THE EFFECTS OF COGNITIVE FACTORS AND PERSONALITY …
Transcript of THE EFFECTS OF COGNITIVE FACTORS AND PERSONALITY …
THE EFFECTS OF COGNITIVE FACTORS AND PERSONALITY
ATTRIBUTES ON LEARNING POTENTIAL
by
CHRISTINE HELEN BENDIXEN
DISSERTATION
submitted in fulfilment
of the requirements for the degree
MASTER OF ARTS
in
PSYCHOLOGY
in the
FACULTY OF ARTS
at the
RAND AFRIKAANS UNIVERSITY
SUPERVISOR: DR. M. JOOSTE
JANUARY 2000.
I
DECLARATION
hereby declare that the dissertation submitted for the
Master of Arts degree to the Rand Afrikaans Universi ty,
apart from the help recognised, is my own work and has
not been formerly submitted to another universi ty for a
degree.
ABSTRACT
In this study, a test-train-retest cogni tive assessment
model was used. The training model for mediation was
group-administered, standardised to correspond to a
Theorist learning style and presented on video. The aim
was to establish whether this form of testing is viable.
In addi tio::, the influence of the following variables on
learning potential scores was examined:
• General cognitive ability (measured by Cattell's
Culture Fair Intelligence Test, Scale 2, Form A) .
• Fourteen personality factors (measured by the High
School Personality Questionnaire) .
• Ten motivational traits (measured by the Picture
Motivation Tests) .
• Four learning styles (measured by the Learning Styles
Questionnaire) .
The ability to transfer what had been learned during
mediation was also examined. Transfer was defined as the
difference between the CCFIT, Scale 2, Form A and Form B,
(administered as pre- and post-tests). Learning potential
scores were defined as the difference between the pre
and post-test scores of Raven's Standard Progressive
Matrices, using a Solomon 4-Group Design to control for
possible practice effects. The mediation was standardised
according to the LSQ's Theorist learning style using
Feuerstein's Set Variations 1 as a teaching tool. The
subjects were 120, black (mostly African), Grade 10
learners.
The results may be summarised as follows:
• The intervention significantly increased scores from
the pre- to the post-test of the RSPM. There was no
statistically significant evidence of a practice effect
on post-test scores.
• Conscientiousness (G+), realism - tough-mindedness (1-)
and proneness to guilt (0+) accounted for 22 % of the
variance in learning potential scores.
• Aggression (self-assertiveness) accounted for 6,6% of
the variance in learning potential scores.
• Cognitive ability scores were independent of learning
potential scores.
• Gain scores on the transfer test were a result of both
the intervention and practice. These scores did not
correlate with learning potential scores.
The fact that the CCF1T pre-test scores did not predict
future learning supports the contention that traditional
intelligence tests are inadequate measures of the
intellectual capacity of educationally disadvantaged
subjects.
The role of conscientiousness in learning is well
documented. The other non-intellective factors require
further research.
The finding that a short, group-administered mediation
can produce signi ficant changes in post-test cogni tive
scores suggests that this technique can be used to
broaden the application of dynamic assessment.
SAMEVATTING
In samelewings met diverse kulturele bevolkings en ongelyke
opvoedkundige geleenthede, kan normatiewe assesserings en
vorige akademiese prestasie nie op 'n betroubare wyse
gebruik word om 'n individu se potensiele kognitiewe vermoe
te asses seer nie. Dinamiese assessering word as 'n
alternatief tot die bogenoemde evalueringspraktyk
voorgehou.
In hierdie studie is 'n toets-oplei-hertoets model vir
kognitiewe evaluering gebruik. Die opleidingsmodule vir
kognitiewe bemiddeling is in groepsverband toegepas deur
middel van 'n video aanbieding, gestandaardiseer volgens
die eienskappe van die Teoretiese leerstyl. Die doel
hiervan was om vas te stel of hierdie evalueringsmodel
doeltreffend is. Verder is die volgende veranderlikes
nagevors om die invloed daarvan op die verkree tellings van
leerpotensiaal te ondersoek:
• Algemene kognitiewe vermoe (gemeet deur Cattell's Culture
Fair Intelligence Test (CCFIT), Skaal 2, Vorm A).
• Veertien persoonlikheidsfaktore (gemeet deur die
Hoerskool Persoonlikheidsvraelys (HSPV)).
• Tien motiveringstrekke (gemeet deur die
Prentmotiveringstoets (PMT)).
• Vier leerstyle (gemeet deur die Learning Styles
Questionnaire (LSQ)).
Die oordrag van di t wat geleer was gedurende bemiddeling,
is ook ondersoek. Oordrag is bepaal deur die
verskiltellings tussen die CCFIT, Skaal 2, Vorm A en Vorm B
(afgeneem as voor- en na-toetse) te verkry.
Leerpotensiaaltellings is verkry deur die verskil tussen
die voor- en na-toetstellings van die Raven's Standard
Progressive Matrices te bepaal, terwyl die Solomon 4
Groepontwerp gebruik is om 'n moontlike oefen-effek te
kontroleer. Die aanbiedingstyl van die bemiddeling het
voldoen aan die kenmerke van die Teoretiese leerstyl. Daar
is van Feuerstein se Set Variations 1 as In kognitiewe
bemiddelingsinstrument gebruik gemaak. Die streekproef het
bestaan ui t 120 Graad 10 Kleurling en swart leerlinge as
proefpersone.
Die resultate kan as volg saamgevat word:
• Die een uur gestandaardiseerde kognitiewe
opleidingsintervensie, wat gebruik maak van Feuerstein se
Set Variations 1, vermeerder tellings op die RSPM op 'n
statisties betekenisvolle peil vanaf die voor-toets tot
die na-toets. Daar was geen statisties betekenisvolle
aanduidings van 'n oeffen-effek vanaf die voor-toets tot
na-toets nie.
• Die persoonlikheidstrek, Pligsgetrouheid (G+), het
positief gekorreleer met leerpotensiaaltellings. 'n
Regressie-analise het drie persoonlikheidstrekke
opgelewer, naamlik Pligsgetrouheid (G+), Realisme
Ontoegeeflikheid (1-) en Geneigdheid tot skuldgevoelens
(0+). Hierdie trekke verklaar 22% van die variansie van
die leerpotensiaaltellings.
• Die motiveringstrek, Aggressie (selfhandhawing),
korreleer positief met leerpotensiaaltellings. In 'n
regressie-analise het hierdie trek 6,6% van die variansie
verklaar.
• Daar is 'n mate van onafhanklikheid tussen die tellings
van algemene kognitiewe vermoe en leerpotensiaal.
• Die intervensie het gelei tot 'n toename in die tellings
vanaf die CCFIT Vorm A tot die CCFIT Vorm B. Hierdie
tellings is egter deur oefen-effekte tot 'n mate
gekontamineer.
• Die verskil tellings tussen die CCFIT voor-toets en die
na-toets as oordragtoets, het nie gekorreleer met
leerpotensiaaltellings nie.
Die feit dat die voor-toetstellings, naamlik die CCFIT
tellings, nie toekomstige leer voorspel het nie, dien as
ondersteuning vir die argument dat tradisionele
intelligensietoetse onvoldoende meetinstrumente is van
intellektuele potensiaal in opvoedingsgeremde persone. Die
mate van oordrag weens bemiddeling kon nie in hierdie
studie vasgestel word nie. Die items van die CCFIT kon
moontlik te moeilik gewees het vir die milieugeremde
proefpersone.
Daar is al baie geskryf oor die rol van pligsgetrouheid in
leer. Daar sal egter meer navorsing gedoen moet word om
helderheid oor die invloed van ander nie-intellektuele
faktore op leerpotentsiaaltellings te kry.
Die bevinding dat 'n korttermyn bemiddeling in
groepsverband, beduidende verskille In na-toetstellings
oplewer, dui aan dat hierdie tegniek moontlik aangewend kan
word vir algemene gebruik in dinamiese assessering.
DEDICATION
To my family, Michael, Karen, Melanie, Peter and Martin,
thank you for your encouragement. A special thanks to
Michael for all the help especially with the statistics;
to Karen for proofreading the document; to Melanie for
all the time spent on the video; and to Peter for his
patience.
ACKNOWLEDGEMENTS
I am grateful to:
The staff and pupils of a Johannesburg
Secondary School who willingly submitted to all
the testing for this project.
To Dr. Jooste, my supervisor, for his
objectivity and interest.
THE EFFECTS OF COGNITIVE FACTORS AND PERSONALITY
ATTRIBUTES ON LEARNING POTENTIAL
CONTENTS
CHAPTER 1
INTRODUCTION
1.1 RESEARCH BACKGROUND 1
1.2 NORMATIVE ASSESSMENT 2
1.3 DYNAMIC ASSESSMENT 3
1.4 APPROACHES TO DYNAMIC ASSESSMENT 5
1.5 FEATURES OF THIS RESEARCH 7
1. 5.1 GROUP ADMINISTRATION 7
1. 5.2 ST~TDARDISED PROTOCOL 8
1. 5.3 SHORT LEARNING INTERVENTION 8
1. 5.4 SCORING 9
1. 5.5 GENERAL SKILLS 10
1. 5.6 PRACTICE EFFECTS 11
1. 5.7 TRANSFER EFFECTS 11
1.6 DEFINITION OF MAIN TERMS 12
1. 6.1 LEARNING POTENTIAL 12
1. 6.2 COGNITIVE FACTORS 12
1 . 6.3 NON-INTELLECTIVE FACTORS 14
1.6.3.1 Personality 14
1.6.3.2 l'1otivation 15
1.6.3.3 Learning Styles 16
1.7 STATEMENT OF THE PROBLEM 17
1.8 AIMS OF THIS RESEARCH 18
1.9 DELIMITATIONS OF THIS RESEARCH
19
·18
1.10 LAYOUT OF THE CHAPTERS
CHAPTER 2
LITERATURE REVIEW
2.1 INTRODUCTION 20
2.2 HISTORICAL REVIEW 22
2.3 VYGOTSKY'S THEORY OF THE ZONE OF PROXIMAL
DEVELOPMENT 25
2.4 CURRENT MODELS OF DYNAMIC ASSESSMENT 27
2.4.1 THE TEST-TRAIN-RETEST GAIN SCORE MODEL 27
2.4.2 THE CYLINDRICAL MODEL OF LEARNING
POTENTIAL 28
2.4.3 TESTING THE LIMITS ASSESSMENT 33
2.4.4 GRADUATED PROMPTING ASSESSMENT 35
2.4.5 A ~CONTINUUM OF ASSESSMENT SERVICES" MODEL 37
2.4.6 TRAIN-WITHIN-TEST 38
2.5 EMPIRICAL FINDINGS 40
2.5.1 LEARNING AND COGNITIVE FACTORS 40
2.5.2 LEARNING AND PERSONALITY 42
2.5.3 LEARNING AND MOTIVATION 46
2.5.4 LEARNING AND LEARNING STYLES 48
2.6 LIMITATiONS OF THE EXISTING LITERATURE ON
DYNAMIC ASSESSMENT 50
2.7 THE PRESENT RESEARCH PROJECT IN VIEW OF THESE
PURPORTED LIl'1ITATIONS 52
CHAPTER 3
RESEARCH METHODOLOGY
3.1 INTRODUCTION 54
3.2 STATEMENT OF THE PROBLEM 54
3.3 AIM OF THIS STUDY 55
3.4 HYPOTHESES 56
3.5 SUBJECTS 62
3.6 EXPERIMENTAL DESIGN 64
3.7 PROCEDURES 65
3.7.1 THE INITIAL TESTING PHASE 65
3.7.2 THE EXPERIMENTAL PRE-TEST PHASE 66
3.7.3 THE EXPERIMENTAL POST-TEST PHASE 66
3.8 INSTRUMENTS 67
3.8.1 RAVEN'S STANDARD PROGRESSIVE MATRICES 67
3.8.2 FEUERSTEIN'S SET VARIATIONS 1 72
3.8.3 HIGH SCHOOL PERSONALITY QUESTIONNAIRE 74
3.8.4 THE PICTURE MOTIVATION TESTS 87
3.8.5 THE LEARNING STYLES QUESTIONNAIRE 91
3.8.6 CATTELL'S CULTURE FAIR INTELLIGENCE TEST 96
3.9 STATISTICAL ANALYSIS OF THE DATA 98
CHAPTER 4
RESEARCH RESULTS
4.1 INTRODUCTION 101
4.2 HYPOTHESIS 1 101
4.3 HYPOTHESIS 2 104
4.4 HYPOTHESIS 3 106
4.5 HYPOTHESIS 4 111
4.6 HYPOTHESIS 5 115
4.7 HYPOTHESIS 6 117
4.8 HYPOTHE~':;IS 7 118
4.9 HYPOTHESIS 8 124
CHAPTER 5
DISCUSSION AND CONCLUSION
5.1 INTRODUCTION 126
5.2 Sl:JMMARY OF RESULTS 126
5.3 DISCUSSION 127
5.3.1 GRO;JP ADMINISTRATION OF A SHORT LEARNING
TEST USED IN A STANDARDISED COGNITIVE
TEACHING INTERVENTION 127
5.3.2 PRACTICE EFFECTS 128
5.3.3 THE NON-INTELLECTIVE FACTORS 129
5.3.3.1 Personality Factors 129
5.3.3.2 Motivation 132
5.3.3.3 Learning Styles 133
5.3.4 COGNITIVE FACTORS 134
5.3.5 TRANSFER EFFECTS 135
5.4 CONCLUSIONS 137
5.5 LIMITATIONS OF THIS RESEARCH 138
CHAPTER 6
SUMMARY AND RECOMMENDATIONS
6.1 INTRODUCTION 140
6.2 CHAPTER 1 - INTRODUCTION 140
6.3 CHAPTER 2 - LITERATURE REVIEW 141
6.4 CHAPTER 3 - RESEARCH METHODOLOGY 144
6.4.1 THE AIM OF THIS STUDY 144
6.4.2 HYPOTHESES AND DATA ANALYSIS 145
1466.4.3 SUBJECTS
6.4.4 EXPERIMENTAL DESIGN 146
6.4.5 PROCEDURES 147
6.5 CHAPTER 4 - RESEARCH RESULTS 148
6.6 CHAPTER 5 - DISCUSSION ~~D CONCLUSION 149
6.7 RECOMMENDATIONS FOR FUTURE RESEARCH 151
6.8 RECOMMENDATIONS FOR PRACTICAL USE OF THIS
RESEARCH 152
REFERENCES 155
TABLES
Table 3.1
Table 3.2
Table 3.3
Table 4.1
Table 4.2
Table 4.3
Table 4.4
Table 4.5
Table 4.6
Table 4.7
Table 4.8
Table 4.9
Table 4.10
Table 4.11
Table 4.12
Table 4.13
Table 4.14
Table 4.15
Table 4.16
Sex 62
Age 63
Home Language 63
The effects of intervention! no
intervention on learning potential scores 102
The Omnibus Normality test on learning
potential scores 102
Variance-Ratio Equal-Variance Test on
learning potential scores 103
Equal-Variance t-Test on learning
potential scores 103
Raven's Standard Progressive Matrices
pre-test: descriptive statistics 104
Raven's Standard Progressive Matrices
post-test: descriptive statistics 104
Omnibus Normality Test of residuals 105
Kruskal-Wallis One-Way ANOVA on ranks 105
High School Personality Questionnaire:
descriptive statistics 106
Pearson's Correlation Coefficients for
personality traits and learning
potential scores 107
Regression model summary of the 14
HSPQ traits 109
Regression model of the 14 HSPQ traits 109
Overall test of significance 110
Correlation matrix of independent
variables 110
Picture Motivation Tests: descriptive
statistics 111
Pearson's Correlation Coefficients for
motivational factors and learning
potential scores 113
Table 4.17
Table 4.18
Table 4.19
Table 4.20
Table 4.21
Table 4.22
Table 4.23
Table 4.24
Table 4.25
Table 4.26
Table 4.27
Table 4.28
Table 4.29
Table 4.30
Table 4.31
Regression model summary of the 10
PMT traits 114
Regression model of 10 PMT traits 114
Overall test of significance 115
Learning styles: descriptive statistics 116
Pearson's Correlation Coefficients for
learning styles and learning potential
scores 116
Pearson's Correlation Coefficients for
Cattell's Culture Fair Intelligence Test
Scale 2, Form A and learning potential
scores 118 •Cattell's Culture Fair Intelligence Test,
Scale 2, Form A, raw scores 119
Cattell's Culture Fair Intelligence Test,
Form A, standard scores 119
Cattell's Culture Fair Intelligence Test,
Scale 2, Form B, raw scores 120
Cattel's Culture Fair Intelligence Test,
Scale 2, Form B, standard scores 120
The effects of intervention/ no
intervention on Cattell's Culture
Fair Intelligence Test 121
Results of the Omnibus Normality Test on
the difference scores on Cattell's
Culture Fair Intelligence Test 121
Results of the Mann-Whitney u-test on
the difference scores of Cattell's
Culture Fair Tests 122
Kruskal-Wallis Multiple-Comparison
z-value test 123
Pearson's Correlation Coefficients for
the difference scores between the CCFIT
Form A and Form B and learning
potential scores 125
FIGURES
Figure 3.1 The Solomon 4-Group Design 64
Figure 3.2 Kolb's Circular Learning Pattern 92
Figure 6.1 The Solomon 4-Group Design 147
Chapter 1
INTRODUCTION
1 . 1 RE SEARCH BACKGROUND
Education has been identified as one of the most important
tasks facing South Africa today. Due to the disparity in
the quality and availability of education across the
different population groups, using past academic performance
as a criterion for selection of the most suitable candidates
for educational and career opportunities can only perpetuate
the injustices of the apartheid education system. The use of
traditional psychometric tests in a population as culturally
diverse as South Africa is also questionable since many of
the commonly used tests were originally designed for white,
middle-class, western subj ects with concomitant equal and
similar educational opportunities. It is therefore important
to find new and more equitable methods of assessing
individuals in a socially diverse society.
Since the early 1960's dynamic assessment has been studied
extensively as an al ternative to traditional psychometric
testing (Lidz, 1987). Due to the time and expertise needed
to train subjects individually during assessment, the
incomparability of scores, and the lack of knowledge
concerning examiner effects, more emphasis is being placed
on short-term learning tests with a standardised training
phase (Guthke & Stein, 1996). However, very few researchers
have examined the effects of extraneous variables on
learning potential scores. In this research a short
standardised training phase, which is presented on video, is
1
used, and the effects of cognitive factors, learning styles,
personality traits and motivational factors are examined in
relation to learning potential scores.
1.2 NORMATIVE ASSESSMENT
The migration of culturally different populations throughout
the world has resulted in many societies becoming as
heterogeneous as South African society. The need to assess
culturally diverse populations has led to practitioners from
many countries questioning the validity and applicability of
traditional norm-referenced assessment procedures.
Although cultural differences are commonly cited as a reason
for underestimating intelligence, those who are not deriving
the full benefit from education due to physical or mental
disabilities are also at risk of being misclassified.
Many diverse proposals have been proffered to address the
inadequacies of normative assessment. These include the
following suggestions:
• Culture-fair or culture-free tests have been developed.
Some of these have been criticised for their poor
theoretical background (Anastasi, 1990) . The term
culture-fair has been used to describe tests that
minimise the effects of cultural influences, e.g. Raven's
Progressive Matrices (Raven, 1976) and Cattell's Culture
Fair Tests (Cattell, 1959a). However, the notion of a
cul ture "free" test is not widely accepted, since the
effects of cultural learning cannot be eliminated from
cognitive tests.
2
• Developing separate tests for each cultural group
(Williams, 1972) or adapting existing tests to be more
suitable for other cultural groups.
• Establishing new reference norms by including different
groups in the sample (Resing, Bleichrodt, & Drenth,
1986) .
• Using differential norms that compensate for societal or
cuI tural deprivation - a form of posi tive discriminati.on
(Brown, 1994; Petersen & Novick, 1976).
• Testing the usefulness of items with statistical and/or
linguistic procedures for detecting item bias in tests
(Kok, 1988). Removal of biased items could affect aspects
of the test that are relevant for successful prediction.
• An attempt to replace the 'static' traditional
intelligence tests with a more 'dynamic' assessment
procedure.
This research is concerned with the last of the above
proposals.
1.3 DYNAMIC ASSESSMENT
Dynamic Assessment is the generic term used to describe a
variety of evaluation approaches that emphasise guided
learning to determine a subject's potential for change.
While static tests have been characterised as retrospective
(i.e. they assess what has been learned in the past) dynamic
tests are described as prospective (i.e. they assess
potential ability based on present learning) A feature
common to all dynamic assessment models is the emphasis on
the individual's potential for change.
3
Proponents of dynamic assessment maintain that this form of
testing is preferable whenever doubt exists as to the
fairness of traditional instruments, since it is considered
a means of offering an optimal chance of achieving an
equi table test result. Not only are some of the concerns
surrounding cross-cultural assessment addressed by dynamic
assessment techniques, but it also becomes possible to
broaden the scope of assessment. For example, dynamic
assessment makes it possible to:
• Discriminate between individuals who are educationally
deprived, those who are mentally retarded and those who
are slow learners.
• Assess those with physical disabilities, such as the
blind or deaf.
II Assess giftedness in the culturally deprived.
II Reduce the differences between ~disadvantaged" and
~privileged" children (Guthke & Stein, 1996).
II Reduce the effects that the quality of teaching in
schools has on test results (Guthke & Stein, 1996).
• Reduce the effects of anxiety, neuroticism and stress
and increase the effects of creativity (Guthke & Stein,
1996) .
Dynamic assessment also overcomes some obstacles or
inhibiting characteristics, such as lack of motivation,
anxiety, impuls i vi ty and lack of planning. The predictive
power of intelligence tests is also enhanced since the
extent of the individual's ability to take advantage of
training is measured (Day, Engelhardt, Maxwell, & Bolig,
1997) .
4
1.4 APPROACHES TO DYNAMIC ASSESSMENT
Campione (1989) has proposed a taxonomy of various
approaches to dynamic assessment along three dimensions:
(i) focus which refers to the different ways
potential can be assessed;
(ii) interaction the differences in the
interaction between the examiner and subject;
(iii) target - whether the test is general or domain
specific.
(i) Focus
The maj ori ty of researchers in dynamic assessment use the
test-train-retest paradigm. The focus within this paradigm
differs according to the results the researcher prefers to
emphasise. Practitioners who base their research on
Feuerstein's (1979) Learning Potential Device, focus on
identifying the cognitive strengths and weaknesses in order
to develop programmes sui table for the individual (Lidz,
1987; Mearig, 1987; Skuy, Gaydon, Hoffenberg, & Fridjohn,
1990) .
other researchers focus on:
• the learning potential or gain score (Budoff, 1987a);
• the post-test score (Carlson & Weidl, 1992; Embretson,
1987);
• the transfer of learned skills to other situations
(Campione, Brown, Ferrara, & Bryant, 1984; Ferrara,
1987).
5
The test-train-retest paradigm was used in this research.
The focus was on both the learning potential score and
transfer of learned skills.
(ii) Interaction
The interaction between the examiner and the subject may be
a standardised protocol (Campione et al., 1984; Guthke,
1993) or an unstructured clinical interview (Feuerstein,
1979; Skuy et al., 1992) The choice of an interaction
method is dependent on the aims of the assessment. A
standardised protocol generates quantitative data that is
psychometrically acceptable, whereas the clinical interview
generates a clinical picture of the subject's cognitive
strengths and weaknesses.
