AN
ANALYIS OF SELECTED COGNITIVE ABILITIES OF SECONDARY
SCHOOL STUDENTS AND ITS RELATIONSHIP WITH ACADEMIC
ACHIEVEMENT
[Jurnal
Psikologi. 1998]
John Arul Phillips
INTRODUCTION
The factors influencing academic
achievement has been a
much researched area
and one of the
dominant factors in
Malaysian schools is the socio-economic background
of the
learner. In a recent study it was shown that
socio-eocnomic
factors
played an important role
in influencing academic
achievement in
the primary grades
and its influence was
relatively
less among secondary school
students (Leong et.
al, 1992).
The main focus of this study is to determine the
extent to
which the cognitive abilities of learners,
which
has been
operationally defined to include spatial aptitude,
deductive reasoning, analogical
reasoning and mechanical
comprehension; influences
their performance in the various
school
subjects.
Lohman (1979) in a review of studies on
spatial ability
identified
two main
aspects of spatial
ability, namely;
spatial orientation
and spatial visualisation. Spatial
orientation
involves the ability to
imagine how a
given
object
or set of
objects would appear
from a spatial
perspective
different from that in which
the objects are
shown. Usually, spatial-orientation tasks require
people to
reorient
themselves relative to the object
or objects in
question. Spatial visualisation requires
complex mental
rotation of
one or more visualised objects
such as those
involved in
mental paper folding or mental rearrangement of
pieces of an
object to form the whole object.
Guay and
McDanial(1977) found that spatial
ability of
school
children was significantly correlated with achievement
in
mathematics. Lam (1989) found similar evidence among 16
year old
Malaysian students but it was confined to a selected
aspect of
spatial ability based
on the Punch Holes Test.
More specifically, Fennema and Sherman (1977) showed that
it
was spatial visualisation that was more importantly
related
to mathematics achievement.
Besides
mathematics, spatial
ability was
found to be strongly linked to achievement in
science (
1980).
Gender differences in
spatial ability has
been
extensively investigated. Studies by
Johnson and Meade,
(1987)
and Wittig and Peterson (1979) showed that males have
better
spatial ability than females
beginning from early
adolescence
and continuing through adulthood. Wong
(1992) in
a study of 16
year old Malaysians found that
males scored
significantly
higher in spatial ability than females.
Gender
was the
best single predictor
of spatial ability
and
accounted for
about a third of total variance. Also, there
was evidence
to indicate that
students from high
socioeconomic background were
better in spatial
ability
compared to
their school-mates from
low socioeconomic
families.
It has been suggested that
reasoning occupies a
central
position in explaining intellectual abilities
(Rips, 1984).
Two types
of reasoning have
been identified, that
is
deductive
reasoning and inductive reasoning.
Deductive reasoning has
been defined as an attempt by
the learner
to integrate elements of the old
information in
the
construction of new information (Sternberg, 1982). It is
reasoning based
on a given
premise that is sufficient to
reach a valid
conclusion. A number of
different kinds of
deductive reasoning problems have been studied. For example,
mathematical word
problems, propositional reasoning,
and
syllogistic reasoning
all involve primary
deductive
inference. Shaver and
his associates (1974)
found that
performance
on deductive reasoning tasks was highly correlated
with performance on verbal,
spatial and abstract reasoning
ability
tests. In a review of research on deductive reasoning
among
adults, Sternberg (1982) observed that
subjects differ
in the
strategies they use to solve linear syllogisms. The
large
majority of subjects used a mixed
spatial-linguistic
strategy while
a small number
use either a
spatial or
linguistic
model.
In inductive reasoning the information
contained in the
premises of a
problem is insufficient to reach a
conclusion.
A number
of different kinds of inductive reasoning problems
have
been studied and
the most common
being analogical
reasoning. An analogy is a problem of the form A is
to B as
C is to D (A:B: :C:D),
where, in most instances, the last
term is omitted
and must be filled in, selected from among a
number of
options. Analogies can be presented in any of a
number of
different kinds of
content, such as
verbal,
geometric or
schematic-picture. In an early study, Lunzer
(1965) presented students between 9-17 years
of age with
verbal
analogies and found that children had great difficulty
with even
the simplest analogies until
about nine years of
age, and did
not show highly successful performance until the
age of
11. Whitely (1977) showed that analogical reasoning
was closely related to scores obtained on standard
measures
of mental
ability. Phillips (in press) found that 13 year
old students
in a Malaysian school who
performed well on
analogical
reasoning tests were also high academic achievers.
scientific
thinking.
