields of education, psychology and

medicine, and there is some evidence to suggest that memory processes may be subject to

cultural factors at least in the case of Afncan Americans (Jensen & Figueroa, 1975;

Kamphaus & Reynolds, 1987). Memory tests span a range of behaviors from simple (e.g.,

digit recall) to significantly complex (e.g., multiple trial learning tasks or story recall after

delay/interference). However, until recently there has been no investigation of racial

differences on a comprehensive set of memory tasks. Mayfield and Reynolds (1997)

examined performance differences for blacks and whites using standardization sample of

the Test Of Memory And Learning (TOMAL; Reynolds & Bigler, 1994). Of the 14 tests

administered, only one significant difference across race was found. On Letters Forward

blacks scored significantly higher than whites. As Reynolds (1997) points out, all

neuropsychological measures (including tests of memory) must be evaluated for cultural

44

effects as "findings in this area do not generalize across tests or necessarily across

nominal groups" (p. 182).

Summary

At first glance two general but rather simplistic conclusions may emerge from the

literature reviewed above- that Native Americans process information differently from

the average Anglo middle class American and that this distinct cognitive style is

primarily visual in nature. Indeed, the field of education appears to have embraced these

beliefs. A number of education professionals have propagated the view of the right-

brained-visual-North American and the need to adapt curriculum to best suit this style

(Gardner, 1980; Kaulback, 1984). Yet evidence to support the hypothesis that Native

American students leam more with visually based instruction is minimal and

contradictory at best (Kleinfeld & Nelson, 1991).

Given the highly unclear evidence regarding cultural determinants of verbal and

visuo-spatial skills in general, and performance on tests of memory in particular, the

present study is an attempt to investigate the performance of Native American subjects on

visual and verbal memory tasks. It fiuther aims to explore the effect of learning and

rehearsal on both immediate and delayed recall on these tasks.

45

CHAPTER THREE

METHODS

This chapter will describe the sample targeted for study, the instruments used, and

the procedures followed for the collection and analyses of data.

Sample

Subjects included 15 Native American children (10 males, 5 females) from a

school district in a rural reservation in Southern United States. Ninety nine percent of the

district's population is Native American. Subjects ranged in age from nine years, 0

months (9:0) to fifteen years, two months (15:2) (X = 12:22). Almost all subjects came

from homes that were economically below the poverty line.

Participants in this study were part of a larger group of subjects who composed

the control group for a broader study. The larger study aimed at examining effects of

Fetal Alcohol Syndrome (FAS) and Fetal Alcohol Effects (FAE) on frontal lobe

ftxnctioning. Confrols for the larger study were obtained by receiving district enrollment

records and identifying the sex-matched child with the birth date closest to that of the

respective FAS/FAE child. Controls were not receiving special education services and

had no learning problems or history of FAE at the time of the study.

Subjects for the larger study ranged in age from 6 to 17. However, only children

aged 9 and above were included in the present study because testing requirements

(number of items to be administered) for younger children are different on the Verbal

Leaming and Visual Learning subtests of the Wide Range Assessment of Memory and

46

Learning (WRAML; Sheslow & Adams, 1990). Given that the primary aim of this study

was to examine performance on these two subtests of the WRAML, it was thought that

inclusion of the younger children would confound results and findings.

Participation in this study was contingent upon receiving written parental

permission to be tested. Parents were apprised of the nature of the experiment as well as

the risks and benefits involved, and had the right to withdraw permission at any time if

they chose to do so. Subjects signed an assent form before being included in the study.

The approval of the University of Arizona Institutional Review Board (Human Subjects

Committee) was obtained (see Appendix).

Instrumentation

Each participant was administered a battery of tests including the three described

below as well as a number of tests purported to measure fi"ontal lobe functioning. Since

this study focused on performance on the Visual- and Verbal-Learning subtests of the

WRAML and its possible implications in terms of educational performance, only tests

relevant to the purpose of the study have been outlined.

1. Wide Range Assessment of Memory and Learning (WRAML; Sheslow & Adams,

1990).

2. Wechsler Intelligence Scale for Children-Third Edition (WISC-UI; Wechsler, 1991).

3. Differential Abilities Scale - School Achievement Tests (DAS; Elliot, 1983).

47

The Wide Range Assessment of Memory and Learning (WRAML)

The WRAML is one of the first standardized, comprehensive measures of

memory functioning in children, h is a well standardized psychometric instrument which

allows the evaluation of a child's ability to actively leam and memorize a variety of

information. It was normed for children aged five to 17 years. There are three major

"structural" divisions within the WRAML. The first makes a distinction between memory

and learning (single vs. multiple trial recall), the second between modality of information

presented (visual/verbal), and the third involves time between task administration and

recall demand (short^within seconds, or delayed/within 20-40 minutes). There are three

verbal, three visual and three learning subtests, yielding a Verbal Memory Index, a Visual

Memory Index and a Learning Index. For each of the nine subtests a scaled score can be

obtained. For the Verbal, Visual and Learning Indexes, as well as the General Memory

Index, standard scores, and percentiles can be derived.

The entire WRAML was administered to allow computation of the Index Scores.

This study examined performance on the Visual Learning and Verbal Learning subtests.