The lesson ln this research was presented on video. The
interaction between the instructor and subject was therefore
minimal and standardised.
(iii) Target
The goal of assessment can either be a general assessment of
intelligence or assessment of domain-specific skills and
processes. Feuerstein (1979) concentrates on identifying
strengths and deficient cognitive functions across a variety
of content areas. General skills in the form of a variant of
Raven's Progressive Matrices were the target in the
Campione, Brown, Ferrara, Jones, and Steinberg (1985) study.
Ferrara, Brown, and Campione (1986) also targeted general
skills in their study using a Series Completion task.
Hamers, Pennings, and Guthke (1994) have researched domain
specific areas such as mathematics and reading.
6
Raven's Standard Progressive Matrices (Raven's SPM) and
Cattell's Culture Fair Intelligence Tests (CCFIT), which
were used in this research, are both measures of the general
factor g.
Using the above taxonomy this research can be categorised as
using a test-train-retest paradigm focusing on learning
potential scores, using standardised interventions and
targeting general skills.
1.5 FEATURES OF THIS RESEARCH
1.5.1 GROUP ADMINISTRATION
Dynamic assessment is essentially an individual method of
testing. Time and expertise constraints have resulted in
many studies using a small number of subjects (e.g. Hickson
& Skuy, 1990, n = 22; Rutland & Campbell, 1995, n = 26;
Schottke, Bartram, & Weidl, 1993, n = 22). Some studies do,
however, use group administration. The Learning Potential
Assessment Device (LPAD) includes eight tests that may be
used during group administration. In a large study of 962
children in Israel, Babad and Bashi (1977) found that group
administration of the Series Learning Potential Test showed
significant effects of coaching. Rand and Kaniel (1987)
state that group testing should not replace individual
testing, but rather be used as a screening device to detect
students who show difficulties in performance. Considering
the time and expertise necessary for the administration of
individual learning potential tests, group testing may
become more acceptable and widely used in the dynamic
assessment paradigm.
7
In this study, Set Variations 1 (Var. 1) which is one of the
tests In the battery of the group administered LPAD, was
used as a teaching tool (refer to 3.8.2). This test is
similar in kind and form of representation to the analogical
thinking tasks of Raven's SPM which was used as both a pre
and post-test.
1.5.2 STANDARDISED PROTOCOL
Many researchers (Budoff, 1987ai Carlson & Weidl 1979;
Embretson, 1987; Guthke, 1993) have emphasised the need for
a standardised protocol during the teaching phase of dynamic
assessment. A high degree of individualisation of the
training phase (e.g. Feuerstein, Rand, Jensen, Kaniel, &
Tzuriel, 1987) can lead to subjectivism in test
administration and interpretation, and no possibility of
intersubject comparisons. The choice of whether to use
standardised or clinical intervention procedures depends on
the goals of the assessment. Clinical intervention will lead
to a diagnosis of cognitive strengths and weaknesses,
whereas standardised protocols are generally concerned with
devising methods to increase the predictive validity of
assessment and to provide quantitative data that is
psychometrically acceptable.
Since the goals of this research were to examine the effects
of non-cognitive factors on learning potential scores it was
necessary to standardise the learning phase.
1.5.3 SHORT LEARNING INTERVENTION
The teaching phase of the maj ori ty of learning potential
tests relies on lengthy training phases. Guthke (1993)
8
developed the Short-term Learning Potential Test, which
requires only one testing session during which systematic
feedback and assistance are given. He was able to show that
a relatively short training session of one hour could lead
to significant learning gains. Diemand, Schuler, and Stapf
(1991) administered the Raven's Advanced Progressive
Matrices to students of technology and found that a fifty
minute training phase was sufficient to produce significant
gains.
The video used as a standardised teaching protocol in this
study was approximately one hour in length.
1.5.4 SCORING
The evaluation of change in test performance is central to
all approaches in dynamic assessment. The results of dynamic
assessment yield a number of scores:
• The pre-test score, which would normally be used for
classification or prediction in static testing.
• The data which is available from the instructional
interaction. The LPAD attempts to specify the processes
involved in change during administration. Campione and
Brown (1987) measure how much help the subjects need in
order to reach a specified criterion. Guthke (1993) uses
the amount of help and the kinds of prompts that the
child needs during the assessment as a test score.
• Carlson and Weidl (1979) and Embretson (1987) focus on
the post-test score. They believe that the intervention
provided minimises factors that reduce performance, such
as misunderstanding instructions. The final test scores
are believed to have a greater predictive validity.
9
• The gain score, which is the difference between the pre
and post-test scores was the major focus of Budoff's
(1987a) research. He argued that gain scores give
diagnostic information beyond pre-test and other
standardised measures.
Simple gain scores have been heavily cri ticised by some
researchers (Boeyens, 1989; Embretson, 1987). However, the
concept of gain is embedded in most research in dynamic
assessment.
In this study gain scores were correlated to personality
factors, motivational traits, and learning styles to assess
the effects of these factors on learning potential.
1.5.5 GENERAL SKILLS
Much of research conducted using dynamic assessment
concentrates on general skills or abilities (Budoff, 1987b;
Car lson & Weidl, 1992; Embretson, 1987; Feuerstein, 1979;
Lidz, 1987). The assumption here is that assessments of
fairly general abilities will provide information across a
number of situations.
In this research Set Variations 1 was used as a teaching
tool and the RSPM was used as both a pre-test and a post
test to assess learning potential scores. These tests are
similar in the kind of problems they present. The CCFIT
Forms A and B were used as pre- and post-tests to assess
transfer. These tests were constructed as measures of the
general factor g.
10
1.5.6 PRACTICE EFFECTS
The typical test-train-retest design of many learning
potential tests makes it very difficult to separate the
effects of practice from those of intervention. Results of
retesting can vary considerably and several unknown factors
probably moderate the retest effect. Klauer (1993) maintains
that fluid intelligence (which involves perceptual and
cogni tive performance skills) shows a higher susceptibility
to retest effect than crystallised intelligence (vocabulary
and numerical skills). Both the RSPM and CCFIT measure fluid
intelligence. Klauer suggests that it is advisable to
include a retest-only control group when interpreting mean
gain.
This study included retest only groups in order to separate
the effects of practice from those of intervention.
1.5.7 TRANSFER EFFECTS
Trans fer refers to the capacity to apply what has been
learned to new problems or situations. Transfer tasks must
be related to the trained tasks but at the same time be
different enough not to be a replication of the learning
task. Near transfer refers to the ability to transfer what
has been learned to problems of a similar kind and of
approximately equal complexity. Far transfer refers to the
application of rules learned to novel situations (Ferretti &
Butterfield, 1992).
Campione and Brown (1987) suggest that it is not sufficient
to teach children rules and principles, it is also necessary
to teach in a way that will allow children to use these
rules with some flexibility. Vye, Burns, Delcos, and
11
Brans ford (1987) found that performance following dynamic
assessment is predictive of within-domain (near) transfer
but not of across-domain (far) transfer.
In this study Cattell's Culture Fair Intelligence Test Form
A was administered as a pre-test and Form B as a post-test
to measure far transfer effects. These tests consist of
problems not entirely dissimilar to those in Raven's
Standard Progressive Matrices, but are presented in a more
complex and novel way.
1.6 DEFINITION OF MAIN TERMS
1.6.1 LEARNING POTENTIAL
The difference between the scores obtained on the pre-test
and post-test using the test-train-retest paradigm was
defined as the learning potential score. Raven's Standard
Progressive Matrices was administered twice - once as a pre
test, then after a teaching phase, re-administered as the
post-test.
Vygotsky's (1978) Zone of Proximal Development (ZPD) is a
key concept in learning potential assessment. The ability to
profit from guided instruction is defined as learning
potential.
1.6.2. COGNITIVE FACTORS
Two issues were involved in the role of cognitive factors in
this research:
12
(i) Can general cognitive ability predict learning
potential scores?
(ii) Can general cognitive ability and/or learning
potential scores predict transfer gains?
(i) General cognitive ability was assessed on Cattell's
Culture Fair Intelligence Test Form A (refer to 3.8.6). The
IQ scores obtained were used to establish any relation
between these static measures and learning potential scores.
Early empirical evidence reported low or insignificant
correlations between various intelligence measures and
learning potential measures (Brown & Ferrara, 1980; Budoff,
1987 (b); Vye et al., 1987) However, three contemporary
studies (Campione et al., 1985; Ferrara et al., 1986;
Ferretti & Butterfield, 1992) reported significant
correlations between intelligence and learning, maintenance
and transfer.
(ii) Transfer refers to the ability to apply what has been
learned to novel tasks. Transfer scores were obtained from
the difference between CCFIT Form B (the post-test) and the
CCFIT Form A (the pre-test). This transfer measure was used
to ascertain whether there was any relationship between
learning potential and transfer scores.
Bryant (1982) and Bryant, Brown, and Campione (1983) found
that gain scores were better predictors of transfer than
static ability measures.
13
1.6.3 NON-INTELLECTIVE FACTORS
Feuerstein (1979) maintains that non-intellective factors,
such as motivational levels, personality factors and
learning styles are an integral part of an individual's
manifest behaviour. These factors should not therefore be
considered non- intellective, but rather a central part of
cognitive modifiability and performance.
Classical test theory has never had a clear hypothesis about
the exact relationship between true ability and affective
factors. Tzuriel (1992) suggests that we need to ask
questions, such as: ~What exactly are those non-intellective
factors? How do they effect performance?" and ~How can we
differentiate between non-intellective factors and cognitive
fa·ctors?"
This research examined three possible variables that could
influence learning potential scores: Personality, Motivation
and Learning Styles.
1.6.3.1 Personality
The High School Personality Questionnaire (HSPQ) (Cattell &
Cattell, 1973) which was used in this research, yields a
personality profile that identifies fourteen primary
personality factors (refer to 3.8.3). These traits were
investigated to ascertain whether there was any relation to
learning potential scores.
It is generally believed that non-cognitive factors, e. g.
personality characteristics, can influence test performance.
Al though very little research is available on the role of
14
personality traits in dynamic assessment, learning theorists
do generally agree that personality plays an important role
in the learning process (Boekaerts, 1996; de Fruyt &
Mervielde 1996; De Raad, 1996; Eysenck, 1996).
Ruijssenaars, Castelijns, and Hamers (1993) maintain that it
is generally assumed that personality variables such as fear
of failure and stress, are greater during the pre-test than
during the post-test. Guthke and Lehwald (1980) found that
the personal i ty characteristic \\ fear" had no differential
effect on pre-test and post-test results. Sensi tivi ty to
stress and frustration-tolerance were found to be stronger
during the pre-test than during the post-test. It is
postulated that training allows the subject to become used
to the task. Familiarity with the task decreases stress.
Budoff (1987a) reports that personality variables such as
neurotic anxiety, acting-out, bravado, mischievousness,
obedience and depressed self-criticism correlate with a poor
performance and/or poor gain scores on Koh's Block Designs.
Correlates of good Koh's performance scores were feelings
that others think well of one's physical ability, belief
that one will succeed in adversity and high achievement
motivation.
1.6.3.2 Motivation
The Picture Motivation Tests (Du Toit, 1983a) use a sYmbolic
pictorial technique for measuring a number of motivational
aspects that are considered important in understanding the
individual personality. Ten subtests measuring different
motivational aspects were used in this research (refer to
3.8.4). These factors were investigated to ascertain whether
15
there was evidence of any relationship to learning potential
scores.
Very little research is available on the effects of
motivation on learning potential. The role of motivation in
learning has been extensively studied in educational
psychology (Dweck, 1991; Mayer, 1998; Strage, 1997).
Atkinson (1980) maintains that if one assumes that a lack of
ability can be compensated for by achievement motivation, it
is conceivable that subjects with equal test scores can have
different combinations of proportions of true ability and
achievement motivation.
Vroom (1964) indicated that when motivation is low, both
high and low ability individuals show similar low levels of
performance. However, when motivation is high, performance
variability due to individual differences in ability is more
evident (Kanfer & Ackerman, 1989).
Meijer (1993) found that a combination of high levels of
both achievement motivation and fear of failure lead to a
strong desire to perform well and a strong fear of
performing poorly. These tendencies expend a large part of
the cognitive processing capacity and attention to the task
is reduced.
1.6.3.3 Learning Styles
Honey and Mumford (1982) maintain that when a teaching style
and a learning style are in accord, learning can take place
more effectively. They developed the Learning Styles
Questionnaire, which measures four main styles of learning:
16
Theorist, Reflector, Activist and Pragmatist (refer to
3.8.5). The standardised training phase in this research
would favour a Theorist approach to learning. The sUbject's
learning style was determined in order to ascertain whether
the teaching style had an effect on the learning potential
scores.
Although the effects of specific forms of the training phase
on results of learning potential tests have not been
studied, it can be assumed that certain forms of training
give some subj ects an advantage while others will be at a
disadvantage (Guthke, 1993). Hamers and Sijtsma (1993)
maintain that the efficiency of learning may be contingent
on the teaching strategy employed.
1 . 7 STATEMENT OF THE PROBLEM
In light of the time and expertise required, the
incomparability of scores, the lack of knowledge concerning
the examiner effects and the role of cogni tive and non
intellective factors in dynamic assessment, this research
proposes to examine the following questions:
I. Whether a short, group administered dynamic assessment
procedure using a standardised intervention protocol
presented on video, is viable.
II. Whether current general intellectual ability has a
significant effect on learning potential scores.
III. Whether non-intellective factors such as certain
personali ty factors , motivational traits and learning
styles have significant effects on learning potential
scores.
17
IV. Whether transfer from pre-mediation to post-mediation
cognitive functioning is statistically significant.
1.8 AIMS OF THE RESEARCH
In this research the effects of certain cognitive factors,
personality traits, motivational factors and learning styles
on learning potential scores are examined. Learning
potential scores are defined as the difference between the
pre- and post-test scores on Raven's Standard Progressive
Matrices. The training phase is standardised according to a
Theorist learning style and is presented on video to the
subjects using Feuerstein's Set Variations 1 as a teaching
tool. Transfer performance is measured as the difference
between the pre- and post-test administration of Cattell's
Culture Fair Tests Forms A and B, respectively.
1.9 DELIMITATIONS OF THIS RESEARCH
This research is exploratory in the sense that only one
aspect of learning potential is being examined, (i.e.
general cognitive ability) This precludes any aspects
concerned with specific learning, such as learning
Mathematics or English.
It also only concentrates on high school learners from
previously disadvantaged communities. All the subjects are
from a single grade in a single school of these communities.
Furthermore this study is concentrated at a specific point
in time. It does not relate to sustainable performance. A
longi tudinal rather than a cross-sectional study would be
18
necessary to ascertain whether improved performance can be
maintained over a long time.
1.10 LAYOUT OF THE CHAPTERS
Chapter 2 consists of a review of the literature pertinent
to this research and includes an historical perspective.
In Chapter 3 the research approach is defined and the
research questions are formulated. This includes a
description of the method of data collection and analysis.
In Chapter 4 the statistical results and a discussion of the
findings are presented.
In Chapter 5 a summary of the thesis is presented and
recommendations for further research are discussed.
Chapter 6 consists of a summary of chapters 1 5.
Recommendations for future research and practical uses of
these results are suggested.
19
Chapter 2
LITERATURE REVIEW
2.1 INTRODUCTION
Two methods have traditionally been employed in the
assessment of a student's ability to learn: past academic
achievement, and/or intelligence tests. Both these methods
are inextricably linked to the quality and availability of
educational opportunities afforded to the individual. These
methods have, therefore, proved to be good predictors of
future learuing in relatively homogeneous societies, from a
cuI tural diversi ty point of view, where equal and similar
educational opportunities are available to all social groups
in that population.
However, a marked disparity in the quality and availability
of educational opportunities, both at school and at home,
resul ts in some groups being systematically disadvantaged.
For example, Visser (1978) found that past academic
achievement was a good predictor of future learning in white
schools but not in black schools. Systematic differences
have also been found in IQ tests. For example, Jensen (1969)
found a mean difference of 15 IQ points between white and
black groups of children, and Babad and Bashi (1977) found a
time lag of two years between advantaged and disadvantaged
children.
In addition, various authors (Duran, 1989; Hamers, Hessels,
& Pennings, 1996; Reynolds, 1982; Sattler, 1982) have
20
suggested that the validity of cross-cultural IQ testing is
questionable for the following reasons:
• Cultural setting. Developmental opportunities may be very
different from those available to most western children,
e.g. rearing practices, expectations, aspirations, formal
and informal learning.
• Language and cross-cultural communication processes.
Understanding the instructions may be affected by
language skills not being fully developed or because the
test is administered in a language other than the
subject's home language.
• Examiner bias. Psychologists and subj ects may belong to
different racial groups. This could intimidate children
especially if communication is inadequate.
• Inappropriate content. Tests are geared towards white
middle-class homes and values and not all children will
have been exposed to materials used in the test items.
Items could also contain references to the cultural
background of the test composer e. g. "What is bacon?"
could be difficult for a child from an Islamic
background.
• Test-wiseness. It is generally assumed that subjects have
acquired the skills necessary for test-taking such as
dealing with time constraints, understanding the
instructions, dealing with one item at a time and
considering all possible answers.
• Inappropriate standardisation samples. Most measures of
intellectual ability use norm-referenced tests where the
goal is to compare the performance of a particular person
wi th the average performance of subj ects in a normative
sample. In South Africa it cannot always be assumed that
all subjects had the opportunity to acquire the same
21
knowledge and skills. Results should be compared to
carefully constructed (i.e. reasonable representation of
language, sex, age, rural vs. urban etc.) norm groups,
which may not always be available.
• Measurement of diverse constructs. Mercer (1979)
contends, for instance, that IQ tests measure the degree
of Anglocentrism at home.
• Differential predictive validity. Cognitive tests fail to
predict some relevant criteria for minorities on an
acceptable level.
Despite these considerations, result-orientated intelligence
tests, where performance assessment is based on current
functioning without the benefit of help, have been widely
used across many cultures since James McKeen Cattell
described the first "mental test" in 1890 (Cattell, 1890).
However, the need for a more dynamic form of testing was
20 thalready being mooted early in the century.
2.2 HISTORICAL REVIEW
The concept of intelligence as an innate, relatively
permanent ability, was questioned as far back as 1909 by
Binet, who maintained that intelligence could, to some
extent, be taught (Binet, 1909); and by Thorndike who
defined intelligence as the 'ability to learn' (Thorndike,
1924).
In the 1920's psychologists began to suggest new approaches
to assessment that intimated the need for dynamic
assessment. For example, Buckingham (1921) suggested that
assessment of the 'ability to learn' should include both
what has been learned and what may be learned in the future.
22
Dearborn (1921) suggested that tests should involve actual
learning rather than the results of learning.
The next few decades saw isolated studies concerned with the
effects of practice and coaching on intelligence scores
(Haeussermann, 1958; Macpherson, 1948; Vernon, 1954; Volle,
1946; Woodrow, 1946;).
In the 1960's efforts were made to devise direct measures of
learning by introducing a test-train-retest model. Shucman
(1960) trained severely retarded children to a criterion of
three consecutive responses on each task. She found that
these tests could discriminate between IQ levels of this
group, and that transfer and retention scores were the most
sensitive reflectors of IQ. Post-training scores were found
to be more stable than initial test scores and were better
predictors of teacher ratings.
Jensen (1969) studied the performance of ethnic minorities.
Using learning tasks he found that standard IQ tests
discriminated between fast- and slow-learning Anglo American
children, but learning tests resulted in ~low-IQ" Mexican
Americans performing at a much higher level than their IQ
tests suggested. He concluded that, although Mexican
Americans consistently scored lower on static tests, the
distribution of learning abilities is not different from
those of the Anglo-American population.
After almost 50 years of isolated questioning of static
intelligence testing, various factors converged in the
1970's that lent impetus to the growing dissatisfaction with
assessment practices:
23
• In the United states and Israel evaluation of low-SES
minority children became an issue. Thousands of children
who did not appear to be dull obtained low scores on
measures purporting to test intelligence. This led to a
preponderance of minorities in special education classes.
• Haywood (1970) and Haywood, Filler, Shifman, and
Chatelenat (1975) brought the work of Feuerstein and his
co-workers to the attention of the American public.
• Budoff (1974), Campione and Brown (1987), and Carlson and
Weidl (1978) among others were carrying out a significant
body of research directly related to dynamic assessment.
• Vygotsky's (1935) Mind in Society: The development of
higher psychological processes, which proposed the ~zone
of proximal development", was translated into English in
1978 by Cole, John-Steiner, Scribner and Souberman.
In addition, the expansion of psychometric assessment due to
the democratisation of education and the migration of
cul turally diverse populations led to the need to produce
more adequate ways to assess individuals. Assessment now
needed to include the following groups:
• Various age groups, from the newborn to the aged.
• Individuals from various cultures, some of whom may be
preliterate or speak a language different to that of the
test and/or the tester.
• Individuals with different levels of functioning, from
those who were previously not considered testable due to
their low levels of functioning, to the intellectually
gifted.
This gave rise to diverse attempts to modify psychometric
practice. A large body of research has accumulated since
24
1970 and various aspects of dynamic assessment are being
studied in many parts of the world. The theoretical
foundation of the dynamic assessment approach is based on
Vygotsky's (1978) concept of the zone of proximal
development.
2.3 VYGOTSKY'S THEORY OF THE ZONE OF PROXIMAL DEVELOPMENT
Although Vygotsky (1896-1934) was a contemporary of Piaget,
his theories were relatively unknown until quite recently.
This was because his work was banned in Russia between 1930
and 1950 for political reasons (Kozulin, 1995), and only
became generally available in the West after the translation
of Mind in Society in 1978. His theory of the Zone of
Proximal Development, based on his concept of 'development
generated learning' (Vygotsky, 1978), has had a major impact
on dynamic assessment.
Development-generated learning was developed as a
theoretical model of the relationship between education and
developmental processes. Vygotsky (1978) maintained that a
child's mind does not develop spontaneously, but is a result
of the acquisition of 'psychological tools', such as
concepts, symbols, formulae, etcetera. These tools are
presented (or mediated) to the child by an adult or a more
capable peer. These tools are first used at an external
level and slowly become internalised. Internalisation alters
the child's mental processes.
This model was developed into a diagnostic principal for the
psychological assessment of children. Vygotsky (1978)
maintained that psychologists should not limit themselves to
the current status of an individual's intelligence, which is
25
usually thought to be determined by biological maturation or
inherent ability and measured on standardised tests. The
process of transition (through mediation) to new forms of
behaviour should also be examined. He did not reject the
standardised psychometric approach to assessment, but argued
that the learning of new 'psychological tools' should be
incorporated into the assessment procedure. To this end he
distinguished between two zones: The Zone of Actual
Development and the Zone of Proximal Development (Karpov,
1995; Karpov & Haywood (1998).
The number of test items a child is able to answer correctly
wi thout any assistance measures the Zone of Actual
Development (ZAD). This score provides a quantitative index
of current developmental status.
The Zone of Proximal Development (ZPD) is used as an
indication of the child's ability to benefit from
interaction with an adult or more capable peer. The
difference between the ZAD score and the level of competency
the child reaches with assistance is operationally defined
as the ZPD.