Mechanical
comprehension
requires the respondent
to
apply simple
principles of physics
and mechanics in
responding to
questions concerning the operations of common
machines, tools,
and vehicles. The subject is required to
predict the
outcome of mechanical activities,
or to reason
backwards from effects to probable mechanical
causes (Murphy
and
Davidshofer, 1991). Studies by Ghiselli
(1966) has shown
moderate
correlations with performance in training
courses
and job
performance of machinists,
mechanics and machine
operators.
Specifically, the
study sought to
find answers to
the following
questions:
1. To what extent is academic
achievement related to the
cognitive
abilities (i.e. spatial aptitude, deductive
thinking,
analogical reasoning and mechanical
comprehension)
of secondary school students?
2. Does the
socioeconomic background of
students
influence
their cognitive abilities?
3. Is there a difference in
cognitive abilities between
male
and female students?
METHOD
a. Subjects
The sample of 106 Form One
students were selected from
one secondary school
in the Federal
Territory of Kuala
Lumpur. The subjects, between the ages of 12-13 years
of age
were selected
from three intact classes of high,
average and
low academic
ability students as streamed by the school based
on their UPSR
scores. There were 44 males and 62 females.
b. Instrumentation
An instrument called
the Cognitive Ability
Test,
consisting of
84 items was adapted and developed consisting
of 6 subtests
(see Table 1). The mechanical comprehension
subtest and
parts of the spatial ability subtest were adapted
from the
Differential Aptitude Test
(DAT) by Bennett,
Seashore and
Wesman (1963). Parts of
the analogical
reasoning subtest
was adapted from
Test Your Child's
Reasoning Ability, Booklet I & II,
by Headway, Hodder
&
Stoughton Ltd.
by the
researcher.
The instrument was
pilot-tested with a
group of 75
randomly
selected Form One students wherein respondents
were
encouraged to
comment on the items. Respondents
commented on
the items
especially with regards to clarity of instructions,
the difficulty of
understanding the items and clarity of
presentation of
the figure items.
Based on their
suggestions, relevant
modifications were made
to the
instrument. To obtain an indication of the
reliability of
the CAT,
a odd-even split half reliability test was carried
out and the
coefficients are reported
in Table 1. The
reliability coefficient for
the CAT is 0.85 which may be
regarded as
high. The reliability coefficients
for the
individual
subtests reveal wide variation. For
example, the
reliability
coefficient for the Spatial
Orientation subtest
was 0.69
compared to 0.41 for the
Mechanical Comprehension
subtest. However, all reliability coefficients
obtained were
significant
at p = < 0.01.
________________________________________________
Spatial Orientation (SPO) 0.69 **
(14 items)
Spatial Visualisation (SPV) 0.62 **
(16 items)
Verbal Analogical Reasoning
(VAR) 0.58 **
(14 items)
Figure Analogical Reasoning
(FAR) 0.62 **
(10 items)
Deduction (DED) 0.63 **
(14 items)
Mechanical Comprehension
(MEC) 0.41 *
(16 items)
_______________________________________________
Cognitive Ability Test
(CAT) 0.85 **
(84 items)
_______________________________________________
note: ** p = < 0.001
* p = < 0.01
Table 1:
Reliability Coefficients for
the
Cognitve Ability Test
(CAT) and Subtests
c. Operational Definition
Academic achievement was determined by performance
in
selected
subjects at the primary and secondary school levels.
Based on
the Primary School Evaluation Test (UPSR) grades
were obtained
for Bahasa Melayu, Mathematics and English.
To
obtain a
composite score, points were assigned
wherein grade
A was assigned 5 points, grade B was
assigned 4 points, grade
C was
assigned 3 points, grade D was
assigned 2 points and
grade E was
assigned 1 point. For academic achievement
at
the secondary school level, class test scores were obtained
for seven
subjects namely Bahasa
Melayu, English,
Mathematics, Science, History, Geography and Living Skills,
and a total
composite score was computed.
RESULTS
a. Cognitive Abilities and Academic Achievement
Based on the composite score of
performance in the UPSR,
subjects were
divided into high and
low academic ability
using the mean
as the cut-off
point (see Table
2).