Following is a description of these two subtests:

Verbal Learning Subtest. The Verbal Learning Subtest was adapted firom the Rey

(1958). Children nine years and older are read a hst of 16 non-related words. After the

words are presented the child is asked to recall as many words as she/he can (immediate

recall), in any order (i.e. using a fi-ee-recall paradigm). Three additional presentation and

48

free recall trials follow. This allows for analysis of a learning curve over trials. A delayed

recall trial (after 20 to 40 minutes) is also included.

Visual Learning Subtest. The Visual Learning subtest is also comprised of four

presentation trials, each of which is followed by a free-recall trial. The stimuli are visual

designs (14 designs for children nine and older) presented in a particular position on a

board. The child is required to remember which spatial location is associated with which

design. Immediate feedback as to the correctness of the child's responses is provided.

Similar to the Verbal Learning task a delayed recall trial can be administered after an

intervening task (20 to 40 minutes).

Norms. 2363 children were included in the norm sample for the WRAML.

Selection was based on the 1980 U.S. Census and the 1988 Rand McNally Commercial

Atlas and Marketing Guide. Table I shows ±e percentage of individuals from various

racial sub-categories included in the norm sample.

Reliabilitv. Three types of reliability indexes were calculated: coefficient alpha,

person separation, test-retest. The first two are measures of internal consistency while the

third is a measure of test stability. Correlation coefficients for the two learning subtests

and the Index scores are presented in Table 2. Alpha coefficients ranged from .78 to .90

for the nine individual subtests. Person Separation Indexes for subtests ranged from .79 to

.94. Test-retest measures were used with the three learning subtests (intervals ranged

from 61-267 days) (see Table 2). The authors of the WRAML report that subtest scaled

49

Table I

Percentage of Individuals in Norm Sample by Racial Sub-Category

Racial Sub-Category Percentage

White-Anglo 78.3%

White-Hispanic 1.2%

Non-White Hispanic 5.4%

Black 12.0%

Asian 2.2%

Pacific Islander 0.1%

Native American 0.9%

score SEMs (Standard Error of Measurement) ranged from .9 to 1.3. The median SEMs

for Index standard scores are presented in Table 2.

Validity. The authors also report that three studies were conducted to investigate

criterion-referenced validity of the WRAML (WRAML Administration Manual; Sheslow

& Adams, 1990). Nine subtests of the WRAML along with four memory subtests of the

McCarthy Scales of Children's Ability were administered to a group of 6-7 year olds. The

WRAML and the Memory Scale of the Stanford Binet - 4"' Edition were administered in

counterbalanced order to a group of 10-11 year olds. In a similar study, the Wecshler

Memory Scale - Revised together with the WRAML was administered to a group of 16

50

Table 2

Correlation Coefficients and SEMs for the Verbal Learning Subtest, the Visual Learning Subtest and Index Scores

Subtest/ Index

Coefficient Alpha

Test-Retest Person-Separation

SEM

Verbal .78 .82 .82 1.3 Learning* (9 & older)

Visual .88 .81 .88 1.0 Learning* (9 & older)

LP* .91 .81 4.5

VMI** .93 .82 3.9

VIMI** .90 .61 4.7

GMI** .96 .84 3.0

(adapted from the WRAML manual; Sheslow & Adams, 1990)

^Scaled Scores (mean = 10, sd = 3) **Index Scores (mean = 100, sd = 15)

LI = Learning Index VMI = Verbal Memory Index

VIMI = Visual Memory Index GMI = General Memory Index

and 17 year olds. Corrected correlations of these studies are provided in the manual and

are represented in Table 3.

51

Table 3

Correlation of WRAML Index Scores with scores on the McCarthy Memory Index, the SB-IV Short Term memory, and WMS-R Index Scores

Indexes McCarthy SB-rV STM WMS-R General iMemory Index Memory Index

VMI .90 .67 .53

VIMI .48 .62 .44

LMI .10 .72 .41

GMI .72 .80 .54

(adapted from the WRAML manual; Sheslow & Adams, 1990)

VMI = Verbal Memory Index VTMI = Visual Memory Index

LMI = Learning Memory Index GMI = General Memory Index

To test for construct validity the authors tested four hypotheses:

1. That there would be a positive correlation between each subtest and age and that there

would be an increasing mean subtest score across age groups.

2. That intercorrelations of the WRAML subtest and Index scores would be positively

correlated with one another since they are all measures of memory.

3. That three factors would be extracted from the intercorrelations comprising a verbal, a

visual and a learning factor.

4. That correlations between WRAML Index scores and standardized measures of

intelligence would be low to moderate, the assumption being that memory is

positively associated with but not the same as general ability. The WRAML Manual

(Sheslow & Adams, 1990) provides correlational evidence to support these

hypotheses (pp. 93-98).

Factor analytic research on the WRAML has resulted in some controversy over its

factor structure and subtest specificity. In one factor analytic study of the WRAML,

Stone (1990) found that while a majority of subtests loaded on factors as predicted by the

authors there were several exceptions. For example, the Visual Learning subtest loaded

highest on the "Visual" factor (and not the "Learning" factor) while Story Memory

loaded higher on the Learning factor than on the Verbal factor. Results were similar for

both age groups. Stone concluded that the structural model was "generally" but not

completely confirmed. However subsequent factor analyses on the standardization data of

the WRAML seem to indicate a three factor solution for the WRAML consisting of a

"verbal memory" factor, a "visual memory" factor and an "attention" factor (Burton.