Luria (1961) modified Vygotsky's developmental assessment
procedure into an assessment of learning potential. The
interaction between child and adult was transformed into a
training phase that became part of the assessment procedure.
By comparing pre-test and post-test scores he was able to
differentiate between a child's actual development and
his/her potential performance level.
26
Vygotsky's (1978) theory of the ZPD has become the central
concept in the practice of dynamic assessment (Ramers,
Ressels & Pennings, 1996).
2.4 CURRENT MODELS OF DYNAMIC ASSESSMENT
Current models of dynamic assessment are generally based on
Luria's (1961) methods. The basic format consists of a pre
test, in which the subject is tested while working alone in
order to provide a baseline measure. The subject then
undergoes a training protocol. Finally the subject is
retested to assess whether he/she has gained from the
instruction. Jitendra and Kameenui (1993) identified five
distinct models of dynamic assessment in research
literature. These models are essentially American. A
European model that has been widely reported has been
inclUded. Although they all use the test-train-retest method
there are wide variations in the target skills, testing and
training procedures. The six models are:
• Test-train-retest Gain Score Model
• The Cylindrical Model of Learning Potential Assessment
• Testing-the-Limits
• Graduated Prompting
• The ~Continuum of Assessment Services" Model.
• Train-within-test.
2.4.1 TEST-TRAIN-RETEST GAIN SCORE MODEL
Budoff (1974, 1987a, 1987b) used the basic test-train-retest
paradigm to assess the learning potential of educable
retarded children. The initial thrust of this technique was
to standardise procedures of dynamic assessment in order to
27
yield a less biased estimate of the ability to profit from
experience. The training phase consists of teaching the
child how to think about solving problems when the content
may be unfamiliar and appropriate strategies are not
apparent. Praise and encouragement are provided and the
child is allowed to experience success.
Budoff (1987a) defines learning potential as the gain score
from pre- to post-test. He originally suggested three
categories: gainers, those who showed significant gains
between pre- and post-tests; non-gainers, children who
showed no improvement from training; and high scorers, those
who did well on the pre-test. By 1987 he preferred to see
gain status along a continuum rather than as three distinct
categories. Budoff has consistently found that training
results in a substantially greater level of improvement for
low socio-economic status children. He suggests that (
children who perform adequately following a brief period of
training are not mentally handicapped but rather
educationally handicapped due to inadequate family and
school experiences.
2.4.2 THE CYLINDRICAL MODEL OF LEARNING POTENTIAL ASSESSMENT
This model is based on Feuerstein's (1979) theory of
structural cognitive modifiability and the mediated learning
experience. The assessment procedure follows the test-train
retest method, but in this case the training phase consists
of intensive mediated learning experiences. The subj ect' s
performance is analysed and interpreted using the following
task dimensions:
28
(1) The modality of presentation, which may be verbal,
pictorial, numerical, figural, symbolic, graphic,
or any combination of these.
(2) The novelty and complexity of the tasks may be
manipulated according to the needs of the subject,
but generally starts by giving all the relevant
information necessary to teach the cognitive
principles involved in the task.
(3) The cognitive operations used to solve the task
are the rules according to which the information
is organised, manipulated and understood. These
operations include categorisation, analogy,
seriation, logical multiplication, permutations
and syllogism.
Feuerstein (1979) developed the Learning Potential
Assessment Jjevice (LPAD) to identify impaired cognitive
functions in basic learning skills, to study the reasons for
low functioning and to ascertain the amount of investment
needed to improve cognitive functioning. All the test
instruments in this battery were constructed or adapted to
take the above task dimensions into account.
The., goals of this dynamic approach to assessment can be
either functional or structural. Functional dynamic
assessment limits the quantity and quality of the changes
that can be targeted. structural dynamic assessment goes
beyond immediate levels of functioning to search for changes
in the structural nature of the cognitive processes. This
view assumes the human organism to be an open system, which
is accessible to structural change, regardless of the
aetiology, stage of development or the severity of the
condition. The results of this form of assessment will not
29
be differences in the levels of performance of the subjects,
but the amount and nature of the investment necessary to
produce desired changes.
Feuerstein (1979, 1980) distinguished two kinds of learning:
(1) Learning by direct exposure to a stimulus. The
stimulus is perceived and reacted to on a basis of
trial-and-error.
(2) Mediated learning, where an experienced and
intentioned adult intervenes between the child and
the stimulus. The adult interprets the stimulus
for the child and in so doing instils learning
sets and habits.
According to Feuerstein mediated learning is an essential
form of learning. Deprivation of this form of learning can
lead to a reduced level of modifiability, a passive attitude
to cognitive tasks, an absence of motivation and a negative
self-concept. This is an important cause of the poor
performance of persons labelled as retarded on standard
intelligence tests.
The Leaning Potential Assessment Device (LPAD) uses mediated
learning to assess an individual's cognitive strengths and
weaknesses. The LPAD involves changes in four basic areas of
assessment:
(a) The structure of the test the tasks are
presented in the test-train-retest format that
allows the examiner to estimate the effects of the
teaching process.
30
(b) The test situation - the examiner is the teacher
observer and the examinee the learner-performer.
(c) The orientation of the test is the exploration of
the nature of learning so as to obtain information
to modify and enhance teaching.
(d) The interpretation of results improved
performance is interpreted as an indication of
cognitive potential.
Each instrument in the LPAD:
• requires the use of one or more cognitive functions;
• has been refined specifically for use in assessing
learning potential through years of use with large
numbers of subjects and in a variety of settings;
• represents tasks requiring higher mental processes;
• is controlled so that functioning is not contingent on
familiarity or prior knowledge;
• is able to detect microchanges in subjects following
exposure to stimuli mediated to them in the LPAD.
The LPAD is administered in a flexible, individualised and
intensely interactive process where the task may be changed
according to need, and the examinee modifies his/her
responses according the needs of the subject. The advantage
of the LPAD is that the diagnostic approach leads to
remedial programmes. Feuerstein has devoted many years to
assessing the modifiability of mentally retarded, culturally
deprived and autistic children and adolescents using the
LPAD and attempting to reverse the effects of the lack of
mediated learning using his Instrumental Enrichment Program
(Feuerstein, Hoffman, Jensen, & Rand, 1985).
31
Many researchers have continued to develop Feuerstein's
(1979, 1980) work. Employing the extensive and richly verbal
interaction based on the mediated learning developed by
Feuerstein, researchers have studied various 'minority
groups' . These include, among others, the mentally
handicapped (Molina & Perez, 1993), the deaf (Keane,
Tannenbaum, & Krapf, 1992), subjects with schizophrenia
(Sclan, 1986 and Skuy et al., 1992), adults with severe head
injuries (Heinrich, 1991), stroke patients (Carr, 1985),
immigrants (Kaniel & Tzuriel, 1992) and potentially gifted
students (Skuy, 1988).
The LPAD was developed primarily for use with adolescents
and school-going children. Mearig (1987) has modified the
existing LPAD instrument for use with kindergarten to
primary school age children. Tzuriel and Klein (1987)
developed the Children's Analogical Thinking Modifiability
(CATM) instrument, and Lidz (1987) developed the Pre-school
Learning Assessment Device, based on Feuerstein's
theoretical model.
The LPAD has been criticised as an assessment tool both from
a theoretical and methodological point of view. Buchel and
Scharnhorst (1993) maintain that the LPAD does not:
• allow for a rational analysis of test tasks because its
dimensions are not well defined;
• present a coherent theory of cognitive functioning;
• properly define the concept of operation;
• standardise hints, scoring procedures or the
interpretation of results;
• lacks reliability and validity studies.
32
Due to the inordinate amount of time and training necessary
to administer the Feuerstein (1979) model, many researchers
are looking for alternative methods of assessment. The
advantage of the LPAD is that the aim is diagnostic and it
is used as an aid to intervention. However, the predominant
role of the LPAD as an assessment tool in dynamic assessment
will be lost if improved standardisation procedures are not
incorporated (Buchel & Scharnhorst, 1993).
The changes brought about by dynamic assessment using the
LPAD are believed to be permanent and can be applied to
increasingly more complex and unfamiliar situations. This is
in contrast to many other dynamic assessment procedures
where the quantity and quality of the changes that are
targeted are limited.
2.4.3 TESTING-THE-LIMITS ASSESSMENT
Proponents of this model include Carlson and Weidl (1978,
1979), Carlson and Dillon (1978) and Guthke (1993) among
others. This approach assesses the limits of the subjects'
abilities by integrating various, usually standardised,
interventions into the testing procedure. There is no
training or practice outside the testing situation itself.
The interventions used in this paradigm include:
• Providing simple feedback concerning the correctness or
incorrectness of the responses.
• Prompting the subj ect to verbalise how (s) he solved the
problem after each answer.
• Prompting the subject to verbalise during and after
solving the problem.
33
• Providing elaborated feedback that explains the
principles involved while solving the problem.
• Prompting the sUbject to verbalise during and after the
solution while providing an explanation of the principles
needed to complete the task.
Testing-the-limits does not require alterations in the
general structure of traditional tests. Modifications of the
tests require only that one or more of the above procedures
be incorporated into the testing situation. Raven's Coloured
Matrices, Cattell's Culture Fair Test, Matching Familiar
Figures Test, Harter's Perceived Competency Scale for
Children and Trail Making and Visual Search Tasks are
commonly administered measures.
For example, Carlson and Weidl (1978, 1979) used three
methods in the administration of the Raven Progressive
Matrices: (a) standard administration, (b) sUbjects were
required to verbalise the solution before seeing the
alternatives or (c) verbalisation after making their choice.
They report that the post-test scores for conditions (b) and
(c) were more predictive than the scores from the standard
administration. Increases in level of performance are seen
to reflect modifications in the understanding of the task or
reduced anxiety in the testing situation.
Carlson and Dillon (1978) found that standardised
administration or simple feedback did not lead to higher
levels of performance among deaf subj ects. However, each
elaborative condition resulted in increased performance. The
authors suggest that an activation process, such as focusing
the child's attention, which leads to the solution, is
probably involved.
34
Schroots (1979) and Spelberg (1987) developed and studied
several limit-testing procedures using tasks from existing
intelligence tests. Wijnstra (1986) developed two learning
potential tests - a puzzle-version of Raven's Progressive
Matrices and a numerical series test. The standardised
training procedures of these tests consist of a combination
of feedback and verbalisation.
Guthke (1993) used one testing session during which either
systematic feedback or extensive assistance in addition to
simple feedback was provided. Both these interventions were
fully standardised. He reported increased performance on all
intelligence tests after training.
Irrespective of the tests used, the testing conditions of
verbalisation and elaborated feedback has led to higher
levels of performance than standard testing conditions
(Bethge, Carlson, & Weidl, 1982; Carlson, 1989; Carlson &
Weidl, 1978, 1979). Increased performance with these
conditions was found regardless of intelligence level,
learning disabilities, or cultural and racial differences.
Dillon (1979) contends that this method is suitable for
routine psychoeducational assessment.
2.4.4 GRADUATED PROMPTING ASSESSMENT
The graduated prompting assessment model developed by
Campione and Brown (1978, 1984, 1987) is based on Vygotsky's
zone of proximal development. The subj ect' s initial
competence is assessed as a baseline measure. The child is
then presented with a number of problems. If slhe is unable
35
to solve a particular problem, a series of hints is given.
These prompts are standardised and hierarchically sequenced.
Unlike testing-the-limits the hints are independent of the
child's response. The initial hints are very general, if the
child is still unable to answer correctly; the succeeding
hints become progressively more specific and concrete. This
allows for the estimation of the minimum amount of help the
subject requires to solve the problem. The amount of
assistance needed for independent problem solution yields a
learning score.
This method differs from many other approaches in that it is
not how much improvement results from intervention, but
rather how much help is needed to achieve a specified
criterion. The same hinting procedure is used for transfer
problems, and is scored in the same way. Following these
interventions a post-test is given and a gain score
resulting from the intervention is determined.
Campione and Brown (1987) work with inductive reasoning
tasks such as series completion and Raven-type matrix
problems. They found that lower ability children required
more prompting to learn a set of rules to a certain
criterion and also more help to apply these rules to new
situations. A number of studies show that learning and
transfer scores were better predictors of gains than static
ability scores. Transfer scores also account for more
variance in gain scores than do learning scores.
Resing (1993) based her work on the approach of Campione and
Brown (1987). She developed two learning potential tests for
inductive reasoning: Exclusion and Verbal Analogies. The
training procedures were standardised and the hints given
36
during training were hierarchically ordered from general to
specific. Transfer was stressed as an aspect of learning
potential. Her results demonstrated the applicability of
this form of testing for children in primary school and in
special schools.
2.4.5 A ~CONTINUUM OF ASSESSMENT SERVICES" MODEL
Burns, Haywood, Delclos, and Siewert (1987), Tzuriel and
Klein (1987) and Vye et al. (1987) used this model which
incorporates the mediational aspects of the LPAD and the
graduated prompting of Campione and Brown (1987). The
Continuum of Assessment technique involves the
administration of a static measure followed by graduated
prompting procedures. If the child performs below a certain
criterion, (s)he is then provided with mediation using
brief, standardised scripts. Mediation involves
metacogni tive skills such as planning and monitoring but
uses brief, scripted instructional procedures. The mediation
phase of the continuum model includes:
• Familiarisation with the task materials. This involves
the direction of the subject's attention to the relevant
dimensions.
• Teaching specific rules and procedures necessary for
completion of the task.
• Allowing the subj ect to practice on assessment items and
giving elaborated feedback on performance.
The nature of the prompts given during mediational
assessment is contingent upon the child's performance,
whereas in the graduated prompting method the prompts are
37
based on task analysis and arranged from general to
specific.
Proponents of Feuerstein's (1979) model would argue that
standardised scripts do not allow for individualisation of
the process and relevant information may be lost. Although
this is true, standardised mediational approaches overcome
many of the difficulties associated with the LPAD (e.g.
extensive input by trained examiners, sUbjectivity of
inferences made during testing, and lack of standardisation
of procedures) .
Burns et al. (1987); Tzuriel and Klein (1987) Vye et al.
(1987) have used this model for research purposes and as an
assessment technique with pre-school children, middle school
children and with disabled subj ects. The mediation method
appears to lead to greater generalisation than graduated
prompting.
2.4.6 TRAIN-WITHIN-TEST
The train-within-test paradigm has neither pre-test nor an
explicit training phase. Training is an integral part of the
test and consists of increasing help according to the needs
of the child. This avoids the problematic issue of change
measurement (Hessels, 1996).
The Learning Potential Test for Ethnic Minorities (LEM) was
developed by Hamers, Hessels, and Van Luit (1991) to
estimate the general cognitive abilities of minority
children. Before testing the child is given extensive
practice to become acquainted with the testing materials and
situation.
38
Training is standardised and consists of repeating items,
non-verbal feedback (i. e. right/wrong information) or
demonstration, depending on the task. The hints are not
hierarchically structured; help is given depending on the
needs of the specific learner. All instructions are non
verbal, the child is taught through demonstration and
practice. This allows for testing children with poor
language proficiency. Hamers et al. (1996) found that the
LEM reduced the di fferences in mean test scores between
Dutch, Turkish and Moroccan subjects. In addition, children
with low intelligence test scores could be differentiated
into low, medium or high scorers on the learning test. This
implies that many children benefit from the learning
potential procedure and that many "false-negatives" could be
discerned.
other learning potential batteries for ethnic minorities
using a similar model have been developed in the United
Kingdom. Coxhead and Gupta (1988) developed the Learning
Efficiency Test Battery based on a demonstration, practice,
testing procedure. Hegarty (1979) developed the Test of
Children's Learning Ability using a teach, practice, test,
teach, test procedure.
These models are all subsumed under the heading of dynamic
assessment because they all link assessment and instruction.
There are, however, significant differences in their
theoretical orientation, purpose of assessment, types of
skills assessed, types of tasks used, the nature of the
interaction between examiner and subject, and quantity and
quality of empirical support they command.
39
Researchers using these different models (Budoff, 1987b;
Burns et al., 1987; Guthke, 1993; Hessels, 1996; Kahn &
King, 1997; Rutland & Campbell, 1995;) generally report that
dynamic assessment leads to more accurate prediction and
classification of individual subjects than the unaided test
scores.
2.5 EMPIRICAL FINDINGS
Very few empirical studies directly related to this research
project have been found in the available literature. There
is, however, a growing body of evidence from research in
both educational and personality psychology that indicates
individual differences in learning ability cannot be
explained solely as a result of a general intellectual
ability. There appears to be a complex and dynamic
interaction between cogni tive, affective and motivational
factors that influences learning (Volet, 1996).
2.5.1 LEARNING AND COGNITIVE FACTORS
Empirical results of intelligence-related differences in
learning have often been contradictory. Early empirical
studies reported low or insignificant correlations between
intelligence and learning (Brown & Ferrara 1980; Campione &
Brown, 1984; Vye et ale 1987). However, later studies
contradicted these findings. Campione et al. (1985) found
that mentally retarded children learned as fast as average
children, but they needed more hints to transfer and were
less likely to maintain strategy use. Correct responses in
this study required children to apply a single rule to the
problem. Ferrara et al. (1986) found that when the task
required the simultaneous application of two rules, average
40
children needed more hints to learn the rules than above
average children, and more hints to transfer these rules to
other tasks.
These contradictory results may be explained by the
methodological differences in the studies. In the Campione
et ale (1985) study the subjects were matched according to
their mental age, Ferrara et al. (1986) did not match her
subjects before the testing. When the task was easier (the
application of one rule as opposed to two) and the pre-test
performance was equated across groups, intelligence was not
related to learning.
Ferretti and Butterfield (1992) reported that insignificant
differences were found when the subjects did not need to co
ordinate multiple sources of information. However, once the
task required the simultaneous co-ordination of more than
one dimension, intelligence-related differences were
evident. These results suggest that the difficulty of the
task has some influence on intelligence-related differences
in learning.
Budoff (1987a) found that higher scores on non-verbal or
minimally verbal tests, such as the WISC Performance scale
and Raven Progressive Matrices were associated with better
learning potential scores.
These results suggest that intelligence-related differences
in learning ability may be found in both the RSPM and the
CCFIT. Both these tests are non-verbal and although the
earlier problems can be solved using one rule, the problems
become progressively more difficult.
41
See Chapter 3 for a discussion of Ravens Progressive
Matrices and Cattell's Culture Fair Tests.
2.5.2 LEARNING AND PERSONALITY
Budoff and his associates (Budoff & Pines, 1971; Harrison &
Budoff, 1972a, 1972b; Harrison, Singer, Budoff, & Folman,
1972) examined the effects of personality factors on
learning potential scores. They found that subjects
classified as gainers showed the following characteristics
(Budoff, 1987a):
• A greater sense of personal adequacy;
• Greater flexibility on a concept shift task;
• More flexibility and the ability to delay response;
• The ability to manage frustrations more effectively;
• Saw themselves as less neurotic or maladjusted and
• Set their aspiration levels more realistically even under
stress of failure.
Guthke and Lehwald (1980) found that the personality
characteristic 'fear' did not have a differential effect on
pre-test or post-test results. Sensi tivi ty to stress and
frustration tolerance was stronger during the pre-test than
during the post-test. They postulate that getting used to
the task helped to minimise these effects. Neuroticism was
found to have a greater effect on traditional tests and
long-term learning tests than short-term learning tests.
These findings are not directly related to the personality
traits measured using the High School Personality
Questionnaire (HSPQ). However, the relationship between
42
personality and learning has been well-documented in
educational and personality psychology.
Many researchers have used the ~Big Five" i.e. extraversion,
agreeableness, conscientiousness, emotional stability and
intellect, (Costa & McCrae, 1992i Goldberg, 1990; 1993) to
study the relationship between personality traits and
learning or academic achievement. The results of these
studies may be summarised as follows:
• The correlation between Extraversion and learning appears
to be age-related. There is a positive correlation
between this dimension and school achievement among pre
adolescents. This relationship appears to decrease with
age so that at student levels the relationship is
inverted (De Raad & Schouwenburg/ 1996; Eysenck/ 1996).
This dimension is similar to the second-order factor
Extroversion, which is calculated from various scores,
measured on the HSPQ.
• Agreeableness is concerned with interpersonal
relationships and as such this dimension is not generally
included in studies examining the relationship between
personality and learning. De Fruyt and Mervielde (1996)
found that this factor was not correlated with
educational outcomes. Factor A in the HSPQ measures the
extent to which the individual fits in socially and is
closest to this dimension.
• Conscientiousness has consistently been found to have a
positive effect on learning and academic achievement (De
Fruyt & Mervielde, 1996; De Raad & Schouwenburg / 1996 i
Johnson & Bloom/ 1995). De Fruyt and Mervielde (1996)
maintain that Conscientiousness may be the non-cognitive
equivalent of the cognitive factor g, and part of the
43
variance in educational measures can be explained by this
variable. Visser et al. (1992) maintain that this factor
(Factor G in the HSPQ) correlates positively with
academic achievement.
• The correlation between Emotional Stability and learning
also appears to be age-related. The correlation between
Neuroticism and low achievement becomes closer with
increasing age (De Raad & Schouwenburg, 1996; Eysenck,
1996). De Fruyt and Mervielde (1996) found that the
relationship between Neuroticism and low achievement was
only significant for males. The factors that contribute
to anxiety (+D, +0, +Q4, -C, -G, -H, -Q3), a high score on
Factor I and low scores on Factor E and F contribute to
the measurement of neuroticism on the HSPQ (Smit, 1991).
• The factor variously called Intellect, Imagination or
Autonomy includes such concepts as the need for cognition
(Cacioppo, Petty, Feinstein & Jarvis, 1996), intellectual
engagement and the desire to be reflective and thoughtful
(Sternberg, 1996). Studies related to the correlation
between this trait and learning or academic achievement
have yielded conflicting results. Goff and Ackerman
(1992) found this trait to be unrelated to academic
achievement. Low correlations were reported by Cacioppo
et ale (1996) whereas Blickle (1996) found that this
trait predicts educational success. De Fruyt and
Mervielde (1996) found this factor to be moderately
negatively correlated for females. None of the factors in
the HSPQ measure this trait directly. One aspect of this
trait - Abstract Thinking (Factor B) is measured using
the HSPQ.
De Raad and Schouwenburg (1996) have described the ideal
student as self-controlled, self-confident, tolerant,
44
mature, diligent, well organised, resourceful, methodica~
and persevering. Most of these characteristics are included
in Factor G of the HSPQ (diligent, well organised,
methodical, and persevering). The other characteristics do
not fit those measured by the HSPQ exactly but are related
in some respects to various factors. For example, Q3
emphasises self-control, -0 measures self-confidence,
tolerance is part of Factor A, maturity is found in Factors
A and C, and resourcefulness in Q2.
Anxiety is a second order factor of the HSPQ. Although high
anxiety is consistently associated with poor academic
achievement (Gaudry & Spielberger, 1971; Sarason & Sarason,
1990) the correlations are generally low, in the order of
0.10 - 0.20 (De Raad & Schouwenburg, 1996).
Although the definitions of these constructs do not overlap
exactly with the definitions of the factors measured using
the HSPQ, these results may give some indication of whether
these traits could effect learning potential tests. If these
results were extrapolated to the current research the
following results would be expected:
• Extraversion, Anxiety (second order factors), Factor
+1 (tender-mindedness), Factor -E (submissiveness)
and Factor -F (soberness) may be uncorrelated or be
slightly negatively correlated to learning potential
scores.