Generally, high ability students (M = 60.3)
outperformed low
ability students (M =
50.8) on total cognitive ability and
the
difference was significant at p = <
.001. However, the
performance of
subjects on the CAT was low considering that
the total
score possible is 84.
------------------------------------------------------------
Academic Performance
High Low
df t
value
(n=50) (n=56)
------------------------------------------------------------
Primary School M
= 60.3 50.8
104 5.81 ***
Evaluation
(UPSR)
Secondary School M =
61.2 49.8 104
7.65 ***
Class Tests SD =
8.3 6.8
____________________________________________________________
Nota: *** p = < 0.001
Table 2: Mean Scores and Standard
Deviations of Performance
on the
CAT according to Academic Ability
Students were
also grouped according to ability levels
based on
performance in class tests at the
secondary school
level. Using the mean as a cut-off point (M = 407),
students
were divided into high and low ability. The performance of
high academic
ability students on total cognitive ability was
higher (M =
61.2) than low academic ability students
(M =
49.8). This
difference was statistically significant at p =
< 0.001.
_____________________________________________________________
SPO SPV VAR
FAR DED MEC
Cognitive
Ability
Test
BAHASA MELAYU .34 .18
.36 .28 .31
.11 .40
ENGLISH .33 .34
.39 .43 .50
.42 .60
MATHEMATICS .36 .43
.31 .38 .44 .30 .56
SCIENCE .31 .38
.41 .36 .51
.36 .59
GEOGRAPHY .29 .33
.34 .26 .43
.18 .46
HISTORY .30 .22
.40 .35 .42
.24 .48
LIVING SKILLS .28 .14
.27 .22 .49 .07 .37
ACADEMIC (Secondary) .39 .38 .43
.41 .53 .34
.62
ACADEMIC (Primary) .34 .35
.38 .36 .38
.36 .55
_____________________________________________________________
Note:
SPO = Spatial orientation
SPV = Spatial visualisation
VAR = Verbal analogical reasoning
FAR = Figure analogical reasoning
DED = Deduction
MEC = Mechanical comprehension
Table 3: Correlation Coefficients
between School Subjects
and
Performance on the CAT and Subtests
Further the relationship between academic
achievement
and the
individual subtests of the
CAT was computed (see
Table 3). The correlation between total
cognitive ability
and overall performance
on class tests
at the secondary
school level
was 0.62 and in terms of individual
cognitive
abilities, the correlation was especially high for
deduction
(0.53). The
correlation between total cognitive ability and
performance
in the UPSR was 0.55 with none of the
subtests
being more
highly correlated with academic achievement.
A breakdown by subject areas at
the secondary school
level revealed that
English (0.60), Science
(0.59) and
Mathematics (0.56) correlated highly
with total cognitive
ability compared to
the other subject areas. The lowest
coefficient
of correlation was reported for
Living Skills
(0.37).
In terms of
specific cognitive abilities
and the
individual
subject areas, deductive reasoning was reported to
be more
highly correlated with performance in Science
(0.51)
and English (0.50)
compared to the
other subjects. The
correlation between mathematics
and spatial orientation
(0.36)
and spatial
visualisation (0.43) was relatively low.
However, among
the seven school
subjects, spatial
visualisation
and spatial orientation correlated highest with
mathematics
and lowest with Living Skills.
Surprisingly, the
correlation
between spatial ability
and geography was
relatively
low. Also, there
was almost zero
correlation
between mechanical comprehension
(0.07) and performance in
Living Skills.
___________________________________________________________
Variables Multiple R
R Increase in R Beta
entered
ACAD .6284 .3945
.6284 .6461
GEND .6376 .4065
.0092 .1108
SEST .6380 .4071
.0004 .0260
___________________________________________________________
Note:
ACAD = Academic Achievement
(Secondary school tests)
GEND = Gender
SEST = Socioeconomic Status
Table 4: Stepwise Multiple
Regression Analysis with
the
Cognitive Ability Test as the Dependent
Variable
The data was subject to a
step-wise regression
analysis
(see Table
4). The three
variables entered were academic
achievement
score, gender and socioeconomic status with total
cognitive
ability as the dependent variable. The multiple R
obtained was 0.638
and the R square was 0.407. In other
words, 40.7%
of the variance
was contributed by
the
combination of
the three variables entered in
the equation
while the
remaining variance was unaccounted for. Among the
three variables
entered, 39.4% of
the variance was
contributed by
academic achievement while
gender and
socioeconomic contributed only
minimally (1.3%). In other
words, academic achievement is the best single
predictor of
the selected
cognitive abilities studied.
b. Socioeconomic Background and Cognitive Ability
Based on the occupation of the father and
mother (if
any) of
the students, the
sample was classified as high
socio-economic
status (HSES) and low socio-economic status
(LSES). For example, the student who stated that his or her
father was a
security guard or labourer was
classified as
LSES while
a student whose
father is an
executive or
professional
was classified as HSES.