Mittenberg, & Biuton, 1993; Wasserman & Cambias, 1995). Phelps (1995) found a

similar pattern with a sample of 115 academically "at-risk" children (children referred for

academic concerns).

Consequently, the WRAML has been heavily criticized in that results from these

studies seem to indicate a factor structure that is different from the theoretical framework

proposed by the authors. However, the aim of this study is not to confirm or refute the

factor structure of the WRAML, or to use results for diagnostic purposes. Rather, the aim

is to compare the performance of a specific cultural group (viz.. Native Americans) on

two of it's subtests (viz.. Visual Learning and Verbal Learning) and to examine their

53

perfomiance within each of these subtests so as to gain a better understanding of the

processing style of this group. At the time of this study no Hterature was available on the

effect of cultural differences or other demographically related nominal variables on

performance on this test.

The WISC-III and DAS scores were used for descriptive purposes and for post

hoc analyses.

The Wechsler Intelligence Scale for Children-Third Edition fWISC-III)

The WISC-III will be used as a measure of general intelligence as well as a

measure of Verbal and Performance IQ. The test covers an age range from 6:0 through

16:11 years and provides Deviation IQs for the Verbal, Performance and Full Scales

(M=100, SD=15) and standard scores for the 13 subtests (M=10, SD=3). Six of the tests

form the Verbal Scale, and seven form the Performance Scale.

The WISC-III was standardized on 2,200 children, 100 boys and 100 girls in each

of 11 age groups from 6 through 16 years. The sample was stratified on age,

race/ethnicity, geographic region, and parent education so that they matched as closely as

possible the proportions found in the 1988 U.S. census data.

According to Sattler (1992) the WISC-III has "outstanding reliability." The three

scales (Verbal, Performance and Full) have internal consistency reliability coefficients of

.89 or above. Internal consistency reliabilities for the subtests are lower than those for the

three scales and range from .69 to .87. Average test-retest reliability coefficients (based

on the reassessment of 353 children from six age groups) are .94 for the Verbal scale, .87

54

for the Performance scale, and .94 for the Full Scale. With regard to construct validity,

Sattler proposes that the test adequately measures two factors that correspond to the

Verbal and Performance Scales of the test and provides a "fair measure of intelligence (p.

1043). Median correlations with measures of achievement and school grades range from

the upper .30s to the low .70s. Correlations with the WTSC-R, WPPSI-R, and WAJS-R

are in the .70s to .90s for the Verbal, Performance and Full Scale IQs.

The Differential Abilities Scales (DAS)

The Differential Abilities Scales (DAS; Elliot, 1983), is an individually

administered battery of cognitive and achievement tests for children and adolescents aged

2 years, 6 months (2:6) through 17 years, 11 months (17:11). According to the author, the

DAS was developed to serve two major purposes, namely, to provide a composite

measure of conceptual and reasoning ability which may be used for classification and

placement decisions, and to provide a reliable profile of within-person cognitive strengths

and weaknesses for diagnostic purposes.

The achievement tests were co-normed with the cognitive battery to make direct

ability-achievement discrepancy analysis possible. The three achievement tests - Basic

Number Skills, Spelling, and Word-Reading - provide a standardized screening of

literacy and numeracy skills. Basic Numeric Skills focuses on the concepts and skills that

underlie basic competence in arithmetic calculation. Spelling evaluates the child's ability

to produce correct spellings of a range of phonetically regular and irregular words. Word-

55

Reading is a test of recognition and oral reading of single words and aims at assessing

word-decoding ability.

The DAS was standardized on a stratified national sample on the basis of age, sex,

race/ethnicity, parent education, geographical region, and educational preschool

enrollment. The sample included 3, 475 children, 175 for each 6 month age group from

ages 2:6 through 4:11, and 200 cases per year from ages 5:0 through 17:11. Test-retest

reliability data was collected on about 100 examinees at each of three age ranges - 3:6-

4:5, 5:0-6:11, and 12:0-13:11. The test -retest interval was 2-7 weeks (M = 30 days). For

the Achievement Tests the mean reliability coefficients for the age range 5:9-6:11 were

.79, .89, and .97 for Basic Number Skills, Spelling, and Word-Reading respectively,

while for the age range 12:0-13:11 they were .85 for Basic Number Skills, and .94 for

Spelling and Word-Reading. Word-Reading test-retest reliability was .93 at the preschool

subtest level (age range, 5:0-6:3). The construct validity of the DAS is supported by

increasing raw scores with increase in the examinee's age. The manual indicates that

correlations between the DAS Achievement Tests and other tests of achievement

including the Basic Achievement Skills Individual Screener (BASIC) and the Kaufman

Test of Educational Achievement (K-TEA; Kaufrnan & BCaufrnan, 1985), were in the .60s

to .80s.

Procedures

Standardized administration and scoring procedures were followed. Each test was

individually administered in English by a licensed psychologist or a graduate student with

56

at least three years of formal training in psychological test administration. Children were

tested in rooms usually used by the school psychologist and each test was administered in

one sitting. The rooms were airy and relatively quiet allowing for privacy during

assessments. Evaluations were conducted during regular school hours.

Hypotheses Tested

The following hypotheses were tested at the .05 level of significance.

1. Is the performance of Native American children on the Verbal Learning subtest of the

WRAML significantly different from that of the norm group?

2. Are there differences across trials on the Verbal Learning subtest? In other words, do

practice effects impact scores across trials?