• Factors A (outgoing), C (emotional stability), -0
(self-assurance), Qz (self-sufficiency), and Q3 (high
self-sentiment integration) may show positive
correlations to learning potential.
45
• Factor G (conscientiousness) should be positively
related to learning potential.
• Reported results for Factor B (abstract thinking)
are inconclusive.
No studies related to the other factors in the HSPQ have
been found.
See Chapter 3 for a discussion of the factors measured using
the HSPQ.
2.5.3 LEARNING AND MOTIVATION
De Raad and Schouwenburg (1996) maintain that the
di stinction between personality traits and motives may be
merely theoretical since both are dispositional in nature.
Motivation is distinguished by an element of striving.
Different concepts have been dominant at various times in
research related to motivation and learning. Need for
achievement and fear of failure have been replaced by
extrinsic and intrinsic motivation, locus of control and
goal orientation (Boekaerts, 1996).
Very little research dealing directly with the motivational
aspects of the Picture Motivation Test (PMT) could be found.
However, results that focus on some of the aspects measured
on the PMT may suggest possible outcomes of this research.
The majority of studies with regard to learning and
motivation emphasise the Need for Achievement. The
achievement motive has been positively related to
persistence, task performance and grades at school (Carver &
46
Scheier, 1992). The PMT measures both Scholastic Achievement
and General Achievement. Du Toi t (1983b) found that these
factors, plus Cognitive Structure, Endurance, Understanding
and Order contributed to an achievement factor. Aggression
loaded negatively on this factor. Motti-Stefanidi, Besevegis
and Giannitsas (1996) found disruptive and aggressive
behaviour to be related to poor academic achievement.
Cacioppo et al. (1996) reported low posi tive correlations
between a 'need for cognition', defined as a tendency to
engage and enjoy cognitive endeavours, and academic
achievement. This factor resembles the definition of the
Understanding aspect of the PMT.
Romine and Crowell (1981) characterised achievers as
hardworking, consistent, organised, with the need to excel
academically. These factors resemble Scholastic Achievement,
Endurance, Achievement and Order on the PMT.
Ames (1984) and Dweck (1986) found that subjects who enjoyed
exerting effort and were persistent, were less hampered in
the acquisi~ion of intellectual skills than those who
displayed the opposite pattern were. These two concepts are
similar to Understanding and Endurance on the PMT.
Three aspects measured using the PMT Affiliation,
Exhibi tion and Play are concerned with social interaction.
No empirical research relating to these needs has been
found.
From these results the following outcomes may be
hypothesised:
47
• Cognitive structure, Scholastic Achievement, Endurance,
Understanding, Order and General Achievement may be
positively related to learning.
• Aggression may be negatively correlated to learning.
See Chapter 3 for a discussion of the motivational aspects
measured using the PMT.
2.5.4 LEARNING AND LEARNING STYLES
The proliferation of instruments to measure learning and
cognitive styles is evidence that enhancing learning by
matching teaching and learning styles is an intriguing
prospect for educators (Rayner & Riding, 1997). However,
Curry (1991) argues that the systematic operationalisation
of learning styles continues to be susceptible in three
areas:
(1) confusion in definitions;
(2) weaknesses in reliability and validity of
measurement;
(3 ) identification of the most style-relevant
characteristics in learners and instructional
settings.
Although the Honey and Mumford (1982) Learning Styles
Questionnaire (LSQ) is widely used, especially in the U.K.,
very little empirical evidence of its predictive validity is
available (Sadler-Smith, 1997).
Sadler-Smith and Riding (1999) failed to confirm the LSQ's
hypothesised structure and Allinson and Hayes (1988) found
little support for the predictive validity of the LSQ.
48
Allinson and Hayes (1988) maintain that although the utility
of the LSQ has not been completely verified, the LSQ was
able to distinguish similar cognitive dimensions in two
independent samples; the distribution of scores is close to
what might be expected theoretically; and it has good face
validity.
A number of studies have been conducted comparing the LSQ to
personality measures. Furnham (1996) and Jackson and Lawty
Jones (1996) examined the relationship between the LSQ and
the Eysenck Personality Questionnaire (EPQ). They reported
high correlations between Extraversion and an Activist and
Pragmatist learning style. Extraversion was negatively
correlated to the Reflective learning style. These
correlations were so high that Furnham questioned the
necessity of measuring learning styles. Eysenck (1996)
maintains that personality measures and learning styles are
not independent and the LSQ needs considerable improvement.
Despite these results, learning styles continue to be viewed
as an important element of the learning situation. For
example, Sternberg (1996) states that flexibility in the use
of styles is positively associated with academic
achievement. These empirical results do not give an
indication of what may be expected from this research.
However, from a theoretical perspective, matching the
learning style with the teaching style should aid learning.
The hypothesis would then be that pupils with a Theoretical
learning style should be at an advantage during the learning
phase of this research.
49
2.6 LIMITATIONS OF THE EXISTING LITERATURE ON DYNAMIC
ASSESSMENT
Despite the merits of dynamic assessment, these techniques
do have limitations. Various researchers discuss the
following limitations:
• Construct Fuzziness: It is difficult to evaluate a set of
assumptions which partially overlap and have developed
over a period of almost 30 years with at least five
distinct models differing in definition, theoretical
foundations and procedural requirements. For example, the
graduated prompting model views learning as taking place
in a social context whereas testing-the-limits views
learning as contingent upon personality factors and
cogni tive ability. Inadequacies in some definitions of
the concepts wi thin particular models make it difficult
to draw conclusions about various techniques. For
example, the cogni tive functions in Feuerstein's (1979)
LPAD are not related to one another by a consistent
theory of cognitive functioning. These functions also
overlap and are defined on different levels (Buchel &
Scharnhorst, 1993; Jitendra & Kameenui, 1993).
• Procedural Spuriousness: Most of the empirical testing
and authentication of techniques used in dynamic
assessment are carried out by the original creators. It
is difficult to evaluate their claims with no
corroborating evidence. Savell, Twohig and Rachford
(1986) argue that the statistical significance of
resul ts, the selection of dependent variables and the
differences in the training of instructors makes it
difficult to assess research results.
50
• Instrument Inadequacy: Models such as testing-the-limits
and Budoff's (1974) test-train-retest technique
incorporate instructional strategies into traditional
ability tests. The LPAD and the continuum of assessment
models require examiners to make high-level inferences,
which may lead to arbitrary results. Assessment
instruments have not been designed to cover the diverse
academic content areas (Jitendra & Kameenui, 1993)
• Lack of standardisation of test administration: Although
many of the models of dynamic assessment are
standardising the instruction, examiner effects such as
training and personality may influence the interaction
between the examiner and examinee (Buchel & Scharnhorst,
1993) .
• Labour Intensiveness: Because of the inordinate amount of
time it takes to assess subjects using the individualised
techniques of most of these models, implementing dynamic
techniques on a wide scale is not feasible. Group
measures have not been widely tested, so it is too early
to evaluate their efficacy. The use of computers in
dynamic assessment is a promising avenue that needs
development (Guthke & Stein, 1996).
• The role of cognitive ability: Contradictory results have
been reported concerning the effect of cognitive ability
on learning potential and transfer scores. Task
difficulty and amount of verbalisation required in the IQ
test appears to play a role (Campione et al., 1985;
Ferrara et al., 1986).
• The role of non-intellective factors: Although many
researchers suggest that the role of non-cognitive
factors is important in dynamic testing (Feuerstein,
1979; Ruijssenaars et al., 1993; Tzuriel, 1992) very
little research has been conducted in this area.
51
• The measurement of change: The evaluation of change is
central to all dynamic assessment approaches. Using
simple or residualised gain scores has been criticised on
the following grounds:
(a) The ability to solve problems may change both
quantitatively and qualitatively. Should this be the
case, the pre-test and post-test would measure
different abilities (Schottke et al., 1993).
(b) The effects of intervention and re-testing are
difficult to separate (Klauer, 1993).
(c) Gain is a function of the level attained in the pre
test (Guthke, 1993).
(d) The reliability of difference scores is lower than
the reliability of the pre-test scores and post-test
scores (Boeyens, 1989).
Notwithstanding these limitations, results of many of the
studies discussed above support the view that learning
potential is a viable construct and that dynamic assessment
does address many of the criticisms of traditional testing.
Dynamic assessment appears to hold promise for improving the
predictive a8d prescriptive features of static testing.
2.7 THE PRESENT RESEARCH PROJECT IN VIEW OF THESE
PURPORTED LIMITATIONS
Not all the limitations listed above can be addressed in
this research proj ect. However, the following issues form
the basis of this research:
• The assessment procedures are all group administered. The
training phase takes approximately one hour and is
presented on video. This does away with the need for
52
highly trained instructors, time-consuming assessment and
circumvents the problem of different levels of training.
• The test-train-retest format used in this project is
based on the theories of Vygotsky (1978) operationalised
by Luria (1961) and widely researched by Budoff (1987a).
The aim is to establish whether short-term, standardised
cognitive tests can result in gains.
• The video features an instructor demonstrating how to
solve the problems in Set Variations 1. The instructions
follow the format presented in the manual of Feuerstein's
LPAD.
• Cognitive ability will be measured using non-verbal tests
that require the simultaneous co-ordination of more than
one source of information. Higher scores in this
situation have been associated with better learning
potential scores (Budoff, 1987 a; Ferretti & Butterfield,
1992) .
• Personality, motivation and learning styles are measured
wi th instruments that have been widely used. The
instruments measure a broad spectrum of traits, many of
which have been researched in psychology, but not in
dynamic assessment. The role of these factors on transfer
ability will also be examined.
• Gain scores will be used since this research does not aim
to improve the predictability of the tests or to
categorise the subjects. The intention is to ascertain
which non-intellective factors have a bearing on learning
ability.
This research aims to address some of the inadequacies that
researchers have highlighted concerning dynamic assessment,
in particular the role of cogni tive and non- intellective
factors.
53
Chapter 3
RESEARCH METHODOLOGY
3.1 INTRODUCTION
The essential methodological components of this research
project are dealt with in this chapter. The following
elements are discussed:
• The statement of the problem
• The aims of the research
• The hypotheses
• The subjects
• The experimental design
• The procedures that were followed
• The instruments used
• The analysis of the data.
3.2 STATEMENT OF THE PROBLEM
In light of the time and expertise required, the
incomparability of scores, the lack of knowledge concerning
the examiner effects and the role of cognitive and non
intellective factors in dynamic assessment, this research
proposes to examine the following questions:
I. Whether a short, group administered dynamic assessment
procedure using a standardised intervention protocol
presented on video, is viable.
II. Whether current general intellectual ability has a
significant effect on learning potential scores.
54
III. Whether non-intellective factors such as certain
personali ty factors, motivational traits and learning
styles have significant effects on learning potential
scores.
IV. Whether transfer from pre-mediation to post-mediation
cognitive functioning is statistically significant.
3.3 THE AIM OF THIS STUDY
In this research the effects of the following factors on
learning potential scores are examined:
General cogni tive ability measured by Cattell's
Culture Fair Intelligence Test Form A (refer to
section 3.8.6).
Fourteen personality traits measured by the High
School Personality Questionnaire (refer to section
3.8.3) .
Ten motiva tional factors measured by the Picture
Motivation Tests (refer to section 3.8.4)
Four learning styles measured by the Learning
Styles Questionnaire (refer to section 3.8.5).
Learning potential scores are obtained from the difference
between the pre- and post-test scores on Raven's Standard
Progressive Matrices (refer to section 3.8.1). The training
phase is standardised according to a Theorist learning style
(refer to section 3.8.5) and is presented on video using
Feuerstein's Set Variations 1 as a mediation tool (refer to
section 3.8.2). Transfer performance is measured as the
difference between the pre- and post-test administration of
Cattell's Culture Fair Tests Forms A and B, respectively
(refer to section 3.8.6).
55
3 . 4 HYPOTHESES
From the literature review the following hypotheses are
posited. The rationale of the hypotheses follows after the
alternative hypothesis has been stated. The expected outcome
of a hypothesis will be indicated by means of an asterisk to
the left of the relevant hypothesis.
Hol : A standardised teaching intervention by means of a
videotape has no effect on Learning Potential scores (as
measured by the difference between the pre-intervention and
post-intervention scores obtained on the Raven's Standard
Progressive Matrices) .
*Hal: A standardised teaching intervention by means of a
videotape increases Learning Potential scores (as measured
by the difference between the pre-intervention and post
intervention scores obtained on the Raven's Standard
Progressive Matrices) .
Rationale
Individual administration of dynamic assessment tests is
both time and labour intensive (Boeyens, 1989). The need
for improved standardisation has also been emphasised by
various researchers (Buchel & Scharnhorst, 1993; Savell et
al., 1986). This hypothesis is aimed at testing whether a
short, standardised teaching intervention can, in fact, lead
to a gain in scores.
Ho2 : There is no statistically significant practice effect
between the pre- and post-test scores of the Raven's
Standard Progressive Matrices.
56
*Ha2: There is a statistically significant practice effect
between the pre- and post-test scores of the Raven's
Standard Progressive Matrices.
Rationale
Both Anastasi (1990) and Klauer (1993) argue that test
scores obtained from a re-testing with an identical form of
a test may be suspect. They maintain that certain items may
be easier on second presentation and that the subjects may
employ different methods in solving the problems. In order
to ensure that practice effects did not contaminate learning
potential scores, half of the experimental group and half of
the control group did not do a pre-test.
Ho3 : Personality factors as measured by the High School
Personality Questionnaire (HSPQ) are not significantly
related to learning potential scores (as measured by the
difference between the pre-intervention and post
intervention scores obtained on the Raven's Standard
Progressive Matrices)
*Ha3: Personality factors as measured by the HSPQ are
significantly related to learning potential scores (as
measured by the difference between the pre-intervention and
post-intervention scores obtained on the Raven's Standard
Progressive Matrices) .
Rationale
A number of authors have discussed the effects of
personality factors on learning and educational outcomes
(Anastasi, 1990, Boekaerts, 1996; De Raad & Schouwenburg,
1996; Sternberg, 1996.) The general consensus is that
personality factors play a dominant role in behaviour
57
including learning, educational achievement and test-taking.
The High School Personality Questionnaire measures 14
personality factors regarded by Cattell (1980) as the most
important traits in personality structure and functioning in
adolescents. This hypothesis is based on questions about the
relevance of personality factors in dynamic assessment.
Ho 4 : Motiva tional traits as measured by the Picture
Motivation Tests (PMT) are not significantly related to
learning potential scores (as measured by the difference
between the pre-intervention and post-intervention scores
obtained on Raven's Standard Progressive Matrices).
*Ha4: Motivational traits as measured by the PMT are
significantly related to learning potential scores (as
measured by the difference between the pre-intervention and
post-intervention scores obtained on the Raven's Standard
Progressive Matrices) .
Rationale
Atkinson (1980) and McClelland, Atkinson, Clark and Lowell
(1976) assert that the relationship between true ability and
the influence of affective factors, such as motivation, are
not clearly understood in classical psychometric theory.
The basis for this hypothesis is clarification of this
variable as it affects learning potential.
Hos : The learning styles of adolescents as measured by the
Learning Styles Questionnaire (LSQ) are not significantly
related to learning potential scores (as measured by the
difference between the pre-intervention and post
intervention scores obtained on the Raven's Standard
Progressive Matrices)
58
*Has: The learning styles of adolescents as measured by the
LSQ are significantly related to learning potential scores
(as measured by the difference between the pre-intervention
and post-intervention scores obtained on the Raven's
Standard Progressive Matrices) .
Rationale
Furnham (1992) and Honey and Mumford (1982) maintain that
matching learning and teaching styles can lead to more
effective learning. When administering learning potential
tests to groups, the teaching style may affect the
efficiency with which the subjects learn.
Ho6 : The general cognitive ability pre-test scores (as
measured by Cattell's Culture Fair Intelligence Test, Scale
2, Form A), are not significantly related to the subject's
learning potential scores (as measured by the difference
between the pre-intervention and post-intervention scores
obtained on the Raven's Standard Progressive Matrices).
*Ha6: The general cognitive ability pre-test scores (as
measured by Cattell's Culture Fair Intelligence Test, Scale
2, Form A), are significantly related to the subject's
learning potential scores (as measured by the difference
between the pre-intervention and post-intervention scores
obtained on the Raven's Standard Progressive Matrices).
Rationale
Empirical results of intelligence-related differences in
learning potential scores as defined in this hypothesis have
often been contradictory. Brown and Ferrara (1980), Campione
and Brown (1984) and Vye et al. (1987) reported low or
insignificant correlations between intelligence scores and
59
learning potential scores. However, Budoff (1987a), Ferrara
et al. (1986) and Ferretti and Butterfield (1992) found
statistically significant correlations between these
variables. The contrasting results may be explained by the
different tasks used in these studies. When the subj ects
were required to learn to apply a single rule, intelligence
related differences were not found. However, when strategies
required the simultaneous application of two rules,
intelligence-related differences were found.
This hypothesis is based on the question of whether the
subjects' performance on IQ tests will determine their
ability to learn during dynamic assessment.
Ho7 : The standardised teaching intervention by video, using
Feuerstein's LPAD Set Variations 1 as a mediation tool, has
no effect on transfer scores (as measured by the difference
score between Cattell's Culture Fair Intelligence Test,
Scale 2, Form A and Form B) .
*Ha7: The standardised teaching intervention by video, using
Feuerstein's LPAD Set Variations 1 as a mediation tool,
improves transfer scores (as measured by the difference
score between Cattell's Culture Fair Intelligence Test,
Scale 2, Form A and Form B) .
Rationale
Campione (1989) maintains that the flexible transfer to new
situations of insights and other skills learned during
dynamic assessment, are the most important indications that
learning has taken place. The ability to transfer the skills
acquired in Set Variations 1 (used for cognitive mediation
purposes) to Cattell's Culture Fair Intelligence Test
60
(CCFIT) can therefore be seen as an indication of how
successful cognitive reorganisation by means of the
standardised intervention is. An increase of scores from the
CCFIT Form A to the CCFIT Form B after cognitive mediation
will indicate that real learning has taken place.
Hos : The learning potential scores (as measured by the
difference between the pre-intervention and post
intervention scores obtained on the Raven's Standard
Progressive Matrices) are not significantly correlated to
the transfer gain scores (as measured by the difference
between Cattell's Culture Fair Intelligence Test Form A and
Form B) .
*Haa : The learning potential scores (as measured by the
difference between the pre-intervention and post
intervention scores obtained on the Raven's Standard
Progressive Matrices) are significantly posi tively
correlated to the transfer gain scores (as measured by the
difference between Cattell's Culture Fair Intelligence Test
Form A and Form B) .
Rationale
Bryant (1982) and Bryant, Brown, and Campione (1983) found
that learning potential scores were better predictors of
transfer scores than ~static" ability scores. This
hypothesis will establish whether the gain scores obtained
from the transfer tests were compromised by re-testing using
a parallel form of the test (See rationale for Ho 2 ) •
61
3.5 SUBJECTS
All the students in Grade 10 of a Johannesburg high school,
who receive their instruction in English, were tested. A
total of 120 students completed all the tests. The school
was originally designated a "Coloured" school, but is now
catering mainly to the Black population. The intention
initially was to restrict the sample to Coloured children in
order to control both cultural diversity and language
proficiency problems. Most of the Coloured pupils attending
an English medium school would probably speak English at
home. This would not be the case for Black children. Using a
sample from the Black population means that the pupils come
from diverse cultural backgrounds with different home
languages (refer to Table 3.3). One or more of the problems
associated with cross-cultural assessment (refer to Chapter
2, section 2.1) could contaminate the results of the tests
administered to this group. The demographic breakdown is:
TABLE 3.1
SEX
! SEX NUMBER PERCENTA~
MALES 53 44,2
FEMALES 67 55,8
TOTAL 120
The sample has slightly more females than males.
62
TABLE 3.2
AGE
YEARS
14
NUMBER
12
PERCENTAGE -
10,0
f-----
15
16
31
28
25,8
23,3
f--
f-----
17
18
19
31
13
3
25,8
10,8
2,5
f---
20
21
1
1
0,8
0, 8
TOTAL 120 ~
Most subjects are between 15 and 17 years of age. As may be
expected in a disadvantaged community, the distribution of
Grade 10 subjects is right-skewed in terms of typical age
for their grade.
TABLE 3.3
HOME LANGUAGE
LANGUAGE FREQUENCY PERCENTAGE ~
ZULU 45 37,5
SETSWANA 21 17,5
SESOTHO 14 11,7
SEPEDI 12 10,0
XHOSA I----
11 9,2
ENGLISH 8 6,7 ~
VENDA 4 3,3
AFRIKAANS 2 1,7
TSONGA 2 1,7
SESWATI 1 0,8
r-rrOTAL 120
63
The majority of the subjects speak Zulu, with small
representations from many other languages.
3.6 EXPERIMENTAL DESIGN
A Solomon Four-Group design was chosen for this research
(Kerlinger, 1986).
Figure 3.1
THE SOLOMON 4-GROUP DESIGN
GROUP 1 GROUP 2 GROUP 3 GROUP 4~
EXPERIMENTAL Experimental CONTROL Control
GROUP 1 Group 2 GROUP 1 Group 2 r-- Pre-test No Pre-test Pre-test No Pre-test
Mediated Mediated No lesson No lesson
Lesson Lesson
Post-test. Post-test Post-test Post-test
N = 30 N = 30 N = 30 N = 30 -
This design was chosen because the experimental and control
groups can be compared on the basis of whether they
benefited from mediation or not. The sensitising effects of
pre-testing are controlled by only pre-testing Experimental
Group 1 and Control Group 1. If no sensi tising effect has
occurred, a comparison of Experimental Group 1 (wi th pre
test) and Experimental Group 2 (no pre-test) should be
insignificant, as should a comparison between Control Group
1 (with pre-test) and Control Group 2 (no pre-test). If the
differences between these groups are significant,
Experimental Group 2 (no pre-test) and Control Group 2 (no
pre-test) will need to be compared. Control Group 2 also
64
limits the effects of temporary coincidental events that may
have occurred between the pre-test and the post-test
(Kerlinger, 1986).
The subjects were randomly assigned to the experimental and
control groups as all the pupils had to be involved in the
research in some way, according to the prerequisites of the
school. The groups can therefore differ in composition.
3. 7 PROCEDURES
The assessment procedure was administered in three phases.
During the first and third phases, space constraints
necessitated that the subjects were tested in two separate
venues since more than 120 pupils were being assessed
simultaneously.
3.7.1 THE INITIAL TESTING PHASE
All the subjects completed the following tests, which were
only applied once:
I. The Learning Styles Questionnaire (Honey & Mumford,
(1982) .
II. Cattell's Culture Fair Intelligence Test Scale 2 Form A
(Cattell & Cattell, 1959b).
III. The High School Personality Questionnaire (Cattell &
Cattell, 1973).