------------------------------------------------------------
Socio-Economic
Status
High Low
t-value
(HSES) (LSES)
n=43 n=63
------------------------------------------------------------
Spatial Orientation
11.0 10.7 1.34
(2.2) (2.3)
Spatial Visualisation 10.8
9.4 1.62
(2.6) (2.6)
Verbal Analogical 10.6 9.4 2.72**
Reasoning (1.9) (2.6)
Figure Analogical 8.1 7.5 1.62
Reasoning (2.0) (2.1)
Deduction 9.2 8.6
1.37
(2.3) (2.4)
Mechanical Comprehension 9.1
8.6 1.37**
(2.9) (2.0)
___________________________________________________________
Cognitive Ability Test 59.1
53.6 3.02*
(9.7) (8.8)
____________________________________________________________
Note: * p = <0.05
** p = <0.01
The figures in brackets are standard
deviations
Table 5: Mean Score and Standard
Deviations for the
CAT and Subtests According
to Socioeconomic
Status
Overall, students from
high socioeconomic background
scored higher
(M=59.1) than students from low socioeconomic
background (M=53.6) on the Cognitive Ability Test
(see Table
5). The difference was
significant at p = <.05
level.
Consistently, HSES students scored higher than LSES
students
on all
the six subtests.
But, the difference
was
statistically significant
only for verbal
analogical
reasoning and
mechanical comprehension wherein students
from
high income
families scored higher
(M=10.6 and M=9.1
respectively) than
students from poorer
socioeconomic
background
(M=9.4 and M=8.6 respectively).
c. Gender and Cognitive Ability
Data was
also analysed according to gender
(see Table
6).
Overall there were
no significant differences
in
cognitive ability between
male and female
students even
though the
males scored slightly higher (M=56.7) than females
(M=55.2). However, performance on the individual subtests,
revealed that
male students (M=10.72)
scored higher than
female students (M=9.64)
on spatial visualisation. This
difference was significant
at p = <.05 level. Males also
scored
slightly higher than females in both verbal and figure
analogical
reasoning as well as mechanical comprehension, but
the difference
was not significant. Female subjects, on the
other hand
scored slightly higher
than their male
counterparts
in spatial orientation and
deduction, but the
difference
was too small to be significant.
-------------------------------------------------------------
Males Females
t-value
n=44 n=62
-------------------------------------------------------------
Spatial Orientation 10.6 11.0 0.99
(2.5) (2.1)
Spatial Visualisation 10.7
9.6 2.05*
(2.6) (2.6)
Verbal Analogical 10.0 9.8 0.31
Reasoning (1.9) (2.6)
Figure Analogical 8.0 7.5 1.07
Reasoning (2.1) (2.1)
Deduction 8.6 9.0 0.78
(2.3) (2.4)
Mechanical Comprehension 8.6
8.0 1.24
(2.9) (2.0)
____________________________________________________________
Cognitive Ability Test 56.7
55.2 0.78
(10.1) (9.1)
____________________________________________________________
Note: * p = <0.05
The figures in brackets are
standard deviations
Table 6: Mean Scores and Standard
Deviations of the
CAT and the Subtests According
to Gender
DISCUSSION
The relationship of academic
ability to differences in
cognitive abilities measured
is significant. Consistently,
high ability
learners, whether based on primary or
secondary
test
scores, significantly outperformed low
ability learners
on total
cognitive ability. According to
school subjects,
interestingly performance in
English and Science is more
related to
the selected cognitive abilities of students
as
reflected in
the relatively high coefficients reported. It
is probable
that in these two
school subjects, cognitive
skills such
as deductive thinking and
analogical reasoning
are
encouraged.
