The present article aims to:
- explore gender differences in NUS students’ learning
approach and academic performance;
- discuss any differences in light of previous research;
- suggest possible steps to improve students’ learning.
This article does not intend to stereotype any gender; rather,
it is hoped that the findings reported here will shed more
light on NUS students’ approaches to learning.
The Study Process Questionnaire and approaches to
The Study Process Questionnaire by John Biggs (1987) based
on Marton & Saljo’s theory of deep and surface learners,
operationalises approach to learning by measuring a student’s
learning motive and strategy. Motive refers to the reason
why students approach learning tasks and their studies, while
strategy refers to the methods and habits they engage in to
accomplish the task. Surface motives include fear of failure,
or wanting just to obtain a paper qualification, and may drive
students to employ such surface strategies as memorising learning
material without first comprehending it. Deep motives, on
the other hand, entail an intrinsic interest in the subject
and a desire for understanding per se, which usually drives
students to deep strategies like taking the initiative to
find out more about a topic and seeing interrelationships
among different concepts.
In addition to deep and surface approaches, Biggs also defined
a third: the achieving approach. The achievement-motivated
student is driven by competition with peers for the highest
marks. As such, achieving strategies are engaged, such as:
choosing modules that the student feels confident in, and
studying material deeply insofar as it is pertinent to the
examination. In relation to academic outcomes, the use of
a surface approach is associated with inappropriate learning
and poor grades, while an achieving approach is associated
with high grades. The deep approach is deemed best, as it
both stimulates optimum learning and produces good grades.
The model of student approaches to learning outlined above
is based on Biggs’ (1987) 3P model, where learning comprises
3 inter-related components: presage (student-based
factors and the learning environment), which affects the process (how students engage in the task), which determines the product—the
learning outcome. The present study examines gender as a presage
factor, particularly focussing on differences in dominant
motives and preferred learning strategies.
CDTL’s study on NUS students’ approach
Since 2001, CDTL has been working on a University-wide project
to study the approaches to learning of NUS students over the
course of their studies, using an adapted form of Biggs’
(1987) SPQ. The details of this project are available at: http://www.cdtl.nus.edu.sg/research/learnprofile.htm.
In this article, the following areas of gender differences
- performance at NUS in terms of CAP;
- study motives and strategies; and
- the influence of motives and strategies on performance
For the purposes of this article, only data collected in
2002 were analysed. The sample comprised 1061 first-year students
(344 males; 717 females) across all faculties except Medicine,
Dentistry, and Law, as these do not operate under the CAP
Gender differences in CAP scores
On average, males scored higher than females: 3.56 (S.D.=.74)
vs. 3.34 (S.D.=.67) respectively. A stepwise regression
confirmed that gender is a significant predictor of CAP (adjusted-R2=.021, F=23.261, p<.001) and that gender differences
in CAP are not due to differences in age (R2-change=.003, F-change=3.206, n.s.). However, it should
be noted that the size of this gender effect is rather small.
Gender differences in motives and strategies
Descriptive statistics, listed separately by gender, are
summarised in Table 1 below.
Across genders, one-way ANOVAs revealed that males scored
slightly higher than females on achieving motives (F=7.033, p<.01), although this effect was small. Males
also scored slightly higher than females on deep strategies
Within each gender, one-way ANOVAs and post-hoc tests revealed
that for males, both deep and achieving motives are the most
dominant, with surface motives being less endorsed, i.e. DM,
AM > SM (F=39.586, p<.001).
However, for females, deep motives are the most dominant,
followed by achieving motives, and then surface motives, i.e. DM > AM > SM (F=112.346, p<.001).
Both genders also seem to prefer deep strategies the most,
and achieving strategies over surface strategies, i.e. DS
> AS > SS (F=40.113, p<.001
for males; F=42.420, p<.001 for females).
Do motives and strategies influence how gender affects
To answer this question, each individual was assigned a
highest-motive and a highest-strategy based on his or her
highest score on deep, achieving or surface dimensions. Individuals
with equally high scores on more than one dimension were grouped
uniquely according to the combination of dimensions they scored
highest on. All the groups had more than 20 cases each, except
for the groups with all three dimensions at equally high levels.
These two groups were excluded from the analysis, leaving
340 male and 710 female cases for the gender by highest-motive
analysis, and 343 male and 713 female cases for the gender
by highest-strategy analysis. Following this, separate two-way
ANOVAs were performed against CAP, with gender and each of
the new grouping variables as independent variables.
No significant interaction was found between gender and either
highest-motive or highest-strategy. However, these analyses
revealed that motive, at least slightly, related to CAP (F=3.485, p<.01). Students who scored the highest on only
achieving motives obtained higher CAP than those who
scored the highest on just deep or surface motives. No
effect was observed for strategy.