IV. The Picture Motivation Test (du Toit, 1983a).
65
3.7.2 THE EXPERIMENTAL PRE-TEST PHASE
One week later, during the pre-test phase, the Raven's
Standard Progressive Matrices (Raven, 1976) were
administered to half of the Experimental and half of the
Control groups. These subjects were randomly chosen from the
experimental and control groups. The whole Experimental
Group then completed the LPAD Set Variations 1 (Feuerstein,
1979), with the lesson being administered by means of a
videotape shown on a television screen. Set Variations 1
consists of a series of five analogical reasoning tasks,
e.g. A is to B, as C is to D. Each series contains a model
task with six variations. The model task was mediated
according to the instructions for the group administration
of the test. The subjects then practised what they had been
taught using the six variations of the task in that series.
A total number of 30 tasks had to be completed for all five
series. No dummy lesson was given to the control group since
the school did not want the pupils to miss more classes than
was strictly necessary. They were therefore only expqsed to
the usual teaching experiences in the school setting, as
well as random life experiences outside the school setting.
3.7.3 THE EXPERIMENTAL POST-TEST PHASE
One week later during the post-test phase Raven's
Progressive Matrices were administered again, this time to
all the subjects.
•Cattell's Culture Fair Intelligence Test, Scale 2, Form B,
the transfer test, was administered to all the subjects one
week later.
66
3.8 INSTRUMENTS
3.8.1 RAVEN'S STANDARD PROGRESSIVE MATRICES
The Standard Progressive Matrices (RSPM), developed in Great
Britain by Raven, were designed to measure eductive ability.
Eductive ability is one of the two main components
underlying general intelligence or g in Spearman's (1927)
theory of cognitive ability. It includes the ability to:
• perceive accurately and give attention to detail,
• forge new insights,
• identify relationships,
• perceive what is not always immediately obvious,
• generate new, largely non-verbal concepts which make
it possible to think clearly, and
• Make meaning out of confusion.
Eductive ability remains latent, develops later in life and
declines earlier in old age when the environment does not
satis fy the needs and motives necessary for the child or
adult to achieve or sustain eductive ability. The abilities
measured in this test are built on top of one another; it is
generally not possible to solve the more difficult problems
before being capable of solving the easier ones (Raven,
Court & Raven, 1992).
The scale consists of five Sets (A - E), each containing 12
problems. Each matrix has a part that is missing; the
subject has to choose the correct insert from six or eight
alternatives. The first item in each set is almost self
evident, the problems becoming progressively more difficult,
but still continuing to use the same principles as the
67
earlier problems. The first items in each set provide a form
of training in the method needed to solve the problems. The
five sets provide five opportunities to understand the
method of thought needed to solve the problems and five
progressive assessments of the subject's ability. The
earlier sets require accuracy of visual discrimination,
while the later more difficult sets involve analogies,
permutations and alternations of patterns. There is no time
limit. A person's total score provides an index of
intellectual capacity.
Standardisation
Since the development of the Standard Progressive Matrices
in the mid-1930's extensive norms have been collected in
various parts of the world, including Britain, Ireland,
Germany, New Zealand, Australia, Czechoslovakia, Canada,
China and Belgium. The British standardisation of 1979
confirmed suggestions that there was an increase in SPM
scores from the earlier standardisation samples. The 1979
standardisation also yielded the following findings (Raven
et al., 1992)
• There are no sex differences in the scores obtained
on the SPM except at age 11 ± six months.
• Only 9% of the within-age variance is explained by
social background.
• As in the 1939 and 1972 standardisation, the test
works - ~scalesn - in the same way for children from
different socio-economic status backgrounds.
• Once items become too difficult for children, they
get the item right less often than would be expected
by chance. Their responses are, therefore, not
68
"random", but guided by hypotheses albei t wrong
hypotheses.
In 1984/86 the test was standardised for particular school
districts throughout America. The norms varied with the
ethnic and socio-economic composition of the district and
its geographical location. The test does, however, scale the
same way in each ethnic group and has similar predictive
validity. Owen (1991) found that the RSPM was suitable for
use with four population groups (Black, Whites, Coloureds
and Indians), even though the means differed considerably.
__t-J_o ll.0rms are available for the different ethnic groups in
South Atrica; it was therefore necessary to use raw scores
in this res_ea:rl:::h rather than rely on norms that are not
suitable for the population group. The RSPM contains an
internal consistency check between responses, in order to
determine whether guessing and other random responses
dominated the subject's response patterns, or whether
correct responses could be accepted as a valid reflection of
ability.
Reliability
(a) Internal Consistency
Correlations between item difficulties established in the
UK, US, East and West Germany, New Zealand and China range
from 0,97 to 1,00. These correlations were established
separately for different ethnic groups and different socio
economic groups. The test therefore measures the same entity
in a wide range of cultural and socio-economic groups.
Split-half internal consistency coefficients for Britain and
North America range from 0,89 to 0,98. In other parts of the
69
world (Germany, Belgium, Iran, Korea, Taiwan, China,
Yugoslavia, Uruguay, and India) split-half reliability
coefficients ranged from 0,84 to 0,86 (Raven et al., 1992).
(b) Test-Retest Reliability
Test-retest reliability (temporal stability) studies differ
widely in methodology and intervals between test and retest,
which can range from 1 week to 11 years. Short-term temporal
stability is around 0,90 whilst longer intervals results in
a drop to approximately 0,80. Studies cited in Raven et al.,
(1992) indicate correlations between 0,78 and 0,92 for
intervals from 1 week to 3 years.
Validity
Correlations between the WISC-R and the RSPM range from 0,70
and 0,92. Correlations with verbal and vocabulary tests tend
to be lower, generally below 0,70.
Inter-test correlations for adult subjects between the RSPM
and WAIS range from 0,75 and 0,88. However, some
correlations in eros s-cul tural research tend to be lower.
More research is required in cross-cultural settings in
regard to concurrent validity.
Correlattons between RSPM and performance on achievement
tests are not as high as with intelligence tests, ranging
from 0,22 to 0,87. Correlations with school grades range
between 0,20 and 0,90. Validity estimates tend to be higher
when the criterion measures Maths and Science skills that
are predominantly non-verbal skills rather than language
skills.
70
Factor analytic studies reveal high loadings of up to 0,83
wi th g. Most studies have found a small group factor of
spatial ability but no loading with verbal-educational and
numerical ability factors (Raven et al., 1992).
The Effects of Training.
Budoff (1976), Feuerstein (1979) and Savell et al., (1986)
reported dramatic short-term increases in RSPM scores when
subjects have been taught strategies that are required to
solve the matrices. It is not clear whether these strategies
lead to a general increase in eductive ability or whether
the improvement is confined to the RSPM. Since Cattell's
CuI ture Fair Intelligence Test and Raven's Standard
Progressive Matrices were both constructed as measures of g
(Anastasi, 1990) the former test will be used to establish
whether any transference took place.
The RSPM was administered twice: once as a pre-test and
after intervention using the Set Variations 1 as a post
test. The difference between these scores is the Learning
Potential score.
The RSPM was used in this study because of its similarity to
Set Variations 1, which was used as a mediation tool. Both
consist of a series of matrix problems. In addition, it is
generally accepted as a valid and reliable instrument for
measuring g, due to its local and internationally
established research base (Raven et al., 1992, Owen, 1991).
71
3.8.2 FEUERSTEIN'S SET VARIATIONS 1
Set Variations 1 (Var.1) is part of the Learning Potential
Assessment Device developed by Feuerstein (1979). It is
suitable for group administration and is almost always
included in any battery using the Learning Potential
Assessment Device. Var.1 consists of a series of five
analogy tas ks (A - E). Each series contains one teaching
example followed by six variations that the subject
completes on his/her own.
The RSPM and the LPAD Var.1 have a very similar format. Each
problem is presented with a part missing; the subj ect is
required to choose the correct insert from eight
alternatives. In order to standardise the mediation process
so that all subj ects were given an equal opportunity to
learn the skills, the lesson was presented on video. The
teaching followed the instructions presented in the manual
on group testing using the LPAD Var.1 This method of
instruction is most sui ted to a Theorist Learning Style.
Contrary to the mediated lessons given using the LPAD there
was very little interaction between the examiner and the
subjects.
The mediated lesson focused attention on the following (LPAD
Set Variations 1 Manual, p. 6.33):
• Focusing: The subjects were made to focus on gathering
information e.g. pointing at items in the rows or
columns.
• Selection of stimuli and provision of stimuli: Items
were isolated so that they are clearly perceived and
then integrated again.
72
• Imitation: The video explained in detail how the task
could be solved by modelling and explaining the thought
processes involved.
• Verbal stimulation: The teacher on the video introduced
verbal labels (i.e. circles, ovals, squares etc.),
descriptions of transformations, rules and outcomes.
This allows for a more analytic, operational way of
thinking.
• Cause and effect relationships: In-depth explanations
of how the transformation has taken place in the rows
and columns are given.
• Orientation: Spatial position and direction of figures
and lines were described.
• Temporal orientation and sequencing: The order of the
sequence was emphasised (i . e . from left to right in the
rows and top to bottom in the columns) .
• Comparative behaviour: Given items were compared
minutely with each other.
• Inductive and/ or deductive reasoning: Inferences were
made about the rules governing the analogy and these
were then applied.
• Need for logical evidence and critical interpretation:
The alternative solutions were examined and accepted or
rejected on the basis of evidence.
• Need for precision at the input and output phase: The
video emphasised the need to examine each part of the
whole precisely with regard to orientation, direction,
relative location of content etc.
In reliability studies of the LPAD Var.1 Rand (1982, 1983)
found that the test consistently and systematically
discriminated between regular pupils and culturally deprived
73
pupils at a public school in Israel. Split-half reliability
coefficients ranged from 0,82 to 0,90.
Tzuriel and Rand (1983) examined the effects of differential
learning conditions using Set Variations 1 and 11. Using the
RSPM as a pre-test and post-test they found that groups who
received high-learning or low-learning interventions showed
raised performance levels on the post-test in comparison to
subj ects in the nonlearning group. Rand and Ben-Schachar
(1979) also found that subjects who received Set Variations
testing between two administrations of the RSPM showed a
statistically significant increase in their level of
performance on the RSPM post-test.
In this research the LPAD Set Variations 1 was used only as
a teaching tool and not as a test of the subject's ability.
Because of the similarity in kind and in the form of
presentation of the two tests, Variations 1 was used as a
mediated lesson to teach the skills necessary to solve the
matrix problems in the RSPM. It also fulfils the
requirements of a short lesson that can be presented on
video.
3.8.3 HIGH SCHOOL PERSONALITY QUESTIONNAIRE
The High School Personality Questionnaire (HSPQ) was
developed by Raymond and Mary Cattell (Cattell & Cattell,
1973). The aim was to fill the gap between the Sixteen
Personali ty Factor Questionnaire for adults and the
Personality Questionnaire for Children. The HSPQ gives a
personality profile for people aged between 12 and 18 years
of age.
74
Terms taken from psychology and psychiatry to describe
personali ty traits were subj ected to factor analysis and
resul ted In the identi fication of 14 primary personality
factors, which the HSPQ measures. Two second- order factors
have been identified. Each of these 14 primary factors is
represented by a letter of the alphabet and is scored on a
bipolar continuum. These factors, and the interpretation of
high and low scores are described by Visser, Garbers-Strauss
& Prinsloo (1992 pp. 23-34) as follows:
(1) Primary Factors:
FACTOR A
WARMHEARTEDNESS
LOW SCORE (-A)
RESERVED
Reserved, detached,
inflexible, aloof
Critical
Stands by personal ideas
Precise, objective
Distrustful, sceptical
Prone to sulk
Rigid
HIGH SCORE (+A)
OUTGOING
Warm-hearted, outgoing,
participating, attentive to
people
Good-natured, carefree,
uncritical
Prepared to co-operate, likes
to participate -
Soft-hearted, casual,
careless
Trusting
Laughs readily
Adaptable, accommodating
A high A score (+A) indicates a person who enjoys group
activities, is warm and easygoing and fits in socially.
People with a low A score (-A) tend to prefer working alone,
do not communicate easily and are introspective. They show
I
75
greater insight in their evaluations of people and things
and are more dependable in the long term.
FACTOR B
INTELLIGENCE .---------c----=-,--~------------ - -=-=~__=__--_c--:--------___,
LOW SCORE (-B) HIGH SCORE (+8)
CONCRETENESS ABSTRACT THINKING
Low mental capacity High general mental capacity
Unable to handle abstract Insightful, fast-learning,
problems intellectually adaptable, has
healthy intelligence
Factor B measures generalised intelligence and level of
abstract thought. This measure is not as reliable as those
obtained from longer intelligence tests.
FACTOR C
EMOTIONAL
LOW SCORE (-C)
EMOTIONAL INSTABILITY
Emotionally less stable,
influenced by emotions
Easily perturbed, changeable
Changeable in attitudes and
interests
Becomes confused easily
STABILITY
HIGH SCORE (+C)
EMOTIONAL STABILITY
Emotionally stable,
emotionally mature
Realistic, calm
Stable, constant in interests
Steadfast
Responsible, distinguishesEvades responsibilities,
between emotional needs andgives up easily
reali ty, adjusts to facts
Tends to worry Calm, unruffled
Gets into fights and problem Shows restraint in avoiding
situations problem situations
76
--
A low C (-C) score indicates a person who has difficulty in
controlling his/her emotions. They tend to have a higher
than average number of neurotic responses, vague health
concerns, digestive and sleep disturbances.
A high C score (+C) indicates an emotionally stable and
controlled person. Their behaviour appears calm and
rational. A high +C score is correlated with leadership.
FACTOR D
EXCITABILITY
LOW
Not r-Calm
SCORE (-D)
PHLEGMATIC TEMPERAMENT f------Reserved, controlled,
inactive, stodgy
Stoical, complacent, calm
Level-headed, deliberate
easily jealous
Unruffled, consistent
Self-effacing, diffident
HIGH SCORE (+ D)
EXCITABILITY
Demanding, overactive,
uncontrolled
Impatient
Excitable, overactive
Prone to jealousy ~
Shows signs of nervousness
Becomes easily confused
Self-assertive, self-
interested, egotistical
A high D score (+D) is associated with the rebellious
adolescent. They are restless sleepers, are easily
distracted and often get angry when they are reprimanded.
Although pleasant and affectionate they are often impulsive
and can be reckless.
77
FACTOR E
DOMINANCE
LOW SCORE (-E) HIGH SCORE (+E)
SUBMISSIVENESS DOMINANCE
Obedient, meek, easily Self-assertive, aggressive
influenced
Docile, accommodating, Competitive, self-assured
compliant I---
Submissive Arrogant, self-assured r--Dependent Independent
Considerate, diplomatic Stern, hostile
Conventional, conforming
Easily upset by authority
Unconventional, rebellious
Headstrong, disobedient -
Humble Demanding admiration
Al though people who score high on Factor E (+E) are often
disobedient and act independently. They also show initiative
and creativity.
In contrast, a low
submission, acceptance
respect for authority.
E score (-E)
of leadership
is associated
from others,
with
and
FACTOR F
CAREFREENESS
LOW SCORE (-F)
SOBERNESS
Introspective, quiet
Sober, silent
Serious, full of cares
Depressed, worried
HIGH SCORE (+ F)
CARE FREENESS
Talkative
Enthusiastic, unthinking,
impulsive
Unworried, careless, carefree
Cheerful values
78
LOW SCORE (- F)
SOBERNESS
Reserved, sticks to inner
values
Slow, caut ious
HIGH SCORE (+ F)
CAREFREENESS
Frank, expressive, reflects
the group
Lively, alert
A high F score (+F) is associated with extroversion. High
scorers tend to show initiative, express their emotions and
have many friends. Their work is often not thorough and they
have a tendency to act impulsively.
Low F scores (-F) are associated with introspection,
nervousness and tension. Their work is thorough, but they
are not popular. They are regarded as secretive and
daydreamers.
FACTOR G
CONSCIENTIOUSNESS
accept general moral
disregards
towards
LOW SCORE (-G)
OPPORTUNISTIC
Opportunistic
Does not
standards,
and obligations
others
Fickle
Frivolous
Self-indulgent
Slack, indolent
Undependable
rules
HIGH SCORE (+G)
CONSCIENTIOUSNESS
Dutiful, persevering,
moralistic
Concerned about moral
standards and rules
Consistent, persevering,
determined ~
Responsible
Emotionally disciplined
Orderly, conscientious
Dutiful
79
A high G score (+G) is associated with persistence,
determination and organised thinking. There is a tendency to
act according to accepted standards.
People who score
can have outbursts
law.
low on G (-G) tend to
of rage and in ser
disregard
ious cases
set
break
rules,
the
FACTOR H
SOCIAL BOLDNESS
LOW SCORE (-H)
SHYNESS
Shy, reserved, considerate
-
Feels threatened easily,
careful, quick to see danger
signals
Reserved, unsociable,
detached
Emotionally cautious
Modest in face of opposite
sex
Apt to be embittered
Controlled, rule-bound
HIGH SCORE (+ H)
SOCIAL BOLDNESS
Socially bold,
unrestrained
Carefree,
cheerful, does
Likes meeting people,
Participating, hearty
Overt, active interest i
opposite sex
Friendly
Impulsive
thick-ski-nned,
adventurous,
not see danger
jovial
n
A high H score (+H) is associated with talkative, jovial
individuals who like the limelight. They are popular but not
always sensitive to other people's feelings. They are often
more socially oriented than task-oriented.
A low H (-H) score indicates a shy, reserved, careful person
who does not express emotions easily. They are uncomfortable
in big groups even though they are considerate.
80
FACTOR I
TENDER-M1NDEDNESS
'LOW SCORE (- I)
TOUGH- MINDEDNESS
Unsentimental, realist view
Self-satisfied
Expects little of others
Independent, accepts
responsibility
Hard (to point of cynicism)
Few artistic responses (but
not lacking in taste)
Unaffected by ~whims"
r------
Acts on practical, logical
grounds
Does not dwell on physical
disabilities
HIGH SCORE (+ I)
TENDER-MINDEDNESS
Sensitive, dependent,
overprotected
Attention seeking, flighty ~
Fidgety, expecting affection
and attention
Clinging, insecure, seeking
help and sympathy
Kindly, gentle, indulgent, to
self and others
Artistically fastidious,
affected, theatrical
Imaginative in inner life
Acts on sensitive intuition
Hypochondriacal
People with high scores on Factor I (+1) are inclined to be
imaginative, artistic, impractical and disorganised. They
are fastidious, dependent, demand attention, are sensitive
and nervous. They tend to react emotionally and suffer from
headaches and nightmares.
Low I scores (-I) are associated with practical, down-to
earth people who have a mature attitude to life. Decisions
are made on practical grounds rather than emotionally.
81
FACTOR J
INDIVIDUALISM
LOW SCORE ( -J)
ZESTFULNESS
Zest for life
Likes group activities r-,Llkes attention
Sinks personality into group
enterprise, loses individual
interests
Vigorous
Accepts common standards
HIGH SCORE (+J)
INDIVIDUALISM
Circumspectly individualist,
reflective
Acts individualistically
Guarded, wrapped up in self
Fastidious, obstructive,
emphasises trivialities,
meticulous
Complains of chronic fatigue,
pains and a lack of
concentration
Evaluates coldly, does not
become involved
People who score high on the Factor J (+J) tend to be
meticulous. They do not follow the group and are often
unpopular. They prefer to remain in the background. They can
be stubborn.
People with
co-operate in
a low
a gr
J
oup
score (-J) adapt
and can be leade
to
rs
circumstances.
or followers.
They
FACTOR 0
GUILT PRONENESS
LOW SCORE ( -0)
SELF-ASSURANCES
Self-assured, placid,
complacent
HIGH SCORE (+0)
PRONENESS TO GUILT FEELINGS
Anxious, full of self-
reproach, insecure, worrying
82
LOW SCORE (-0)
SE LF-ASSURANCES
Cheerful, vigorous, energetic
'thout regrets
Opportunistic, insensitive to
people's approval or
dl sapproval
Uncaring
No fears
Given to simple action
HIGH SCORE (+0)
PRONENESS TO GUILT FEELINGS
Depressed, cries easily,
Hypochondriacal
Touchy, overcome by moods
Strong sense of obligation,
sensitive to people's
approval or disapproval
Scrupulous, fussy
Phobic symptoms
Lonely, brooding
A high 0 score ( +0) is associated with feelings of
inadequacy. They prefer quiet activities to people and noisy
situations. They often feel depressed and guilty when they
make mistakes.
People who score low on Factor 0 (-0) are self-assured,
placid and are not dependent on other people's approval.
FACTOR Q2
SELF-SUFFICIENCY
LOW SCORE (-Q2 )
GROUP DEPENDENCY I----- .Soclally group dependent
A "j oiner" and follower
HIGH SCORE (+Q2 )
SELF-SUFFICIENCY
Self-sufficient, resourceful
Prefers own decisions
A high Q2 score (+Q?) indicates a mature, confident and
resourceful individual. Helshe is stand-offish and tends to
show disdain for the group. They have faith in their own
decisidns and avoid social contact because they feel it is a
waste of time.
83
Those who score low on the factor (-Q2) tend to follow the
group and value social approval. They are conventional and
follow the prevailing fashion.
FACTOR Q3
SELF CONTROL
LOW SCORE ( -Q3)
LOW SELF-SENTIMENT
INTEGRATION
Lax
Follows own urges
Disregards social rules
HIGH SCORE ( +Q3)
HIGH SELF-SENT lMENT
INTEGRATION -
Strong will power, strong
self control
Disciplined, compulsive
Socially correct
A person with a high Q3 (+Q3) score is self-controlled,
ambitious and conscientious. They value accepted social
standards, are considerate of other and plan ahead.
Low Q3 scores are associated with uncontrolled,
impulsive emotionality and the rejection of cultural values.
FACTOR Q4
TENSION
LOW SCORE (-Q4 )
LOW ERGIC TENSION
Relaxed, lethargic, tranquil
Not frustrated
HIGH SCORE (+Q4 )
HIGH ERGIC TENSION
Tense, irritable, overwrought -
Frustrated
A person with a high score on this factor (+Q4) tends to be
unnecessarily worried, frustrated, tense and irritable. This
factor measures situation-linked anxiety which indicated
that the test situation could heighten levels of anxiety.
84
A low score indicated a low level of tension and anxiety. A
very low score is associated with low motivation.
(2) Second-order Factors:
A factor analysis of the correlations between primary
factors produces broader second-order factors. Two second-
order factors have been identified anxiety and
extroversion.
(a) Anxiety:
An anxiety score is obtained by adding sten scores of
relevant primary factors, -C, +D, -G, -H, +0, -Q3 and +Q4
Anxiety is calculated as follows (Visser et al., 1992):
(II-C) + D + (II-G) + (II-H) + 0 + (11-Q3) + Q4) 7
A high score indicates high anxiety and a low score little
anxiety.
(b) Extroversion:
Extroversion is calculated using the sten scores of relevant
primary factors, +A, + F, +H, -J, and -Qz. Extroversion is
calculated using the following formula (Visser et al.,
1992):
A + F + (ll-J) + (ll-Qz) 7
A high extroversion score indicates an outgoing and sociable
person. A low score indicates a withdrawn person.
85
Reliability
Reliability coefficients have been calculated for different
population groups using several test administrations. Test
retest reliability coefficients for the fourteen personality
traits varied from 0,53 to 0,78 although some coefficients
were lower for Black pupils in a few of the scales. Using a
parallel form of the test, each factor was found to
correlate better with itself than with any other factor.