Surprisingly, the mechanical comprehension
subtest was a
poor predictor of
performance in the subject Living Skills
though it
teaches technical elements such as
understanding
and repairing of
household appliances. However, Living
Skills also includes non-technical
aspects such as commerce
which may not be related to mechanical
reasoning. The study
found that
among the school subjects, mathematics
reported
the highest
correlation with spatial
ability which is
consistent
with the findings of Guay &
McDanial (1977) and
Wong (1992). Overall,
academic achievement plays a
significant
role in influencing the cognitive abilities
of
students in
the sample studied.
The higher
cognitive abilities of students from high
income
families suggest that such
abilities may be
better
nurtured in
these families. Greater opportunities
for the
development
of such skill may have been made available
for
learners from
such advantaged families
through reading
materials, thought
challenging games and
activities and
perhaps a
generally more conducive
environment that
encourages
such types of thinking.
In terms
of gender, males
outperformed females in
spatial
visualisation. This finding is partially consistent
with earlier studies wherein females scored
lower in spatial
ability than
their male counterparts. Wong (1992)
found that
males
performed better than females in spatial
visualisation
and spatial orientation.
The present study
found gender
differences was
only for spatial visualisation. In fact,
females
scored higher in
spatial orientation than
males
though the difference was not
significant.
Generally, this study reveals
that there is evidence for
individual differences in
cognitive abilities between
students in
the sample and
suggests that the Cognitive
Ability Test be administered to a larger sample
to detect
developmental
differences and the establishment of norms.
REFERENCES
Elmore, P.B. &
Vasu, E.S. (1980). Relationship between
selected
variables and statistics achievement:
Building a
theoretical
model. Journal of Educational Psychology, 48:
116-123.
Fennema, E. & Sherman, J. (1977).
Sex-related differences in
mathematics
schievement, spatial visualisation and
affective
factors.
American Educational Research Journal, 14 :
51-71.
Ghiselli. E.E. (1966). The validity of occupational aptitude
tests.
Guay, R.B. & McDanial, E.D.
(1977). The relationship between
mathematics achievement and
spatial abilities among
elementary school
children. Journal for
Research in
Mathematics Education, 8:
211-213.
Johnson, E.S. &
Meade, A.C. (1987). Developmental patterns of
spatial ability:
An early sex
difference. Child
Development, 58: 725-740.
Lam, S.F.
(1989). Spatial
ability among Form Two and Form
Four pupils
in a rural
secondary school. Unpublished
Masters practicum report, Faculty of Education,
University
of
Lohman, D.F. (1979). Spatial ability:
A review and reanalysis
of the
correlational literature (Tech.
Rep.
No. 8).
Education,
Leong Yin
Ching et. al
(1992). Factors affecting academic
achievement
in Malaysian schools. Report of
the project
funded by
the World Bank
and the Faculty of Education,
Lunzer, E.A.
(1965). Problems of formal reasoning in
test
situations.
Monographs of the Society for Research in Child
Development, 30(2), Serial No. 100,
19-46.
Murphy, K.R.
&
Davidshofer, C.O. (1991). Psychological
Testing:
Principles and Applications.
Phillips, J.A. (1992). Kebolehan pelajar sekolah
rendah
menakul
secara induktif, Jurnal Pendidik dan
Pendidikan,
12. 47-58.
Rips, L.J.
(1984).
Reasoning as a
central intellective
ability. In
R.J. Sternberg (Ed.) Advances in the Psychology
of Human Intelligence, Vol. 2, Hillsdale,
NJ.:
Erlbaum Associates, Publishers.
Sternberg, R.J.
(1982).
Reasoning, problem solving
and
intelligence. In R.J. Sternberg (Ed.). Handbook of Human
Intelligence,
Sternberg, R.J.
(1985).
Understanding cognitive
abilities
from a
cognitive viewpoint. In
B.B. Wolman (Ed.) Handbook
of Intelligence: Theories, Measurement and Applications,
John Wiley & Sons:
mathematics
achievement: Are they related? Sex-Roles, 17:
115-138.
Whitely, S.E.
(1977). Information-processing on intelligence
test items:
Some response components. Applied Psychological
Measurement.
1 : 465-476.
Witting, M.A.
& Peterson, A.C.
(1979). Sex-Related
Differences in
Cognitive Functioning.
Press.
Wong.
C.K.
(1992).
Validation of a Test of Spatial Ability
and a Study
of Some of its Correlates. Unpublished
Masters
in
education dissertation, Faculty of Education, University
of