3. Do practice effects, if any, impact retention on the Verbal Leaming subtest after a

brief period of delay?

4. Is the performance of Native American children on the Visual Leaming subtest of the

WRAML significantly different from that of the norm group?

5. Are there differences across trials on the Visual Leaming subtest? In other words, do

practice effects impact scores across trials?

6. Do practice effects, if any, impact retention on the Visual Leaming subtest after a

brief period of delay?

7. Is there a relation between performance on the Verbal and Visual Leaming subtests

and overall performance on the WRAML?

57

8. Is there a relation between performance on the Verbal and Visual Learning subtests of

the WRAML and Verbal and Visual Intelligence as measured by the WISC-HI?

9. Is there a relation between performance on the Verbal and Visual Learning subtests of

the WRAML and academic achievement as measured by the DAS?

Statistical Analyses

Consistent with the hypotheses stated above two types of analytical procedures

were used. Supplemental age norms provided by the publishers of the WRAML were

used to calculate z scores for each child on each trial of the Verbal and Visual Learning

subtests. These were then used to run a One Way (repeated measures) ANOVA for each

of the subtests.

A second set of analyses consisted of correlational procedures to examine the

relation of two types of memory (verbal and visual) tasks to overall intellectual and

academic performance of the subjects. This was accomplished by using Product Moment

correlational techniques. Findings and results of data analyses are presented in the

following chapter.

58

CHAPTER FOUR

RESULTS

This chapter presents descriptive statistics as well as results of the repeated

measures ANOVAs. As described in chapter 3, two separate one-way repeated measures

ANOVAs using the z scores of the sample were run for the Verbal Learning and Visual

Learning subtests. This allowed the researcher to determine if; a) the sample is

significantly different from the norm group on the average (i.e., over the 4 points in time)

on either of the subtests, and b) if there is a significant effect for time/trial on either of the

subtests, which would indicate that means on some trials are different from others, and by

implication, the norm group. Results of post hoc analyses are reported where applicable.

Correlational analyses were computed to investigate the degree of relationship between

the Verbal and Visual Learning subtests and the memory indexes on the WRAML, as

well as measures of intelligence and achievement. Data was analyzed using SPSS for

Unix (Release 6.1) and SPSS 7.5 for Windows 95. All hypotheses were tested at the .05

level of significance unless otherwise stated.

Descriptive Statistics

Table 4 presents the means and standard deviations of IQ measures, memory

indices, visual and verbal learning subtests and achievement tests. The mean Verbal IQ

obtained by the sample group in this study was significantly different from the national

normative mean (M = 88.47, SD = 9.72) (t = -4.597 [14], 2 = -000) and so was the mean

Verbal Memory Index (M = 88.27, SD = 7.06) (t = -6.441 [14], g = .000). The mean

59

Standard scores of the sample on the three achievement tests of the DAS were all

significantly below the national normative mean. The mean score on Arithmetic was 81 (t

= -6.567 [14], 2 = .000), Spelling was 83 (t = -5.278 [13], g = .000), and Word Reading

was 80.87 (t = -5.757 [14], g = .000).

Table 4

Descriptive Statistics

Measure Mean Std.Dev. Minimum Maximum

viQ (wisc-rn)* 88.4667 9.7165 70.00 108.00

piQ (WTSc-rn)* 103.4000 10.6154 84.00 117.00

FIQ (WlSC-ni)* 94.8667 9.5234 81.00 107.00

Verbal Memory* 88.2667 7.0556 77.00 100.00

Visual Memory* 101.0667 11.4858 81.00 121.00

Learning* 100.0667 13.7189 78.00 122.00

General Memory* 95.2000 9.7629 79.00 113.00

Verbal Learning** 10.6667 2.8702 7.00 17.00

Visual Learning** 10.7333 2.6040 7.00 15.00

Arithmetic (DAS)* 81.0000 11.2059 68.00 102.00

Spelling (DAS)* 83.0000 12.0512 67.00 113.00

Word Reading (DAS)* 80.8667 12.8723 62.00 112.00

* Index or Standard scores (mean = 100, SD = 15) **Scaled scores (mean = 10, SD = 3)

60

Results Associated with Hypotheses 1, 2 and 3

One of the primary objectives of the study was to compare the performance of

Native American children on the Verbal Learning subtest of the WRAML to that of the

norm group. The mean z scores of the sample on each trial are graphically presented in

Figure I. They are also delineated in Table 5 together with standard deviations and 95%

confidence intervals. Tables 6 and 7 present the results of the ANOVA for z scores on the

Verbal Learning subtest

0.3

0.2

Trial 2

•0.33^ ^0.284

S 0 . 1

N 0

(U »

^ -0.2

« -0.Trial I Trial 3 Trial 4 Trial 5

-0.3

T rials

Figure 1. Verbal learning subtest learning curve.