In summary, the analyses revealed several gender differences.
In comparison to females, males
- performed slightly better in terms of CAP;
- endorse Achieving Motives slightly more; and
- utilise marginally more Deep Strategies.
It should be noted, however, that all of these gender differences
were small in magnitude, and that motives and strategies do
not influence how gender affects CAP.
How then can males’ better grades be explained? A review
of gender research using Kolb’s Learning Style Inventory
found that males scored higher on the Abstract Conceptualisation
scale, indicating a preference for logical thinking and rational
evaluation, which are deep strategies; they were also found
to excel in impersonal learning situations emphasising theory
and systematic analysis (Severiens & Ten Dam, 1994). In
contrast, female students using a deep approach (identified
as ‘comprehension approach’) tend to look for
personal connections and relevance (identified as ‘elaborative
processing’) with learning material (Meyer et al.,
These two findings could explain why female NUS students
score lower on deep strategies, since they may find it harder
to relate some course material to their personal experiences.
It is also possible that if the more distinct deep strategies
of abstract conceptualisation and elaborative processing were
studied, then it would be found that males’ higher grades
reflect an emphasis on learning outcomes associated more with
abstract conceptualisation than with elaborative processing.
However, this calls for further research.
Finally, it is surprising to note that those who scored the
highest on just deep motives or strategies performed no better
than those who scored the highest on just surface motives
or strategies, since deep learning is supposed to be a fundamental
goal of education. Although no gender differences were found
with regards to this, it is an important issue that should
be addressed in the future.
Although the SPQ has been noted for its tenuous relationship
with grades (Najar & Davies, 2001), it is still helpful
for examining the quality of student learning (Sivan et
al., 2000)—seeing how deeply students engage in
their learning, as defined by a propensity toward deep motivation
and deep strategies. The present results suggest that both
male and female students here at NUS are comparably deep learners,
but male students tend to be more achievement-driven, and
seem to have a slight edge over their female peers in their
usage of deep strategies.
Raise awareness of effective learning strategies
Taking a closer look at gender differences in specific responses
to the SPQ, males were more likely than females to engage
the following deep strategies: thinking of real-life applications
of subject material, and drawing links between previous knowledge
and new information. As such, instructors could take care
to present new knowledge by building on students’ existing
knowledge base, and teach them to reflect and do the same.
Assign mixed-gendered discussion and study groups
Another way to increase students’ awareness of learning
strategies is to encourage them to learn from each other—mixed-gendered
groups afford the opportunity for both male and female students
to benefit from each others’ strengths as they collaborate
on assignments, prepare tutorial questions, compare notes
and prepare for examinations. In class, friendly debates among
groups provide an avenue for students to find out each others’
unique perspectives. Out of class, these study groups would
also provide good support, especially given that this is when
most learning happens, and will moreover help students to
move away from over-reliance on the instructor.
Help students connect personally with subject material
It was suggested earlier that female students may encounter
difficulties with subjects that are not perceived as being
personally relevant to them. To address this need for personal
connection with subject material, instruction can be designed
to create engaging experiences with course content. Examples
include talks or seminars by renowned females in respective
fields; role-play exercises [an example is described in Sivan et al., (2000)]; or even spending some time to introduce
course material as a personal story. Additionally, faculty
can find out about students’ study approaches, and address
the appropriateness of these in the context of course content,
delivery and requirements (Meyer et al., 1994). This
may actually help remove perceived barriers to learning—including
the challenge of finding personal relevance to subject material—and
to enable students to understand learning at a higher level.
The findings reported here are based on first-year students
at NUS. It has been observed elsewhere that students tend
to move toward a more surface approach to learning as they
continue in their studies, and that gender differences become
more apparent over the years at University [e.g. Najar &
Davis, (2001)]. CDTL will be continuing this project to determine
how NUS students change their approaches over time. Lastly,
the present study also shows that gender differences are best
understood within a broad framework, of which the SPQ is just
one aspect. It is hoped that this article will encourage instructors
to consider alternative ways of making learning at NUS a deeper
and more rewarding experience for both genders.
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Meyer, J.H.F.; Dunne, T.T. & Richardson, J.T.E. (1994).
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Najar, R.L. & Davis, K. (December 2001). ‘Approaches
to Learning and Studying in Psychology: A Revised Perspective’.
Paper for AARE International Education Research Conference—Fremantle,
2001. http://www.aare.edu.au/01pap/naj01247.htm (Last Accessed: 8 Dec 2003).
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Sivan, A.; Leung, R.W.; Woon, C.C. & Kember, D. (2000).
‘An Implementation of Active Learning and its Effect
on the Quality of Student Learning’. Innovations
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4, pp. 381–389. UK: Taylor & Francis Ltd.
The authors wish to thank Kevin Carlson for his valuable
comments on earlier drafts of this article.