Al though these coefficients were low, they range between
0,22 and 0,52, this is ascribed to the fact that they are
conceptually, not statistically, parallel forms (Visser et
al.,1992).
Validi ty
Between 1967 and 1979 correlations between raw scores of the
HSPQ factors were calculated. Statistically non-significant
or negative correlations were found between the factors.
This implies that the HSPQ identifies the same factors among
South African groups as it does for the American groups on
which the questionnaire was developed. This indicates
construct validity. In 1989 The General Scholastic Aptitude
Test (GSAT) and the HSPQ were administered during the same
testing period. The following results were found:
• Higher extroversion and abstract-reasoning ability scores
on the HSPQ accompanied high verbal IQ scores on the
GSAT.
• Higher superego scores on the HSPQ were associated with
lower verbal IQ scores on the GSAT. A similar pattern was
found for total IQ scores.
86
• The abstract reasoning score on the HSPQ (Factor B)
correlated well with the IQ scores from the GSAT (Pearson
r = 0,41). High scores on E and F were also associated
with higher verbal and total IQ scores.
Since some of the scores from the HSPQ corresponded to
scores from a di fferent measuring instrument, whose
constructs should theoretically correspond, a degree of
confirmation of the concurrent validity of the HSPQ is
implied (Visser et al., 1992).
The HSPQ is used in this study because a broad range of
personality factors is measured and the test has been
standardised for South African high school pupils.
3.8.4 PICTURE MOTIVATION TESTS
The Picture Motivation Tests (PMT) are an attempt to
construct a multi-faceted battery of tests to measure a
relatively large number of motivational aspects. These tests
are based on H.A. Murray's (1938) theory of needs (du Toit,
1983). According to Murray a need, which is a hypothetical
construct, is an internal directional force that determines
how people perceive, conceptualise, experience and act to
alter an unsatisfactory situation~ Murray emphasised the
importance of unconscious motivation. The PMT pictures are
relatively unstructured so as to elicit projective
responses. The subject is, however, given a choice of three
responses. This allows the test to be group administered,
shortens the testing time and enables the objective
interpretation of the results. The three possible responses
are positive, neutral or negative with regard to the
construct. 'lhe PMT consists of twenty separate tests, each
87
containing twelve items that represent twenty motivational
aspects considered important in the school situation. The
tests are arranged in groups of five so that five, ten,
fifteen or all of the twenty tests can be administered,
depending on specific requirements. In this research the
first two groups of five were administered. These ten tests
are arranged in the following order:
(a) First Group: Cognitive structure, Aggression,
Scholastic Achievement, Affiliation, and Endurance.
(c) Second Group: Understanding, Exhibition, Order,
Achievement (general), and Play.
The behaviour tendencies of subjects who obtain relatively
high scores on these constructs are described as follows (du
Toit, 1983, pp. 3-5):
Cognitive Structure (CS):
A dislike of uncertainty regarding information; wants to
have all questions answered fully; takes decisions on the
basis of thorough knowledge; avoids guessing and
uncertainty; prefers precision, completeness, certainty,
clarity, accuracy; tends to be rigid.
Aggression (Ag):
Tends to overcome opposition forcefully, to fight, to
revenge an injury, to attack, injure, even to kill when
aroused, to oppose forcefully or to punish; tends to be
aggressive, quarrelsome, irritable, touchy, antagonistic,
moody, vengeful and hostile.
88
Scholastic Achievement (SA):
Strives to achieve in school subjects, to get good marks, to
master new material, to do homework well, to complete all
assignment even when ill or tired, to excel; tends to be
hard-working, diligent, resourceful, ambitious and to take
initiative in scholastic study.
Affiliation (Af):
Enjoys being with friends; likes to communicate with others;
readily accepts people; tries to make friends and keep up
friendships. Likes to please and win the affection of
others; tends to adhere and remain loyal to friends; shows a
tendency to be friendly, jovial, warm, good-natured, genial,
hospitable, social, easy-going and obliging.
Endurance (En):
Willing to work long hours; will not easily throw in the
towel; patiently enduring, determined, resolute; constant
working habits; persevering and hard working.
Understanding (Un):
Keen to have an understanding of different areas of
knowledge; tends to ask and answer general questions;
interested in theory, logical thinking, analysis and
formulas; will speculate and generalise; intellectually
inquisitive; explores, tests, examines, samples and
experiments.
89
Exhibition (Ex):
Likes to make an impression, to be seen and heard, to
excite, amaze, fascinate, entertain, shock, intrigue, amuse
and entice others; tries to be the centre of interest;
colourful, out of the ordinary, exhibitionistic,
demonstrative, dramatic and attention-getting.
Order (Or):
Likes to put things in order, to achieve cleanliness, to
arrange, organise, tidy up; exhibits a need for balance,
neatness and precision; methodical; dislikes slovenliness
and carelessness; clean, disciplined, consistent, punctual.
Achievement (Ach):
Likes to accomplish something difficult, to master,
manipula te, or organise physical obj ects, human beings or
ideas, and to do this as rapidly, independently and
thoroughly as possible. Tends to overcome obstacles and
attain a high standard, to excel, to rival, to compete and
surpass others, to use own talents to the best of his/her
ability; aspiring, determined, purposeful, productive,
resourceful and diligent.
Play (Pl):
Enj oys having fun, laughing, joking; seeks enj oyable
relaxation; likes to participate in games, sports, parties
and playing; has a light-hearted, easy attitude; playful,
jovial, pleasure-seeking, fond of laughing, funny, carefree
and cheerful.
90
These tests are not timed. Subjects generally complete the
tests in about an hour and a half.
Reliability
Kuder-Richardson 8 reliabili ty coefficients for the 10 PMT
tests for Standard 8 boys and girls range between 0,6 and
0,7. This lS considered satisfactory for a test consisting
of 12 items.
Validi ty
Results of factor analyses show that there is considerable
similarity between the loadings of the PMT and the
Motivation Questionnaire. This is an indication of factorial
(construct) validity (du Toit, 1983).
The PMT is used in this study because a relatively large
number of motivational aspects are measured, it allows for
group administration and elicits projective responses.
Reliability and validity data are at an acceptable level.
3.8.5 THE LEARNING STYLES QUESTIONNAIRE
The Learning Styles Questionnaire (LSQ) is based on Kolb's
(1976) theory of learning and identi fication of learning
styles. Kolb viewed learning as a series of experiences with
cognitive additions rather than as a series of pure
cognitive processes. According to Kolb experiential learning
follows a 4-phase cycle (Figure 3.2) :
91
Figure 3.2
KOLB'S CIRCULAR LEARNING PATTERN
Concrete Experience
Active Experimentation
Reflective observation
Abstract conceptualisation
Learning is seen as a circular process in which Concrete
Experience is followed by Reflective Observation. This in
turn leads to Abstract concepts that are tested through
Active experimentation. People are not equally effective in
all the stages; most people develop learning styles that
emphasise one or more of these stages. He identified four
styles of learning that correspond with these stages: The
Converger, Diverger, Assimilator and Accommodator. The
Learning Styles Inventory was used to establish an
individual's relative emphasis on each of the four styles.
Building on this model, Honey and Mumford (1982) developed
the Learning Styles Questionnaire (LSQ) to eliminate some of
the shortcomings of the Learning Styles Inventory. In
addi tion, they preferred the terms Pragmatist, Reflector,
Theorist and Activist to describe the four learning styles.
Activists and pragmatists are more practically orientated,
92
whereas reflectors and theorists are more theoretically
orientated. They define these learning styles as follows
Honey & Mumford, 1986):
Pragmatists
Pragmatists search out new ideas, theories and techniques
and experiment with them to see if they work in practice.
They are practical and down to earth.
They learn best when
• there is an obvious link between subj ect matter and
the problem;
• techniques they are shown have an obvious practical
advantage;
• they have a chance to practise techniques with
credible assistance;
• they are exposed to a role model;
• they are given opportunities to implement what they
have learned;
• they can concentrate on practical issues.
Reflectors
Reflectors tend to stand back and think about new
experiences. They like to consider all possible angles
before making a decision. They prefer to observe rather than
participate.
They learn best when
• they are permitted to watch and think about
activities;
• they are able to observe and listen;
93
• they can think before acting, have time to
assimilate;
• they can probe to get to the bottom of things;
• they can review what has been taught;
• they are required to produce carefully considered
reports;
• interaction with others is structured;
• there is no time limit.
Theorists
Theorists like to think problems through in a logical
manner. They enjoy working with assumptions, principles,
theories and models, where they can analyse and synthesise.
They learn best when
• what they learn is part of a theory, concept or
system;
• they have time to methodically explore relationships
between ideas or events;
• they are allowed to question the logic behind
something;
• they are intellectually stretched;
• the situation is structured;
• ideas and concepts are rational and logical;
• ideas need not be immediately relevant, as long as
they are interesting.
Activists
Activists rely on an intuitive trial-and-error approach to
solve problems. They are enthusiastic about anything new and
94
thrive on the challenges of new experiences. They do,
however, tend to get bored in the long-term.
They learn best when:
• there are new experiences and problems from which to
learn;
• they are involved in short "here and now"
activities;
• there is excitement and drama;
• they are In the limelight;
• they are allowed to generate new ideas;
• they are involved with other people;
• they can "have a go" .
Honey & Mumford (1986) maintain that when an individual's
learning style preference and the style of teaching
correspond, it is more likely that effective learning will
take place.
The instructions for group administration of the Set
Variations 1 supplied in the manual, are most suitable for
subjects with a Theorist preference, particularly since the
lesson is presented on video (P. Honey, personal
communication, February, 1994).
Most of the work done with the LSQ has concentrated on
businessmen/women. The adolescent version of the LSQ
consists of 40 statements. Subjects are asked to indicate,
on balance, whether they agree or disagree with each
statement, by marking it with either a tick or a cross.
Norms are available for A level/diploma students.
95
Reliabili ty studies have produced average coefficients of
0,89, with Theorist and Reflector preferences most
consistent at 0,95 and 0,92 respectively. Pragmatists
produced a test-retest consistency of 0,87 and Activists
0,81 (Honey & Mumford, 1982).
The LSQ is used in this research because it identifies the
subject's relative strengths in each of four learning styles
and the mediation lesson corresponds to one of these styles
i.e. the theorist learning style.
3.8.6 CATTELL'S CULTURE FAIR INTELLIGENCE TEST
The influence of culture on test performance has been
studied for years. Since it was found to be impossible to
develop a perfectly culture-free test, attempts have been
made to make tests as culture-fair as possible. These tests
do not eliminate cultural influences but try to minimise
their effects (Brown, 1976)
Cattell's Culture Fair Intelligence Test (CCFIT) was
designed to measure fluid intelligence, which is not
significantly influenced by cultural differences (Cattell,
1959b). The test is non-verbal and relies on the subject's
ability to perceive relationships in shapes and figures.
The CCFIT has three levels. Scale 2, which is suitable for
ages 8 to 13 and average adults was used in this research,
since performance was found to fall below original norms in
cultures which are different from those in America and some
European countries (Anastasi, 1990). Each scale consists of
two parallel forms Form A and Form B. Form A was
administered as a pre-test, before the intervention, and
Form B as a post-test in order to measure transfer effects.
96
Each form of the CCFIT consists of four subtests:
1. Series: The task is to select, from the choices
provided, the item that completes the series.
2. Classification: The subject is presented with five
figures and s/he must mark the item that is different
from the others.
3. Matrices: The item which completes the design or matrix
must be indicated.
4. Conditions (or Topology): In this test five choices are
provided. The subj ect is required to choose the one
that meets the same conditions as those in the sample
design.
Examples are given before each subtest so that the subjects
are aware of what is expected of them.
The CCFIT has strict time limits imposed on each subtest.
Reliability
The reliability coefficients for Scale 2 Form A & B range
from 0,80 - 0,87 and for Form A only from 0,67 - 0,76.
Validity
Correlations between the CCFIT and other measures of
intelligence (otis, SAT and Intelligence structure Test)
range between 0,69 and 0,92.
The CCFIT is used in this study because, like the RSPM, it
is a culture-fair test of g. It is sufficiently different
from, and the items are generally more difficult than those
of the RSPM, to measure transfer effects.
97
3.9 STATISTICAL ANALYSIS OF THE DATA
In order to ensure that errors were minimised, two research
assistants marked all the tests separately and disparities
were checked. A further check was done on the printout of
the descriptive statistics.
Learning Potential was calculated as the difference between
the Raven's Standard Progressive Matrices pre- and post-test
raw scores.
All statistical tests were conducted at the 5% significance
level (a = 0,05). The following inferential tests were
conducted to test the hypotheses.
HI: A one-tailed t-test was conducted to test for
differences in Learning Potential scores between the groups
that were and were not subj ected to the teaching
intervention. Variances were tested for equality using the
F-test: in the case of equal variances a conventional t-test
was used and in the case of unequal variances, the Aspin
Welch modified t-test (Hintze, 1995) was used.
Hz: The Kruskal-Wallis One-Way Analysis of variance (ANOVA)
test was used to determine whether any practice effects were
present between the Raven's pre- and post-test scores across
the four groups (two experimental and two control). This
non-parametric test was used in preference to one-way ANOVA
because the assumption of normality was rejected using the
Omnibus Normality Test (Hintze, 1995).
H3 : The association between learning potential scores and
the 14 personality traits was measured using Pearson's
98
Correlation Coefficient. The t-test was used to establish
whether these correlation coefficients were significantly
different from zero. In addition a regression analysis was
performed to establish whether a combination of two or more
variables significantly predict learning potential.
H4 : The association between learning potential scores and
the 10 motivational factors was measured using Pearson's
Correlation Coefficient. The t-test was used to establish
whether these correlation coefficients were significantly
different from zero. In addition a regression analysis was
performed to establish whether a combination of two or more
variables significantly predict learning potential.
Hs : The association between learning potential scores and
the four learning styles scores was measured using Pearson's
Correlation Coefficient. The t-test was used to establish
whether these correlation coefficients were significantly
different from zero. In addition a regression analysis was
performed to establish whether a combination of two or more
variables significantly predict learning potential.
H5 : The correlation coefficients between the learning
potential scores (as measured by the difference between the
pre-intervention and post-intervention scores obtained on
the Raven's Standard Progressive Matrices) and the scores on
Cattell's Culture Fair Test, Scale 2, Form A (initial
testing phase) were tested using Pearson's Correlation
Coefficient. A t-test established whether these coefficients
were significantly different from zero.
H : A one-tailed t-test was conducted to test for
difference in transfer scores on Cattell's Culture Fair
7
99
Intelligence Test between the groups that were and were not
subjected to the teaching intervention. Variances were
tested for equality using the F-test: in the case of equal
variances a conventional t-test was used and in the case of
unequal variances, the Aspin-Welch modified t-test was used.
H8 : The correlation coefficients between the Learning
Potential Scores and the pre- and post-test difference
scores on Cattell's Culture Fair Test were tested using
Pearson's Correlation Coefficient and a t-test for
establishing whether these coefficients were significantly
different from zero.
100
CHAPTER 4
RESEARCH RESULTS
4.1 INTRODUCTION
The results of the data analysis conducted on the hypotheses
as stated in Chapter 3 are presented in this chapter. The
expected outcome of an hypothesis will be indicated by means
of an asterisk to the left of the hypothesis.
4.2 HYPOTHESIS 1
Hol : A standardised teaching intervention by means of
videotape has no effect on Learning Potential scores (as
measured by the difference between the pre-intervention and
post-intervention scores obtained on Raven's Standard
Progressive Matrices)
*Hal: A standardised teaching intervention by means of a
videotape increases Learning Potential scores (as measured
by the difference between the pre-intervention and post
intervention scores obtained on Raven's Standard Progressive
Matrices) .
101
TABLE 4.1
THE EFFECTS OF INTERVENTION/ NO INTERVENTION ON
LEARNING POTENTIAL SCORES
Variable Count Mean Standard
Deviation
Standard
Error
Intervention
= No
30 -0,1 4,286 0,782
Intervention
= Yes
30 2,567 4,174 0,762
95% Lower
Confidence
Limit of
Mean
-1,700
95% Upper
Confidence
Limit of
Mean
1,500
1,008 4,125
The intervention appears to create positive learning
potential scores, as is evidenced by the fact that zero is
not contained within the range of the 95% upper and lower
confidence limits.
TABLE 4.2
THE OMNIBUS NORMALITY TEST
ON LEARNING POTENTIAL SCORES
Value Probability Decision
Intervention
No
= 0,779 0,677 Cannot reject
normality
Intervention
Yes
= 2,475 0,290 Cannot reject
normality
This test indicates that the learning potential scores
follow a normal distribution.
102
TABLE 4.3
VARIANCE-RATIO EQUAL-VARIANCE TEST
ON LEARNING POTENTIAL SCORES
Value Probability Decision
1,054 0,888 Cannot reject
equal variances
The assumptions of normality and equal variance underlying
the t-test are thus met.
TABLE 4.4
EQUAL-VARIANCE t-TEST
ON LEARNING POTENTIAL SCORES
Alternative hypothesis
(Interventlon = no)
(Interventlon = yes) ":f::- 0
t-Value Prob.
Level
-2,441 0,018
Decision (5%
significance
level)
Reject HO l
The standardised teaching intervention had a statistically
significant effect on Learning Potential scores. Therefore,
the alternative hypothesis Hal is accepted.
103
4.3 HYPOTHESIS 2
Ho z: There is no statistically significant practice effect
between the pre- and post-test scores of the Raven's
Standard Progressive Matrices.
*Haz: There is a statistically significant practice effect
between the pre- and post-test scores of the Raven's
Standard Progressive Matrices.
TABLE 4.5
RAVEN'S STANDARD PROGRESSIVE MATRICES PRE-TEST:
DESCRIPTIVE STATISTICS
Group Mean S.D. S.E. Min. Max. Range Number
1 36,767 8,752 1,598 11 51 40 30
3 37,433 9,420 1,720 15 49 34 30 -
Group
Group
1
3
Pre-test,
Pre-test,
mediated lesson, post-test
no mediation, post-test
TABLE 4.6
RAVEN'S STANDARD PROGRESSIVE MATRICES
DESCRIPTIVE STATISTICS
POST-TEST:
Group Mean S. D. S.E. Min. Max. Range Number
1 39,333 8,500 1,551 12 51 39 30
2 37,900 6,799 1,241 25 49 24 30
'3 37,333 10,056 1,836 11 55 44 30
4 34,800 8,240 1,504 13 50 37 30
104
Group 1 Pre-test, mediated lesson, post-test.
Group 2 = No pre-test, mediated lesson, post-test.
Group 3 Pre-test, no mediation, post-test.
Group 4 No pre-test, no mediation, post-test.
From these descriptive statistics, it is unclear as to
whether or not any practice effects are evidenced. This can
only be established by the application of formal inferential
tests.
TABLE 4.7
OMNIBUS NORMALITY TEST OF RESIDUALS
Value Probability Decision (5%
significance level)
Reject normality24,131 0,000
It is therefore necessary to use a Kruskal-Wallis test
rather than ANOVA.
TABLE 4.8
KRUSKAL-WALLIS ONE-WAY ANOVA ON RANKS
Ho: All medians are equal (Groups 1 and 3; Groups 2 and 4) .
Ha: Not all medians are equal.
Method
Corrected for ties
DF Chi-Square Probe Decision ~
(H) Level significance
level)
Accept H0 23 6,505 0,089
105
There is no evidence of a practice effect being present from
the first to the second testing. Therefore, the null
hypothesis (Ho 2 ) cannot be rejected.
4.4 HYPOTHESIS 3
Ho 3 : Personality factors, as measured by the High School
Personality Questionnaire (HSPQ) are not significantly
related to learning potential scores (as measured by the
difference between the pre-intervention and post
intervention scores obtained on the Raven's Standard
Progressive Matrices)
*Ha3: Personality factors, as measured by the HSPQ are
significantly related to learning potential scores (as
measured by the difference between the pre-intervention and
post-intervention scores obtained on the Raven's Standard
Progressive Matrices) .
TABLE 4.9
HIGH SCHOOL PERSONALITY QUESTIONNAIRE:
DESCRIPTIVE STATISTICS
HSPQ
Factors
Count Mean S.D. S.E. Mini
mum
Maxi
mum
Range
A 120 5,125 1,658 0,151 2 10 8
B 120 2,858 1,702 0,155 1 8 7
C 120 5,375 1,680 0,153 1 9 8
D 120 5,617 1,735 0,158 2 9 7 I-------
E 120 4,808 1,740 0,159 1 9 8
F 120 4,633 1,953 0,178 1 10 9 ~
G 120 4,842 1,675 0,153 1 8 7
106
HSPQ Count
Factors
Mean S. D. S.E. Mini
mum
Maxi
mum
Range
H 120 I--
5,625 1,473 0,134 2 9 7
I 120 5,183 2,090 0,191 1 10 9
J 120 6,85 1,708 0,156 2 10 8
0 120 4,741 1,741 0,159 1 9 8
Q2 120 5,217 1,984 0,181 1 10 9
Q3 120 6,075 1,879 0,172 1 10 9 -
Q4 120 4,775 2,092 0,191 1 10 9
ANXIETY 120 5,320 0,921 8,408 3,14 8,57 5,43
EXTRO 120 5,062 0,919 8,391 2,2 7,6 5,4
VERSION ~___L
The names and descriptions of these traits may be found in
section 3.8.3.
Factor B (intelligence) has a lower mean score than the
other factors. Factor J (individualism) is somewhat higher
than the other factors.
TABLE 4.10
PEARSON'S CORRELATION COEFFICIENTS FOR PERSONALITY TRAITS
AND LEARNING POTENTIAL SCORES
Personality
Traits
Count Learning
Potential
Probab
ility
Decision (5%
significance
level)
No significant
correlation
A 60 -0,036 0,783
B 60 -0,047 0,721 No significant
correlation '------
107
Personality
Traits
Count Learning
Potential
Probab
ility
Decision (5%
significance
level)
No significant
correlation
C 60 0,010 0,941
D 60 -0,202 0,121 No significant
correlation
E 60 -0,151 0,251 No significant
correlation
F 60 0,081 0,539 No significant
correlation -~
Significant
correlation
G 60 0,354 0,006
H 60 0,009 0,943 No significant
correlation
I 60 -0,243 0,061 No significant
correlation
J 60 0,0166 0,206 No significant
correlation
0 60 0,185 0,157 No significant
correlation
Q2 60 0,078
0,014
0,556 No significant
correlation
No significant
correlation
~
QJ 60 0,912
Q4 60 -0,083 0,531 No significant
correlation
ANXIETY 60 -0,137 0,298 No significant
correlation
EXTROVERSION 60 -0,074 0,576 No significant
correlation
108
The names and descriptions of these traits may be found in
section 3.8.3.
Only Factor G (Conscientiousness) correlates with Learning
Potential scores. This correlation is weak but positive.
The regression analysis yielded the following results:
TABLE 4.11
REGRESSION MODEL SUMMARY OF THE 14 HSPQ TRAITS
Model R Square
,125
,193
,261
Adjusted R
Square
,110l. G
,1652. G, I
,2213 . G, I, 0
Std. Error of
the Estimate
4,16
4,02 -
3,89
Dependent variable: Learning Potential.
Three variables i. e. G (Conscientiousness), I (Tough
mindedness) and 0 (Proneness to guilt feelings) explain 22%
of the variance in learning potential scores.