61

Table 5

Verbal Learning Subtest: Cell Means and Standard Deviations

Variable Mean Std. Dev. 95% Confidence Interval

Trial 1 -.294 1.007 00 r .264

Trial 2 .234 1.283 -.477 .945

Trial 3 .254 .706 -.137 .645

Trial 4 .284 .745 -.129 .696

Trial 5 .202 .671 -.170 .574

Table 6

Verbal Learning Subtest:Test of Between-Subiects Effects

Source of Variation SS DF MS F Sig of F

Constant

Within Cells

1.39 1

42.15 14

1.39

3.01

.46 .508

Table 7

Verbal Learning Subtest: Test of'Time' " Within-Subiect Effects

Source of Variation SS DF MS F Sig of F

Time

Within Cells

3.52 4

16.16 56

.88

.29

3.05 .024

62

Research question 1 intended to determine if the Native American sample was

significantly different from the norm group in terms of overall performance on the Verbal

Learning subtest. The null hypothesis would therefore read as follows; The overall

performance of the sample on the Verbal Learning subtest is not significantly different

from that of the norm group. Table 6 displays the results of the test for overall group

effect across the five trials. Based on the literature reviewed in chapter two and prior

findings of poor performance of Native Americans on "verbal" tasks, it was expected that

the null hypothesis would be rejected. However, it is evident from Table 6 that the grand

mean was not significantly different from zero and by implication from the norm group.

Research question 2 aimed at studying differences in practice effects across trials

on the Verbal Learning subtest. The null hypothesis for this question would be as follows:

Practice effects do not have differential effects on the performance of the sample as

compared to the norm group on the Verbal Learning subtest. However, as Table 7

indicates, the results of the "within-subjects" test of time (i.e., trial) showed a significant

difference (2 < .05) in z scores across trials for the sample group. The null hypothesis for

research question 2 was therefore rejected.

The purpose of research question 3 was to investigate the impact of practice

effects, if any, on retention on the Verbal Learning subtest. Given the finding that the

sample group showed differential performance across trials on the Verbal Learning

63

Table 8

Verbal Learning Subtest: Dunnett's Test

Mean z score Contrast Value

-.294

.234 2-1 .528

.254 3-1 .548

.284 4-1 .578

.202 5-1 .496

Critical value of Dunnett's statistic tDN, = 2.51

Critical value of contrast = .49

subtest (Table 7), it was thought that a post hoc test such as the Dunnett's would be the

most appropriate measure to employ. It would allow for contrasting trial 1 (treated as the

baseline) with each subsequent trial, including the delay trial and would provide a way of

answering question 3 as well as obtaining more detailed information. Results of the

Dunnett's test are displayed in Table 8. A two-tailed test showed results to be significant

at the .05 level. The critical difference on the Dunnett's was calculated at .49. Since the

differences between each of the 4 subsequent trials and the baseline (trial 1) were greater

than the critical value, it can be inferred that performance on trials 2, 3, 4, and 5 were

significantly different fi-om that on trial 1.

64

Results Associated with Hypotheses 4, 5 and 6

Research question 4 aimed at comparing the performance of the sample group to

that of the norm group on the Visual Learning subtest. The mean z scores of the sample

are presented graphically in Figure 2. These are also delineated in Table 9 together with

standard deviations and 95% confidence intervals. Tables 10 and 11 present the results of

the ANOVA for z scores on the Visual Learning subtest.

d) o o C/5 N

a <L)

0.429

Trial 1

0.236

Trial 2 Trial 3 Trial4 Trial 5

T rials

Fieiire 2. Visual learning subtest learning curve

65

Table 9

Visual Learning Subtest: Cell Means and Standard Deviations

Variable Mean Std. Dev. 95% Confidence Interval

Trial 1 .112 1.037 -.462 .686

Trial 2 .228 .842 -.238 .694

Trials .168 1.146 -.466 .803

Trial 4 .429 .696 .043 .814

Trial 5 .236 .971 -.302 .774

Table 10

Visual Learning Subtest: Test of Between-Subiects Effects

Source of Variation SS DF MS F Sig of F

Constant 4.13 1 4.13 1.25 .281

Within Cells 46.05 14 3.29

Table 11

Visual Learning Subtest: Test of "Time" Within-Subiect Effects

Source of Variation SS DP MS F SigofF

Time

Within Cells

.86 4 .21 .69 .599

17.28 56 .31

66

The aim of research question 4 was to determine if the Native American sample

was significantly different from the norm group in terms of overall performance on the

Visual Learning subtest. The null hypothesis would therefore read as follows: The overall

performance of the sample on the Visual Learning subtest was not significantly different

from that of the norm group. Table 10 displays the results of the test for overall group

effect across the four trials. It is evident from Table 10 that the grand mean was not

significantly different from zero and by implication from the norm group.

Research question 5 aimed at studying differences in practice effects across trials

on the Visual Learning subtest. The null hypothesis for this question would be as follows:

Practice effects do not have differential effects on the performance of the sample as

compared to the norm group on the Visual Learning subtest. As outlined in Table 11, the

results of the "within-subjects" test of time (i.e., trial) shows no significant difference (at

the .05 level) in z scores across trials for the sample group as compared to the norm

group, hi other words, the rate of learning across trials was not significantly different for

the sample group as compared to the norm group.

The purpose of research question 6 was to investigate the impact of practice

effects, if any, on retention on the Visual Learning subtest. Since the results of the

ANOVA did not indicate any significant trial effects for the Visual Learning subtest, it

can be concluded that there was no significant difference in the means of the five trials.

Therefore, no post-hoc analyses were conducted. However, z scores displayed in Table 9

show that the mean z score on trial 5 (delay trial) was in the positive range.

67

Results Associated with Hypothesis 7

Research question 7 aimed at looking at the relation, if any, between performance

on the Verbal and Visual Learning subtests and overall performance on the WRAiML.