TABLE 4.12
REGRESSION MODEL OF THE 14 HSPQ TRAITS
Coefficient T Probability
(Constant) -3,296 -1,400 ,167 I----
G ,965 3,450 ,001
I -,595 -2,502 ,015
0 ,654 2,253 ,028
109
Dependent Variable: Learning Potential.
It is interesting to note that G and 0 are on the positive
poles of these traits i.e. higher scorers, whereas I is on
the negative pole i.e. lower scorers.
TABLE 4.13
OVERALL TEST OF SIGNIFICANCE
Model Sum of df Mean F Significance
1--
Regression
Squares
298,231 ~
3
Square
99,410 6,576
level
,001
Residual 846,503 56 15,116
Total 1144,733 59
Dependent Variable: Learning Potential.
This test indicates that the regression model is
statistically significant.
TABLE 4.14
CORRELATION MATRIX OF INDEPENDENT VARIABLES
,..----~-----~~~----,-- ------G
c--------------_t_
G
~-
o
I
-0,001
o
-0,072
0,122
The independent variables are clearly statistically
independent.
110
The al ternative hypothesis (Ha3) is accepted for Factor G
(Conscientiousness) and for a combination of Factors G
(Conscientiousness), I (Tough mindedness) and 0 (Proneness
to guilt feelings). The null hypothesis (Ho 3) cannot be
rejected for all the other personality factors.
4.5 HYPOTHESIS 4
Motivational traits as measured by the Picture
Motivation Tests (PMT) are not significantly related to
learning potential scores (as measured by the difference
between the pre-intervention and post-intervention scores
obtained on Raven's Standard Progressive Matrices).
*Ha4: Motivational traits as measured by the PMT are
significantly related to learning potential scores (as
measured by the difference between the pre-intervention and
post-intervention scores obtained on Raven's Standard
Progressive Matrices) .
TABLE 4.15
PICTURE MOTIVATION TESTS:
DESCRIPTIVE STATISTICS
-Motiva
tional
Factors
Count Mean S . D. S.E. Mini
mum
Maxi
mum
Range
CS 120 4,508 1,749 0,160 1 8 7
Ag 120 4,417 1,521 0,139 1 8 7
SA 120 4,900 1,558 0,142 1 9 8
Af 120 4,017 1,512 0,138 1 8 7
111
· -r-c-Motlva- Count Mean S.D. S.E. Mini- Maxi- Range
tional mum mum
Factors 1----
End 120 3,808 1,731 0,158 1 8 7
Un 120 4,658 1, 678 0,153 1 9 8
Ex 120 4,383 1,807 0,165 1 9 8 f-
Or 120 4,383 1,848 0,169 1 8 7 --
Ach 120 3,708 1,727 0,158 1 8 7
Pl 120 4,133 1,772 0,162 1 9 8
Abbreviations:
CS Cognitive Structure
Ag Aggression
SA Scholastic Achievement
Af Affiliation
En Endurance
Un == Understanding
Ex == Exhibition
Or Order
Ach Achievement
Pl Play
The means appear similar for all these motivational factors.
112
TABLE 4.16
PEARSON'S CORRELATION COEFFICIENTS FOR MOTIVATIONAL FACTORS
AND LEARNING POTENTIAL SCORES
Motivational Count Learning Proba- Decision (5%
Factors Potential bility significance level i-- .,Cognltlve 60 -0,110 0,401 No significant
Structure correlation
Aggression 60 0,257 0,048 Significant
correlation
Scholastic 60 -0,007 0,958 No significant~--
Achievement correlation
r-Affiliation 60 0,120 0,360 No significant
correlation
Endurance 60 0,073 0.579 No significant
correlation
understanding 60 -0,103 0,433 No significant
correlation
Exhibition 60 -0,057 0,667 No significant
correlation
Order 60 -0,009 0,944 No significant
correlation
Achievement 60 0,049 0,707 No significant
correlation
Play 60 -0,018 0,893 No significant
correlation
The only factor that correlates significantly with Learning
Potential scores is Aggression (Ag). This correlation is
weak but positive.
The regression analysis yielded the following results:
113
--
--
TABLE 4.17
REGRESSION MODEL SUMMARY OF THE 10 PMT TRAITS
,-----
Model R Std. Error of
Square the Estimate r •
4,29Aggresslon ,066
Dependent Variable: Learning Potential.
One variable, Aggression, accounts for 6,6% of the variance
in learning potential scores.
TABLE 4.18
REGRESSION MODEL OF 10 PMT TRAITS
Model Coefficients T Probability
(Constant) -2,117 -1,213 ,230
, 048Aggression ,845 2,025
Dependent Variable: Learning Potential.
There is a positive relationship between Aggression and
learning potential scores.
114
TABLE 4.19
OVERALL TEST OF SIGNIFICANCE
I
Model Sum of
Squares
df Mean
Square
F Significance
level
Regression 75,560 1 75,560 4.099 .048
Residual 1069,174 58 18,434
Total 1144,733 ~-~-~--'--
59
Dependent Variable: Learning Potential.
This test indicates that the regression model is
statistically significant.
The alternative hypothesis (Ha4) is accepted for Aggression.
The null-hypothesis (Ho4 ) cannot be rejected for all the
other motivational traits.
4.6 HYPOTHESIS 5
Ho s : The learning styles of adolescents as measured by the
Learning Styles Questionnaire (LSQ) are not significantly
related to learning potential scores (as measured by the
difference between the pre-intervention and post
intervention scores obtained on the Raven's Standard
Progressive Matrices)
*Has: The learning styles of adolescents as measured by the
LSQ are significantly related to learning potential scores
(as measured by the difference between the pre-intervention
and post-intervention scores obtained on the Raven's
Standard Progressive Matrices) .
115
TABLE 4.20
LEARNING STYLES:
DESCRIPTIVE STATISTICS
~-
Learning
Style
Count Mean S.D. S.E. Mini
mum
Maxi
mum
Range
Activist 120 4,317 1,975 0,180 ° 10 10
Reflector r--- .
120 8,658 1,526 0,139 3 10 7
Theorlst 120 7,908 1,449 0,132 2 10 8
Pragmatist 120 7,033 1,705 0,156 3 10 7
The mean scores for Reflector, Theorist and Pragmatist
Learning Styles are very similar. Mean scores for the
Activist learning style appear to be much lower.
TABLE 4.21
PEARSON'S CORRELATION COEFFICIENTS FOR LEARNING STYLES AND
LEARNING POTENTIAL SCORES
Decision (5%Learning Count Learning Probability ~.
significancePotentialStyle
level)
No0,52260 0,084Activist
significant
correlation
No0,716-0,04860Reflector
significant
correlation r---- , No
significant
0,391-0,11360Theorlst
correlationi I
116
Learning
Style
Count
-
Learning
Potential
Probability Decision (5%
significance
level) --~
Pragmatist 60 0,154 0,241 No
significant
correlation
The null hypothesis cannot be rejected since there is no
statistically significant correlation between the Learning
Styles and learning potential scores.
None of the four learning styles proved significant
predictors of learning potential in the regression analysis.
The null-hypothesis (Ho:,) cannot be rejected for all four
learning styles.
4.7 HYPOTHESIS 6
Ho 6 : The general cogni tive ability pre-test scores (as
measured by Cattell's Culture Fair Intelligence Test, Scale
2, Form A) are not significantly related to the subject's
learning potential scores (as measured by the difference
between the pre-intervention and post-intervention scores on
the Raven's Standard Progressive Matrices).
*Ha6: The general cognitive ability pre-test scores (as
measured by Cattell's Culture Fair Intelligence Test, Scale
2, Form A) are significantly related to the subject's
learning potential scores (as measured by the difference
between the pre-intervention and post-intervention scores on
the Raven's Standard Progressive Matrices).
117
--
TABLE 4.22
PEARSON'S CORRELATION COEFFICIENTS FOR CATTELL'S CULTURE
FAIR INTELLIGENCE TEST, SCALE 2, FORM A AND LEARNING
POTENTIAL SCORES
Count
CCFIT Form A
Raw scores
CCFIT Form A
Standard scores '----
60
60
Learning
Potential
0,093
0,071
Proba-
Bility
0,479
0,592
Decision
No significant
correlation
No significant
Correlation -~
There is no significant correlation between scores on
Cattell's Culture Fair Intelligence Test Form A and learning
potential scores. Therefore, the null-hypothesis (Hoal
cannot be rejected.
4.8 HYPOTHESIS 7
Ho 7: The standardised teaching intervention by video, using
Feuerstein's LPAD Set Variations 1 as a mediation tool, has
no effect on transfer scores (as measured by the difference
score between Cattell's Culture Fair Intelligence Test,
Scale 2, Form A and Form B) .
*Ha7: The standardised teaching intervention by video, using
Feuerstein's LPAD Set Variations 1 as a mediation tool,
improves transfer scores (as measured by the difference
score between Cattell's Culture Fair Intelligence Test,
Scale 2, Form A and Form B) .
118
Tables 4.23 4.26 will first be presented and then
discussed together. The identification of the groups will be
indicated under Table 4.23
TABLE 4.23
CATTELL'S CULTURE FAIR INTELLIGENCE TEST, SCALE 2, FORM A
RAW SCORES
Group Count Mean S. D. S.E. Minimum Maximum Range
1 30 -
23,067 6,045 1,104 9 35 26
2 30 21,8 6,536 1,193 6 31 25
30-
3 30 21,933 6,787 1,239 5 35
314 30 21,167 6,281 1,147 6 25
Group 1 Pre-test, mediated lesson, post-test.
Group 2 No pre-test, mediated lesson, post-test.
Group 3 Pre-test, no mediation, post-test.
Group 4 No pre-test, no mediation, post-test.
TABLE 4.24
CATTELL'S CULTURE FAIR INTELLIGENCE TEST FORM A
STANDARD SCORES
RangeMaximumS.D. S.E. MinimumMeanGroup Count
109 525783,667 11,778 2,150301
4097572,48680,1 13,6212 30
109 833,108 2617,02430 79,3333
4057 972,38513,06279,267304
119
TABLE 4.25
CATTELL'S CULTURE FAIR INTELLIGENCE TEST FORM B
RAW SCORES
Gro
1
2
3
4
-up Count Mean S. D. S . E. Minimum Maximum Range
30 28 5,246 0,958 14 36 22
-
30
30
30
26,9
24,533
24,167
5,622
7,186
4,983
1,026 13
1,3f2 -
6
0,910 14
37
35
35
24
29
21
TABLE 4.26
CATTELL'S CULTURE FAIR INTELLIGENCE TEST FORM B
STANDARD SCORES
Group Count Mean S . D. S.E. Minimum Maximum Range
1 30 88,967 10,746 1,962 57 109 52
2 30 87,067 12,211 2,229 57 113 56
3 30 83,2 12,491 2,281 57 104 47
4 30 81,433 10,827 1,977 57 104 47
These results appear to indicate an increase in scores from
the pre-test to the post-test. This has to be verified by
the application of formal statistics.
120
TABLE 4.27
THE EFFECTS OF INTERVENTION/ NO INTERVENTION ON CATTELL'S
CULTURE FAIR INTELLIGENCE TEST
Variable Count Mean Standard
Deviation
Standard
Error
Intervention
= No
60 2,8 5,200 0,671
Intervention
= Yes
60 5,017 5,057 0,653
95% Lower
Confidence
Limit of
Mean
1,457
95% Upper
Confidence
Limit of
Mean
4,143
3,710 6,323
The intervention appears to have increased scores on the
CCFIT, as is evidenced by the fact that zero is not
contained within the range of 95% upper and lower confidence
limits.
TABLE 4.28
RESULTS OF THE OMNIBUS NORMALITY TEST ON THE DIFFERENCE
SCORES ON CATTELL'S CULTURE FAIR INTELLIGENCE TEST
r---Value Probability
Intervention
= No
11,621 0,003
Intervention
= Yes
2,818 0,244
Decision (5%
significance
level)
Reject normality
Cannot reject
normality
Because normality of the scores is rejected in the control
group, the t-test cannot be used for comparing the transfer
121
Iscores of the experimental and control groups. Therefore the
Mann-whitney u- test was used.
TABLE 4.29
RESULTS OF THE MANN-WHITNEY U- TEST ON THE DIFFERENCE SCORES
OF CATTELL'S CULTURE FAIR TESTS
Alternative
Hypothesis
Diff # °
Approximation with Correction
Z-Value Probability Decision (5%
Level significance
level)
2,313 0,021 Reject H0 7
Gain scores based on the difference score between the CCFIT
Form A to the CCFIT Form B scores were due to the teaching
intervention. Therefore the al ternative hypothesis (Ha6) is
accepted.
It is also necessary to establish whether these results were
contaminated by a practice effect. An ANOVA test could not
be used because normality could not be assumed. A Kruskal
Wallis One-Way ANOVA yielded a chi-square of 9,84
(probability = 0,02) which suggests that the medians of the
CCFI Form B are not equal across the four experimental
groups. These differences were explored further with the
following results:
122
TABLE 4.30
KRUSKAL-WALLIS MULTIPLE-COMPARISON Z-VALUE TEST
CCFI
TFORM B GROUP
0,00
1 GROUP
0,81
2 GROUP
2,18
3 GROUP
2,82
4
2 0,81 0,00 1,37 2,01
3
4
2, 18
2,82
1,37
2,01
0,00
0,64
0,64 -
----- 0,00
• Group 1 is significantly different from Groups 3 and 4 .
This may be due to the teaching intervention since Group
1 and 2 received the intervention whilst the latter two
did not.
• Group 2 is significantly different from Group 4. This may
al so be due to the intervention since Group 2 received
the intervention and Group 4 did not. However, this does
not explain why there is no significant difference
between Group 2 and Group 3.
• Group 3 is significantly different from Group 1, as shown
above. However, there is no significant difference
between Group 3 and Group 2.
• Group 4 is significantly different from Groups 1 and 2.
Once again since Group 4 did not receive intervention
whilst the other two did, it may be inferred that the
intervention was responsible.
To clarify the above, two further tests were executed. A
Wilcoxon Signed-Rank Test for difference in Medians for
CCFIT Form A and CCFIT Form B for the 60 subj ects who
received intervention and the 60 who did not, yielded a Z
Value of 4,177 (probability = 0,00003). The gain scores were
therefore significantly affected by practice.
123
Looking at the role of the teaching intervention a Mann
Whitney Test for difference in medians between those groups
who received the intervention and those who did not yielded
a Z-Value of 2,96 (Probability 0,003). The teaching
intervention also had a significant effect on the gain
scores. The gains on the CCFIT Form B appear to be a result
of an interaction between teaching and practice.
4.9 HYPOTHESIS 8
Has: The learning potential scores (as measured by the
difference between the pre-intervention and post
intervention scores obtained on the Raven's Standard
Progressive Matrices) are not significantly correlated to
the transfer gain scores (as measured by the difference
between Cattell's Culture Fair Intelligence Test, Form A and
Form B) .
*Has: The learning potential scores (as measured by the
difference between the pre-intervention and post
intervention scores obtained on the Raven's Standard
Progressive Matrices) are significantly positively
correlated to the transfer gain scores (as measured by the
difference between Cattell's Culture Fair Intelligence Test,
Form A and Form B) .
124
TABLE 4.31
PEARSON'S CORRELATION COEFFICIENTS FOR THE DIFFERENCE SCORES
BETWEEN THE CCFIT FORM A AND FORM B AND LEARNING POTENTIAL
SCORES
,----
~CFIT Form B
CCFIT Form A
Raw Scores
CCFIT Form B
CCFIT Form A
-
-
Standard Scores '--
--- -,---
Count
60
60
Learning
Potential
0,126
0,106
Proba-
Bility
0,337
0,421
Decision
No significanf
correlation
No significant
correlation
There is no significant correlation between the pre- and
post-test difference scores on the Culture Fair Intelligence
Tests and learning potential scores. Therefore the null
hypothesis (Ho s ) cannot be rejected.
The next chapter will contain a discussion of the findings
reported in this chapter.
125
CHAPTER 5
DISCUSSION AND CONCLUSION
5.1 INTRODUCTION
The focus of this chapter is a summary and discussion of the
results of this research project. Conclusions are drawn and
limitations are discussed.
5.2 SUMMARY OF RESULTS
The results as presented in Chapter 4 may be summarised as
follows:
• The one hour standardised teaching intervention resulted
in positive gains from the pre-test to the post-test on
Raven's Standard Progressive Matrices (RSPM).
• There was no evidence of a practice effect between the
pre- and post-test of Raven's Standard Progressive
Matrices.
• Of the non-intellective factors tested, only
Conscientiousness (as tested on the High School
Personalit.y Questionnaire) and Aggression (as tested on
the Picture Motivation Test) were positively correlated
to Learning Potential scores. However, when a
mUltivariate prediction of learning potential scores from
the personality traits of the HSPQ is made,
conscientiousness, tough-mindedness and proneness to
guilt feelings explains 22% of the variance in the
126
scores. A multivariate prediction of learning potential
scores from motivational factors, indicated that one
variable of the PMT, viz. Aggression was a significant
predictor, explaining 6,6% of the variance in the scores.
• General cogni tive ability (as measured by the Culture
Fair Intelligence Test Form A) and learning potential
scores were independent of one another.
• The increase in scores from the Culture Fair Intelligence
Test Form A to the Culture Fair Intelligence Test Form B
appears to be a result of both the intervention and
practice effects.
• The pre- and post-test difference scores on the Culture
Fair Intelligence Tests did not correlate with learning
potential scores.
5.3 DISCUSSION
5.3.1 GROUP ADMINSTRATION OF A SHORT LEARNING TEST USED IN
A STANDARDISED COGNITIVE TEACHING INTERVENTION
The low scores obtained by the subj ects on the initial
intelligence tests emphasise the unsuitability of standard
normative intelligence testing in a culturally diverse
population. A short, group-administered, standardised,
cognitive teaching phase, presented on video, significantly
improved scores on the RSPM. This suggests that dynamic
assessment in this form may be a more sui table method of
assessing the ability of educationally deprived children,
since it addresses some of the limitations of both dynamic
127
assessment and normative testing. These limitations include
Ithe following:
• The time and expertise required in the administration of
dynamic assessment is minimised.
• The difficul ty of separating children who are mentally
handicapped from those who are educationally handicapped,
may be possible.
• The identification of children, who could benefit from
more extensive, individualised testing is possible.
• Some of the arguments put forward questioning the
validity of cross-cultural normative testing, e. g.
cultural setting, test-wiseness and inappropriate
standardisation, (refer to 2.1) may be addressed by this
form of testing. Test-wiseness in particular may be an
important element in assessing people who are not
familiar with the techniques employed, or the reasons for
testing. For example, one of the subjects in this study
asked whether she would receive a certificate for
completing all the tests.
5.3.2 PRACTICE EFFECTS
Control groups who were not pre-tested were incorporated in
this study in order to separate the effects of practice from
those of the intervention. Although Klauer (1993) maintains
that fluid intelligence is susceptible to retest effects,
this was not found to be the case in this research. This
result is consistent with those reported by Diemand et al.
(1991) who found that the correlation between pre- and post
tests in learning potential designs is lower than those
found between the first and second testings in studies of
retest or parallel test reliability. It appears that re-test
128
effects may not be as prevalent in dynamic assessment as
they are in traditional assessment with verbal tests that
assess crystallised intellectual abilities.
5.3.3 THE NON-INTELLECTIVE FACTORS
5.3.3.1 Personality Factors
Of the personality factors tested in this research only
Factor G, Conscientiousness, was significantly correlated to
learning potential scores. A stepwise regression separated
three factors (Conscientiousness, Tough-mindedness and
Proneness to Guilt), that accounted for 22% of the variance
in Learning Potential scores.
Factor G
Low-scorers on this factor are described as opportunistic,
while high-scorers are described as conscientious.
People who score high on Factor G are conscientious,
persevering, determined and responsible and they act
according to accepted societal norms. This trait correlates
positively with success in a variety of tasks, especially
those that require persistence, determination and organised
thinking, as well as those concerned with academic
achievement (Visser et al. 1992).
Conscientiousness has consistently been found to have a
positive effect on learning and academic achievement in the
fields of personality and educational psychology (De Fruyt &
Mervielde, 1996; De Raad & Schouwenburg, 1996; Johnson &
Bloom, 1995). Conscientiousness appears to be a central
factor in learning efficiency.
129
Factor I
Low-scorers on this factor are described as tough-minded,
whereas high-scorers are described as tender-minded.
This factor was negatively correlated to learning potential
scores. People who score low on this factor (tough-minded)
are practical, down-to-earth people with a mature attitude
to life. Decisions are made on practical, logical grounds
and reactions are to obvious facts, rather than feelings.
In Chapter 2, Section 2.5.2 it was postulated that the
maturity of the person who scores low on Factor I, and the
contribution of a high score on this factor to neuroticism,
would suggest that the slightly negative correlation to
learning potential scores could be expected.
Factor 0
Low-scorers on this factor are described as self-assured,
whereas high-scorers are described as having a proneness to
guilt feelings.
People who score high on this factor feel inferior and
inadequate, they are sensitive to people's approval or
disapproval, they prefer quiet interests, are easily upset
by authority figures and are prone to depression, guilt and
remorse if they make mistakes.
In Chapter 2, Section 2.5.2 it was postulated that a low
score on this factor may show a posi tive correlation to
learning potential scores, since it suggests self
confidence, which is one of the traits that describe the
130
ideal student (De Raad & Schouwenburg 1996). Contrary to
this expectation a high score was found to contribute to the
variance in learning potential scores. A tentative
explanation for this finding may be that high scorers on
this factor could have tried harder so that they did not
make mistakes, and also to gain the approval of the tester.
Of these traits only conscientiousness was independently
correlated to learning potential scores. However, the three
traits - conscientiousness, tough-mindedness and proneness
to guilt, collectively influence learning potential scores.
Both Feuerstein (1979) and Sternberg (1996) maintain that
personality and learning are inextricably linked. This
research partially supports their arguments. However, some
factors peculiar to this research may have had an effect on
the results.
• Since the relationships between both extroversion
and emotional stability and learning have been found
to be age-related, the age of the subjects in this
study may account for the independence of these
factors and learning potential scores.
• The impersonal nature of the assessment techniques
and intervention strategy may have had a mitigating
effect on interpersonal characteristics such as
Factors A and E. These factors may be relevant in a
situation where interaction is emphasised.
• Both Carlson (1989) and Guthke (1993) suggest that
dynamic assessment techniques compensate for
inhibiting personal characteristics. Learning
potential scores are therefore less sensitive to
131
environmental influences and the effects of non
cognitive factors are reduced.
5.3.3.2 Motivation
Only one of the moti va tional traits tested, namely
Aggression, was positively correlated to learning potential
scores. A stepwise regression analysis identified this trait
as contributing 6,6% to the variance in learning potential
scores.
Aggression
Aggression has, in general, been found to be associated with
reduced learning ability and poorer academic outcomes
(Sternberg, 1996).
An inter-battery factor analysis performed on the Picture
Motivation Test and the Motivation Questionnaire resulted in
the extraction of six factors (du Toi t, 1983). Aggression
loaded negatively on Factor 1, the achievement factor.