Table 12 displays Pearson Product Moment correlations for these variables. Correlation

coefficients indicate that the scaled scores on the Verbal and Visual Learning subtests

were significantly related to each other at the .05 level. Scaled scores on the Verbal

Learning subtest were highly correlated with the Visual Memory Index, the Learning

Index and the General Memory Index. Scaled scores on the Visual Learning subtest were

highly correlated with the Visual Memory, Learning, and General Memory Indexes. It

should be noted that the scaled scores on the Learning subtests are based on the additive

raw score across 4 trials. Scores on the subtests comprising the Verbal Memory Index are

based on single trial performance. To explore the possibility that the lack of correlation

between the Verbal Learning subtest and the Verbal Memory Index scores might be a

result of practice over trials (which might wipe out differences between subjects), raw

scores on trials 1 through 4 of the Verbal and Visual Learning subtests were correlated

with the Memory Indexes of the WRAML. As Table 13 indicates, the correlation between

the raw scores on the Verbal Learning subtest and the Memory Indexes appears to decline

over trials. This is not the case with the Visual Learning subtest.

68

Table 12

Correlations between Scaled Scores of the Verbal Learning and Visual Learning subtests and the Index Scores of the WRAML

VEL VIL VMI VIMI LI GMI

VEL 1.000 .589» .012 .607* .906** .841**

VIL 1.000 -.217 .698»* .770** .738**

VMI 1.000 -.204 -.151 .116

VIMI 1.000 .703** .855**

LI 1.000 .893**

GMI 1.000

* Correlation is significant at the .05 level (2-taiIed) ** Correlation is significant at the .01 level (2-tailed)

VEL

VIL^

VMI

, = Verbal Learning Subtest

= Visual Learning Subtest

: = Verbal Memory Index

VTMI = Visual Memory Index

LI = Learning Index

GMI = General Memory Index

69

Table 13

Correlations between Raw Scores on the Verbal and Visual Learning subtests and the Index Scores of the WRAML

VMI VIMI LI GMI

Verbal 1 .176 .484 .504 .604*

Verbal 2 .019 .663** .905** .885**

Verbal 3 .055 .582* .815** .775**

Verbal 4 .000 .638* .864** .817**

Visual I -.281 .631* .784** .706**

Visual 2 -.182 .631* .496 .564*

Visual 3 -.161 .580*

*

*

00

.638*

Visual 4 -.370 .668** .655** .576*

* Correlation is significant at the .05 level (2-tailed) ** Correlation is significant at the .01 level (2-tailed)

VMI = Verbal Memory Index

LI = Learning Index

VIMI = Visual Memory Index

GMI = General Memory Index

"0

Results Associated with Hxpothesis 8

Research question 8 proposed to look at the relation, if any. between performance

on the Verbal and Visual Learning subtests of the WRAML and Verbal and Performance

IQs as measured by the WTSC-III. Table 14 displays Pearson Product Moment

correlations for these variables. Results indicate that while the Verbal Learning subtest

was significantly correlated (at the .01 level) with the Verbal IQ and Full Scale IQ of the

WlSC-in, the Visual Learning subtest showed no such association. Of interest is the

significant correlation between the Learning Index on the WRAML and the Verbal and

Full Scale IQs on the WISC-III as well as the high correlations between the General

.Memory Index on the WRAML and IQs on all three scales of the WTSC-III.

Results Associated with Hypothesis 9

Research question 9 aimed at exploring the relation, if any, between performance

on the Verbal and Visual Learning subtests of the WRAML and academic achievement as

measured by the DAS. Table 15 displays Pearson Product Moment correlations for these

variables. Neither the Verbal Learning subtest, nor the Visual Learning subtest were

significantly correlated to any of the achievement measures on the DAS. Correlation

coefficients displayed in Table 15 also show no significant relations between standard

scores on the DAS and Index scores on the WRAML or IQs on the WTSC-HI.

Implications of results and possible explanations for findings will be explored in

the following chapter.

71

Table 14

Correlations between Verbal. Performance and Full Scale IPs on the WISC-HI. Scaled Scores on the Verbal and Visual Learning subtests of the WRAML. and Index Scores on the WRAML.

Verbal IQ Performance IQ Full Scale IQ

VEL .657** .476 .644**

VIL .372 .376 .433

VMI .226 .129 .190

VIMI .330 .466 .445

LI .590* .451 .589*

GMI .616* .528* .641*

* Correlation is significant at the .05 level (2-tailed) ** Correlation is significant at the .01 level (2-tailed)

VEL = Verbal Learning Subtest

VMI = Verbal Memory Index

LI = Learning Index

VIL = Visual Learning Subtest

VIMI = Visual Memory Index

GMI = General Memory Index

72

Table 15

Correlations between Standard Scores on the DAS. Scaled Scores on the Verbal and Visual Learning subtests on the WRAML. Index Scores on the WRAML. and WISC-ni

IPs.

DAS (Arithmetic) DAS DAS (Spelling) (Word Reading)

Verbal Learning* .342 .302 .418

Visual Learning* .081 -.262 .084

VMI** .164 -.300 -.324

VIM!** .263 .004 .162

LI** .293 .218 .407

GMI** .383 .072 .259

VIQ*** .461 .006 .197

PIQ*** .098 -.054 -.076

FIQ*** .295 -.032 .061

*Subtests on the WRAML **Index Scores on the WRAML *** IQs on the WISC-III

CHAPTER FIVE

DISCUSSION

The goal of this chapter is analyze results and findings from this study in light of

previous studies that addressed the issue of verbal and visual skills of Native Americans.

Limitations of this study are described and suggestions for future research are provided.

Descriptive Data

Intelligence scores acquired by the sample in this study (Table 4) were consistent

with those of other Native American samples in previous studies that used the Wechsler

scales as measures of general ability.

Table 16

IPs obtained bv various Native American groups in previous studies

N Test Verbal Perf.

Halverson-Tanner et al 110 wisc-in 84.5 91.9 (1993)

McCullough et al 42 WISC-R 79.92 99.19 (1985)

McCullough et al 33 WAIS 90.64 106.21 (1985) Browne 197 WISC-R 7.8* 10.5* (1984)

*Average Subtest Score

Not only was the mean Verbal Scale score obtained by the sample group in this

study significantly different from the national normative mean, but the 14.93 VIQ < PIQ

point discrepancy corroborated results of previous studies (see Table 16). The Verbal and

Visual \[emor\' Indexes on the WRAML appear to reflect this visual > verbal bias, with a

difference of 12.80 points between the two scores. According to the supplemental age

norms. 28"»of the norm group evidenced a difference of-10 points between Verbal-

Visual Index scores while only 19% showed a difference of-15 points. Do these tindings

substantiate the interpretations drawn by previous researchers, viz., that Native

Americans process information in a right-brained, holistic manner (Browne, 1984;

McShane and Plas. 1982) and that their spatial abilities are more well-developed than

sequential skills (Diessnerand Walker, 1986)?

Verbal Learning Subtest Data Analyses

A look at the analysis of variance as well as the mean scaled score for the sample

group indicates that the subjects' overall performance on the Verbal Learning subtest was

not significantly different from that of the norm group. Given the results of previous

studies examining the performance of Native Americans on verbal tasks, this finding

appears incongruous at first. However, scaled scores on this subtest are based on additive

raw scores across the four learning trials. An examination of the mean z scores of the

group on the four learning trials as well as the results of the Dunnett's test show that the

sample group does in fact start out slightly below "0" on trial I. If the practice effect for

the sample group was the same as for the norm group, the z scores would be expected to

stay the same through the four trials. However, the z scores not only showed steady

increase fix)m trial 1 through 4, but those on trials 2 through 4 were significantly different

firom trial 1. One explanation could be that the Native American children learned at a

different rate as compared to the norm group. The Dunnett's test also indicates that the

greatest increase in z scores appears to have taken place between trials I and 2. These

results are consistent with those of MacAvoy and Sidles (1991). They assessed the

performance of a Native American Navajo sample on multi-trial tests involving the

learning of Navajo versus English word lists. While the sample that was administered the

Navajo list started out with higher scores on trials 1 and 2, differences in number of

words correctly recalled were wiped out by trial 3.

Additionally, the results of the present study indicate that the Native American

children retained the verbal information they learned at a normative rate after a brief

period of delay. The mean z score on trial 5 (delay trial) while lower than those on trials 2

through 4, is however, higher than that on trial 1 and in the positive range.

If replicated, these findings could have important implications not only in terms of

assessment and diagnosis of children eligible for special education services, but also with

regard to how educators plan and implement curriculum for Native American children.

As MacAvoy and Sidles observe, auditory processing tests are often a part of the learning

disability diagnosis process. Single presentations of verbal material to Native Americans,

could result in misinterpretations of results and consequently to misdiagnosis of learning

disabilities.

On a broader scale many education professionals have called for the adaptation of

school curriculum so as to accommodate for the Native Americans "styles" of

information processing (Gardner, 1980; Kaulback, 1984). On the other hand authors such

^6

as Chrisjohn and Peters (1986) have challenged the validity of studies showing different

processing styles for Native Americans. Moreover, they have also expressed concern that

by concentrating on the Native American's visual "strength" and circumventing their

verbal "weakness," if any, we may be setting up the Native American for certain failure

in the world of mainstream America. The results of the present study question the notion

that Native American learners have weaknesses in verbal learning, and together with the

findings of MacAvoy and Sidles (1991), suggest that a multi-trial approach in presenting

verbal information may enhance learning and retention of content presented to Native

Americans in English.

Visual Learning Subtest Data Analyses

Based on the review of literature it was expected that the Native American sample

in this study would perform at or above the level of the norm group. Results of the

repeated measures ANOVA showed no significant difference in the overall performance

of the sample group as compared to the norm group. Results also indicated no significant

difference in z scores across trials. A perusal of the mean z scores of the sample across

the 4 learning trials of the Visual Learning subtest reveals interesting information. Unlike

the Verbal Learning subtest, the z scores on the Visual Learning subtest do not reflect a

gradual ascension. These results argue against a "visual learning strength" although the

ecological validity of these assessment methods could be challenged.

77

Correlational Data Analyses

The Verbal Learning subtest correlated significantly with the Visual Memory

Index (VTMT), the Learning Index (LI), and the General Memory Index (GMI) but not

with the Verbal Memory Index (VMI) (Table 12). As noted in the results section, the

scaled scores on the Learning subtests are based on the additive raw scores across 4 trials

while scores on subtests comprising the Verbal memory Index are based on single trial

performance. Given the results of the ANOVA (Table 7), it may be concluded that the

scaled scores on the Verbal Learning subtest were affected by learning opportunities and

that differences between subjects may be wiped out by trial 4. Consequently, as learning

increased with multiple trials, correlation with the VMI (comprised of scores on single-

trial tasks) decreased. The Visual Learning subtest was significantly correlated with the

VMI, the LI and the GMI.