Carver and Scheier, 1992 found that the achievement motive
was positively related to task performance and school
grades. Why aggression and not achievement showed a positive
correlation to learning potential scores cannot be explained
wi thout further research, since thi s finding may be
spurious.
Two factors particular to the subjects in this study need to
be mentioned in this regard.
• The subjects came from what is generally acknowledged to
be a very violent area, and as such .are exposed to
violence on a daily basis. Being in control and
132
exercising self-assertiveness and an internal locus of
control, could possibly necessitate the use of aggressive
behaviours.
• The school has a large number of students and the
facilities are minimal. Assertive, dominant behaviour may
be necessary for achievement.
Although the scores on the aggression index were not
particularly high, the milieu in which these sUbjects live
could mean that overcoming obstacles might necessitate the
use of aggression. In addition, what may be considered
aggressive behaviour in some societies may be viewed as
assertiveness or dominance in a more violent society.
A tentative explanation for this finding may then be that
aggression, when defined in a positive sense as
assertiveness and dominant behaviour, may be a necessary
prerequisite for learning to take place in this
disadvantaged context.
5.3.3.3 Learning Styles
The research results show no significant correlation between
any of the four Learning Styles and learning potential
scores. The hypothesis that subjects who show a preference
for a Theoretical approach to learning would be at an
advantage, was not verified. A regression analysis also
failed to extract any of the four learning styles.
Very little research has been undertaken with students using
the LSQ and none with South African scholars. The only norms
available are for British A-Level students and these may not
be sui table for South African subj ects. More research is
133
necessary to establish the validity of this instrument with
regard to South African learners.
5.3.4 COGNITIVE FACTORS
Traditional intelligence assessment using Cattell's Culture
Fair Intelligence Test yielded a mean 1.0. of 80,6 for the
subjects of this study. This normally indicates below
average intelligence. These results are in line with other
studies where disadvantaged subjects have been found to
score approximately 15 points (approximately one standard
deviation) below the average of the predominantly Anglo
American norm groups on which these tests were standardised
(Jensen, 1969; Rohwer, 1971). The inadequacy of these tests
for the population in this research may result from
differences in child rearing practices, different
expectations and aspirations, different formal and informal
learning experiences, extent of test-wiseness and/or
inappropriate standardisation. These cultural differences
are prevalent throughout South African society.
Traditional intelligence tests are often criticised as
inadequate measures of the cognitive abilities of
educationally or intellectually handicapped children. This
is supported by the findings of this study. The low initial
test scores showed a significant increase after a short,
standardised intervention. In addition, the pre-test scores
on the CCFIT Form A did not correlate with the learning
potential scores. The pre-test scores did not therefore
predict future learning capacity.
These results contradict the findings from other studies,
such as Budoff (1987a) and Ferretti and Butterfield (1992).
134
The results of these studies implied that intelligence
related di fferences would be found when the task required
the simultaneous co-ordination of more than one dimension
and that non-verbal tests were associated with better
learning potential scores (refer to 2.5.1). This may be due
to some of the subtests on the CCFIT being too difficult for
a number of the subjects.
However, Vye et al. (1987) found that intelligence measures
did not predict dynamic performance. They suggest that a
large number of the intellectually handicapped children in
their studies would have been misclassified if static
measures were used exclusively.
Kanfer and Ackerman (1989) maintain that general
intellectual abilities appear to be involved when learners
are confronted with a novel task. However, once the demands
of the task are understood, the relationship between general
intellectual abilities and performance declines. The
teaching intervention in this study may have led to an
understanding of the demands of the test and a concomitant
decline in any correlation between the scores obtained on
the CCFIT and learning potential scores.
5.3.5 TRANSFER EFFECTS
The ability to apply what has been learned to novel tasks or
different contexts, is an important element of dynamic
assessment. As may be seen from the results, the increase in
scores from The CCFIT Form A to Form B was positively
influenced by an interaction of the teaching intervention
and practice. This transfer gain was not correlated to
cogni tive ability measured by the RSPM pre-test (Pearson's
135
Correlation 0,070). This is in line with the finding that
the learning potential scores were not correlated to general
cognitive ability as measured on CCFIT Form A (refer to
5.3.4). These resul ts are contrary to a study by Campione
and Ferrara (Campione & Brown, 1987) who found that transfer
measures were strongly related to ability measures. In fact,
in their study, transfer was the best discriminator among
various ability groups.
Another important finding of this research was that the
transfer score (CCFIT Form B CCFIT Form A) was not
correlated to the learning potential scores (RSPM post-test
RSPM pre-test) (correlation coefficient 0,311). This
suggests that the subjects whose learning potential scores
increased due to the teaching intervention were independent
of those who showed gains on the CCFIT scores. This implies
that transfer may be more complex than near or far transfer.
Two forms of transfer may be postulated:
I. A form of transfer where there is a gain on both the
learning potential test and the transfer test but these
gains are independent of each other,
II. A form of transfer where there is a gain on both the
learning potential test and the transfer test and there
is a positive correlation between those who gain on the
original tests and those who gain on the transfer
tests.
The first of these two forms of transfer was found in this
study. The subjects who showed learning potential gains were
not the same as those who showed gains on the transfer test.
Since the results show that the transfer gains in this study
were a result of an interaction between learning and
136
practice, some learning may have taken place even though no
significant gains were recorded for the learning potential
test.
Generalisation took place between Set Variations 1 and
Raven's cognitive tasks. However, the items of the CCFIT
were of a different nature, as they did not assess
analogical reasoning to any s igni ficant degree. Inductive
reasoning and complex abstract reasoning of a conditional
propositional nature is built into many of the items.
Generalisation did not take place, as the learners were not
cognitively trained to carry out these tasks. Furthermore,
the difficulty level of the items was too high in comparison
to Set variations or Raven's Standard Progressive Matrices
for learners who are generally below average intellectual
functioning.
5.4 CONCLUSIONS
This research has concentrated on the identification of
extraneous variables that may affect the efficiency of
learning during dynamic assessment. A short standardised
teaching intervention produced significant changes in post
test scores on both the near transfer test (RSPM) and also
stimulated the subjects to use what they had learned with
some flexibility (on the CCFIT) This form of testing is not
redundant - static and dynamic testing do produce different
estimates of learning ability. In fact, in this study
learning potential and transfer scores were independent of
general cognitive ability.
The role of the non-intellective factors, other than
conscientiousness, in dynamic assessment is still not clear
137
from this study and more research is needed to clarify these
issues.
5.5 LIMITATIONS OF THIS RESEARCH
This research is limited by the fact that only general
cognitive ability was examined. This precludes any aspects
of specific learning, such as learning Mathematics or
English.
The subjects were high school learners from a single grade,
in one school, in a previously disadvantaged community.
Using a sample from the Black population means that the
subj ects come from diverse cultural backgrounds with
different home languages. One or more of the problems
associated with cross-cultural assessment (refer to Chapter
2, section 2.1) could contaminate the results of the tests.
Furthermore, this study is concentrated at a specific point
in time. It does not relate to sustainable performance. A
longitudinal study would be necessary to ascertain whether
improved performance can be maintained over a longer period
of time.
The conditions, under which the testing for this research
took place, were problematic from a psychometric point of
view. The facilities were inadequate and too many subjects
were tested together. Passing traffic often distracted the
subjects and disturbed the testing. During the teaching
phase 60 subjects were in one classroom that could seat
approximately 50 students. This meant that some of the
subjects had to stand and others shared desks. Although far
138
from ideal, these are the conditions under which these
students are taught.
Of the instruments used in this research, the Learning
Styles Questionnaire was probably the least suitable. This
instrument has not been properly validated with adolescents
and is therefore not an appropriate measure of learning
styles for this kind of research until its item content and
psychometric properties have been improved.
The complexity differential between the cognitive tasks used
in mediation and the transfer test is an important factor in
this research. It seems that the CCFIT is more suitable for
research with matriculants or subjects with tertiary
educational qualifications. Ideally, transfer should be
measured with a cuI ture- fair instrument of moderate
difficulty level items in comparison with the items of the
mediation instrument used in the research. An instrument of
this nature is not available at present.
139
Chapter 6
SUMMARY AND RECOMMENDATIONS
6.1 INTRODUCTION
This chapter presents a summary of each of the foregoing
chapters. Recommendations for future research in this field
and practical uses of these results are suggested.
6.2 CHAPTER 1 - INTRODUCTION
Due to the disparity in the quality and availability of
education across population groups in South Africa,
traditional psychometric tests and past academic performance
are not always the most suitable criteria for the selection
of the most suitable candidates for educational and career
opportuni ties. Dynamic assessment has been proposed as one)
possible alternative to normative testing whenever doubt> \
exists as to the fairness of traditional testing methods. ) ...."'''
The majority of dynamic assessment procedures have
concentrated on individualised test-train-retest protocols.
These methods are both time consuming and require highly
trained administrators. In addition, the lack of knowledge
concerning examiner effects and the incomparability of
scores due to lack of standardisation prevent dynamic
assessment from being acceptable from a psychometric point
of view.
140
That cogni tive and non- intellective factors play a role in ")
psychometric assessment is not disputed. However, the extent
and significance of these factors is as yet unclear.
This research focuses on learning potential scores, and uses
a standardised teaching protocol within a test-train-retest
format. General skills are targeted. The following questions
are examined:
I. Is a short, group administered dynamic assessment
procedure using a standardised intervention protocol
presented on video, viable?
II. Does current general intellectual ability have a
significant effect on learning potential scores?
III. Do non-intellective factors such as certain personality
factors, motivational traits and learning styles have a
significant effect on learning potential scores?
IV. Is transfer from pre-mediation to post-mediation
cognitive functioning statistically significant?
This study is exploratory. It concentrates on one community,
at a specific point in time.
6.3 CHAPTER 2 - LITERATURE REVIEW
Dissatisfaction with normative testing methods, the work of
Feuerstein (1979) and the translation of Vygotsky's (1978)
Mind in Society: The development of higher psychological
processes, which proposed the ~zone of proximal development"
(ZPD), has resulted in research into many aspects of dynamic
assessment since the 1970's.
141
Six models of dynamic assessment have been identified in the
literature. These are based on a test-train-retest formula.
The six models are:
The Test-Train-Retest Gain Score Model (Budoff,
1974 )
The Cylindrical Model of Learning Potential
Assessment (Feuerstein, 1979)
Testing-the-limits (Carlson & Weidl, 1978)
Graduated Prompting (Campione & Brown, 1978)
A ~Continuum of Assessment ServicesH model (Burns
et al., 1987)
Train-within-test (Hessels, 1996).
The researchers generally report that dynamic assessment
leads to more accurate prediction and classification of
subjects than unaided test scores.
Results of research in dynamic assessment, personality and
educational psychology suggest that learning is influenced
by a complex and dynamic interaction between cognitive,
affective and motivational factors (Volet, 1996). However,
the influence of these factors on learning potential scores
is not clear.
Empirical findings from a variety of studies suggest the
following results may be anticipated:
1. Intelligence-related differences in learning ability
may be found in both Raven's Standard Progressive
Matrices and Cattell's Culture Fair Intelligence Test
since both these tests are non-verbal (Budoff, 1987 a)
and more than one source of information has to be co
ordinated (Ferretti & Butterfield, 1992).
142
2. If a short, standardised, group administered mediation
is viable, transfer should take place.
3. The High School Personality Questionnaire measures 14
personality factors and 2 second-order factors.
Extraversion and anxiety (second-order factors), Factor
I (tender-mindedness), Factor -E (submissiveness) and
Factor -F (soberness) may be uncorrelated or slightly
negatively correlated to learning potential scores.
Factors A (outgoing), C (emotional stability), -0
(sel f-assurance), Q2 (self-sufficiency) and Q3 (high
self-sentiment integration) may show positive
correlations to learning potential scores. Factor G
(conscientiousness) has consistently been correlated to
learning ability.
4. Factors that may be positively correlated to learning
potential scores measured by the Picture Motivation
Tests are Cognitive Structure, Scholastic Achievement,
Endurance, Understanding, Order and General
Achievement. Aggression may be negatively correlated to
learning potential scores.
5. Honey and Mumford (1982) suggest that matching learning
styles with teaching style should aid learning. The
mediation is presented in a theoretical style so
subjects with a preference for this style should be at
an advantage during the learning phase.
This research aims to address some of the inadequacies that
researchers have highlighted concerning dynamic assessment.
For example, group administration of a short, standardised
test addresses the issues of length of time and expertise
required when administering learning potential tests and it
is more psychometrically acceptable. In addition, an attempt
143
is made to clarify the role of cognitive and non
intellective factors in dynamic assessment.
6.4 CHAPTER 3 - RESEARCH METHODOLOGY
6.4.1 THE AIM OF THIS STUDY
In this research the effects of the following factors on
learning potential scores are examined:
General cognitive ability measured by Cattell's
Cui ture Fair Intelligence Test Form A (refer to
section 3.8.6).
Fourteen personality traits measured by the High
School's Personality Questionnaire (refer to
section 3.8.3).
Ten motivational factors measured by the Picture
Motivation Tests (refer to section 3.8.4)
Four learning styles measured by the Learning
Styles Questionnaire (refer to section 3.8.5).
Learning potential scores are obtained from the difference
between the pre- and post-test scores on Raven's Standard
Progressive Matrices (refer to section 3.8.1). The training
phase is standardised according to a Theorist learning style
(refer to section 3.8.5) and is presented on video using ')
Feuerstein's Set Variations 1 as a mediation tool (refer to )
section 3.8.2). Transfer performance is measured as the
difference between the pre- and post-test administration of
Ca ttell' s Culture Fair Tests Forms A and B, respectively
(refer to s~ction 3.8.6)
144
6.4.2 HYPOTHESES AND DATA ANALYSIS
The hypotheses tested in this research are as follows:
H1 : A standardised teaching intervention by means of
videotape has no effect on Learning Potential scores. A one
tailed t-test was conducted to test this hypothesis.
Variances were tested using an F-test. In the case of equal
variances a conventional t-test was used, otherwise the
Aspin-Welch modified t-test was used.
H2 : There is no statistically significant practice effect
between the pre- and post-test scores. Since normality was
rejected using the Omnibus Normality Test, the Kruskal
Wallis One-Way Analysis of Variance test was used to
determine the presence of practice effects.
H3 , H4 , and H5: Personality factors, motiva tional traits and
learning styles are not significantly related to learning
potential scores. Pearson's Correlation Coefficient was used
to measure these hypotheses. A t-test was used to establish
whether the correlation coefficients were significantly
different from zero. In addition a regression analysis was
performed to establish whether a combination of two or more
variables significantly predict learning potential.
H6 : The general cognitive ability pre-test scores are not
significantly related to the subject's learning potential
scores. Pearson's Correlation Coefficient was used to test
this hypothesis. A t-test established whether these
coefficients were significantly different from zero.
145
H7 : The standardised teaching intervention by video, using
Feuerstein's LPAD Set Variations 1 as a mediation tool, has
no effect on transfer scores. A one-tailed t-test was
conducted to test this hypothesis. Variances were tested
using an F-test: in the case of equal variances a
conventional t-test was used, otherwise the Aspin-Welch
modified t-test was used.
He: The learning potential scores are not significantly
correlated to the transfer gain scores. Pearson's
Correlation Coefficient was used to test this hypothesis. A
t-test was used to establish whether these coefficients were
significantly different from zero.
6.4.3 SUBJECTS
The sample consisted of 120, mostly Black, Grade 10 learners
from a Johannesburg high school. 44,2% were males and 55,8%
were females.
6.4.4 EXPERIMENTAL DESIGN
A Solomon Four-Group design was chosen for this research
(Kerlinger, 1986).
146
GROUP 1
EXPERIMENTAL
GROUP 1 1---
Pre-test
Mediated
Lesson
Post-test
N =: 30 "-----
Figure 6.1
THE SOLOMON 4-GROUP DESIGN
GROUP 2 GROUP 3
Experimental CONTROL
Group 2 GROUP 1
No Pre-test Pre-test
Mediated No lesson
Lesson
Post-test Post-test
N = 30 N =: 30
-GROUP 4
Control -
Group 2
No Pre-test
No lesson
Post-test
N =: 30 -~
6.4.5 PROCEDURES
Assessment took place in three phases. During the initial
testing phase all the subjects completed the Learning Styles
Questionnaire, Cattell's Culture Fair Intelligence Test,
Scale 2, Form B, the High School Personality Questionnaire
and the Picture Motivation Tests. One week later half the
experimental groups and half the control group did the
Ravens Standard Progressive Matrices. The experimental group
then completed the Set Variations 1. A week later all the
subj ects did Raven's Standard Progressive Matrices, and a
further week later Cattell's Culture Fair Intelligence Test,
Scale 2 Form B.
147
6.5 CHAPTER 4 - RESEARCH RESULTS
The following results are reported in Chapter 4:
HI: The standardised teaching intervention had a
statistically significant effect on learning potential
scores.
H2 : There is no evidence of a practice effect from the
first to the second administration of the RSPM.
H3 : Only Factor G (conscientiousness) correlated with
learning potential scores. A regression analysis yielded
three variables that account for 22% of the variance in
learning potential scores. These factors are G
(conscientiousness), I (tough-mindedness) and 0 (proneness
to guilt).
H4 : The only factor that correlated significantly with
learning potential scores was Aggression. The regression
analysis indicated that this trait accounts for 6,6% of the
variance in scores.
Hs : No statistically significant correlation between the
learning styles and learning potential scores was found. In
addition, none of the learning styles proved significant
predictors of learning potential in the regression analysis.
H6 : There is no significant correlation between scores on
Cattell's Culture Fair Intelligence Test Form A and learning
potential scores.
148
H7 : The gains scored from the CCFIT Form A to the CCFIT
Form B can be explained by an interaction of the mediation
and practice effects.
He: There is no significant correlation between the pre
and post-test difference scores on the CCFIT and learning
potential scores.
6.6 CHAPTER 5 - DISCUSSION AND CONCLUSION
A short, standardised teaching intervention, presented on
video, produced significant changes in the post-test scores
of the learning potential test (RSPM). It also stimulated
the subjects to use what they had learned with some
flexibility (on the CCFIT), although the latter result is
contaminated by practice effects.
General intellectual ability scores (CCFIT Form A) did not
predict learning potential or transfer scores. Some of the
items on the CCFIT may have been too difficult for the
subjects. Another explanation may be that understanding the
demands of the task could cause a decline in the
relationship between intellectual ability and task
performance (Kanfer & Ackerman, 1989).
The transfer scores (CCFIT Form B - CCFIT Form A) were
influenced by both the teaching intervention and practice.
These transfer scores were not related to the learning
potential scores i.e. the subjects who gained on the
learning potential scores were not the same as those who
gained in transfer scores. This may be as a result of the
influence of practice effects or because the items on the
149
CCFIT were much more difficult than those in either the
Var.l or RSPM.
Of the personality factors assessed only conscientiousness
was significantly related to learning potential scores. A
regression analysis yielded three factors
conscientiousness, tough mindedness and proneness to guilt,
which accounted for 22% in the variance of learning
potential scores. Conscientiousness has been found to have a
posi tive effect on learning and academic achievement by a
number of researchers. Tough-mindedness has not been
researched, but the practical, down-to-earth and mature
elements of this factor suggest that it could aid learning.
Subj ects with a high score on proneness to guilt tend to
feel inferior, inadequate and sensitive to approval. It is
postulated that these subjects may have tried harder to
please the examiner.
Aggression was the only motivational factor that was
significantly correlated to learning potential scores. This
factor accounts for 6,6% of the variance in learning
potential scores. It is postulated that in order to succeed
in the context of the violent society in which they live the
subjects might need to be aggressive or assertive.
None of the learning styles assessed had any significant
impact on learning potential scores. The LSQ needs to be
researched in order to establish its validity in the South
African context.
Limitations of this research include the following:
Only a general cognitive ability was examined.
150
The subjects were from one grade in one school.
The subjects have a diverse cultural and language
background.
The study is concerned with a specific point in
time, it cannot be ascertained whether the gains
can be maintained.
Testing conditions were not optimal.
The LSQ needs improvement in item content and
psychometric properties.
The CCFIT may have been too difficult for the
level of the subjects.
6.7 RECOMMENDATIONS FOR FUTURE RESEARCH
The short standardised teaching intervention used in this
study may be a viable method of testing various hypotheses
associated with dynamic assessment.
The psychometric properties of the LSQ need to be upgraded
and improved or a more valid instrument (e.g. The Learning
Styles Inventory, Dunn, Dunn & Price, 1989) should be
considered. Employing different teaching styles during the ,- .._~
intervention phase may serve to clarify the role of this
variable on the learning process.
Among the motivational and personality factors stUdied in
this research, aggression (self-assertiveness) needs to be
examined more carefully since this may have been a spurious
resul t.
Why do some subjects transfer what they have learned, while
others do not? How and when does transfer of learning to
151
novel tasks take place? Are there two forms of transfer?
These are some questions that need to be answered in order
to clarify this important aspect of dynamic assessment.
The simultaneous assessment of a large number of subj ects
requires good facilities and a number of examiners. It would
be preferable to test smaller groups to ensure that all the
subjects understand the instructions for each test.
During the initial testing phase four tests were
administered with short breaks between each test. It would
be preferable to spread this testing phase over two sessions
to prevent the subjects from becoming bored or tired.
The practice items on Set Variations 1 were not checked to
ensure that the subj ects understood what was required of
them during mediation. A form of testing-the-limits could be
incorporated into this phase by repeating the lesson for
those subjects who could not cope with the practice items.
A mediation protocol, presented on video, could be produced
for a variety of specific cognitive skills, including school
subjects.
6.8 RECOMMENDATIONS FOR PRACTICAL USE OF THIS RESEARCH
Education and training are important areas that need to be
developed in South Africa. Selection criteria for sui table
candidates for tertiary education and job training are
generally based on past academic results and/or traditional
psychometric tests. Neither of these is suitable in South
Africa due to the inequities of the educational system and
152
the ~~ltural diversity of the population. Dynamic assessment
could overcome these problems.
Dynamic assessment is essentially an individual method of
testing. Time and expertise constraints limit the number of
people who could benefit from this form of assessment. A
group administered, short, standardised version, presented
on video would ensure that this form of assessment could be
used with larger numbers of people and in different
contexts.
Many businesses have to deal with the reality of affirmative
action. This often means that the previously disadvantaged
applicants need to be trained for specific positions. It is
very expensive to train personnel only to find that they are
not suitable candidates for the position. An assessment
procedure such as this, targeting specific skills, could be
a useful tool for selection of suitable candidates for
training. A similar format could be used in the selection of v/
students into tertiary institutions.
other uses for this form of dynamic assessment could include
some of the following situations:
• It could make it possible to discriminate between those
who are educationally handicapped and those who are
mentally handicapped.
• It could help to identify those who would benefit from a
more intense individual form of assessment in order to
ascertain strengths and weaknesses in cognitive
functioning, e.g. the LPAD.
• Deaf people could be assessed using a video in sign
language, which does away with the need for a tester to
be both a qualified test administrator and proficient in
sign language.
153
Finally a more elaborate mediation programme could be
developed into a teaching tool. Such a programme could be
divided into a series of self-contained modules targeting
specific skills. After each module, students would be
required to complete certain assignments and reach a certain
level of competence, before tackling the next module. This
could be beneficial for learners who have difficulty with
specific subjects especially maths and science, where the
pass rate in schools in South Africa is extremely low.
154
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