The Verbal Learning subtest was also significantly correlated with the Verbal and

Full Scale IQs on the WISC-IH (Table 14). The Visual Learning Subtest on the other

hand showed no significant correlation to IQs on the WISC-IH. Interestingly, while the LI

was significantly related to Verbal and Full Scale IQs and the GMI was significantly

related to all three Scale scores on the WISC-HI, neither the VMI nor the VIMI were

significantly related to IQ scores on the WISC-HI. However, the VMI showed a higher

correlation with the Verbal IQ than the Performance IQ while the VIMI appears to be

more highly correlated with the Performance IQ than the Verbal IQ. While these trends

were not significant, they reflect those reported by the WRAML authors who reported

78

this pattern for 40 children administered the WRAML and the WISC-R (Adams &

Sheslow, 1990).

The three measures of achievement on the DAS (Arithmetic, Spelling, and Word-

Reading) did not show a significant correlation with any of the other measures relevant to

the study. This together with the below average performance of the sample group on all

three subtests of the DAS brings into question the validity of this measiu-e when used

with Native American children.

The following section provides an overview of the limitations pertaining to the

current study, with a view to putting the results in a meaningful perspective for future

research.

Limitations and Implications for Futiu^e Research

A major limitation of this study is the small sample size. A replication of this

study should involve a larger sample size, and preferably an instrument that provides

uniform tasks and norms across the school-related age range. While there are such

instruments available (CAVLT), the focus of this study was to investigate performance

on both verbal and visual tasks. The instnmient used in this study incorporates both kinds

of tasks but provides separate norms for children below 9 years of age.

A second issue relates to the generalization of results. "Native Americans" are not

a homogenous groups in that differences in tribal cultures, lifestyles (hunting/gathering

vs. agricultural), residence (rural vs. urban), socio-economic status, and levels of

acculturation, are well dociunented (McShane & Berry, 1988). Therefore, results acquired

79

with this sample may not be readily generalized to other Native American groups. A

larger study involving representatives of various Native American cultures may provide

more valid information in this regard.

The focus so far in discussing the learning abilities of Native Americans has been

exclusively on "cultural styles" and issues of "cultural discontinuity" in the classroom

(Ledlow, 1992). However, if Native Americans are to succeed in mainstream culture,

then basic issues such as socio-economic level and exposure to the English language must

not to be overlooked in undue emphasis on "cultural" issues. Hence, we need to look at a

multi-trial approach rather than "modality issues" in terms of assessing learning

disabilities and adapting school curricula for the Native American.

80

APPENDIX: HUMAN SUBJECTS COMMITTEE LETTER

THE UNivtRsnvof

Human Suhtevit Ct'nmmicr ARIZONA. If>:: E Mibtl SI I'D Bo« 2-1? I J7 HEALTM SCltNCtS CENTIR Ttmon. /^rtzuna J7 ^20) tiia 072I

1.3 May 1997

Kr i sc ine L . Kaemingk , Ph .D. Depar tment o f Psychology Psychology Bui ld ing , Room 312 PO BOX 210063

RE: HSC A94.92 PRENATAL ALCOHOL EXPOSURE AND NEUROPSYCHOLOGICAL FUNCTION

Dear Dr . Kaemingk:

We r ece ived your 12 May 1997 l e t t e r reques t ing tha t Winoo Shah , Ph .D. Candida te , be a l lowed access to ex i s t ing da ta f rom the above re fe renced pro- ]ecc fo r purposes of d i s se r ta t ion . Approva l fo r th i s reques t i s gran ted e f fec t ive 13 May 1997 .

The Human Subjec t s Commit tee ( Ins t i tu t iona l Review Board) o f the Univers i ty o f Ar izona has a cur ren t assurance of compl iance , number M-1233 , which i s on f i l e wi th che Depar tment of Hea l th and Human Serv ices and covers th i s ac t iv i ty .

Approva l i s gran ted wi th the unders tanding tha t no fu r ther changes o r add i t ions wi l l be made e i ther co the procedures fo l lowed or to che consen t fo rmfs) used (copies of which we have on f i l e ) wi thout the )^nowledge and approva l o f the Human Subjec t s Commic tee and your Col lege o r Depar tmenta l Review commiccee . Any research re la ted phys ica l o r psycholog ica l harm to any sub jec t mus t a l so be repor ted CO each commiccee .

A un ivers icy po l icy requi res chac a l l s igned sub^ecc consen t fo rms be kepc in a permanent f i l e in an a rea des igna ted fo r chac purpose by che Deparcmenc Head o r comparab le au thor icy . This wi l l assure che i r access ib i l i ty in the event chac un ivers icy o f f ic ia l s requi re che in formacion and che p r inc ipa l inves t iga tor i s unava i lab le fo r some reason .

S incere ly yours .

Wi l l i am F Denny , M.D. Cha i rman Human Subjec t s Ccmmiccee

WFD:i s

cc : Depar tmenta l /Col lege Review Commit tee

81

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disabilities identification process for too long. LP forum. 21 (1), 27-30.

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