4. least the 1990s (Head, 1999). It has since become an issue of great public and political concern
in many countries though most notably in the UK, US and Australia (Rowan, Knobel, Bigum
& Lankshear, 2002). In fact, recent reports assert that females are still leading in university
enrolment in these countries (Henry, 2009; Strauss, 2010).
Indications of a gender gap in Malaysia can be inferred from the stark imbalance in public
university enrolment and high dropout rates of boys from school. However, unlike in the
West where the gender gap has generated much debate, similar discussion is lacking whilst
the literature available are few and far in between although the consequences of such gender
disparities in achievement are certainly no less serious. Among the few studies that attempted
to address the gender gap in Malaysia is the government-initiated study by Zalizan, Khatijah
Rohani, Hazadiah and Ma’arof (2001). They observed that female enrolment in public uni-
versities have exceeded those of males since at least 1996 with a majority of 51%. The most
recent data available shows that in 2009, females’ percentage of majority has risen well
beyond 60% (Ministry of Higher Education [MOHE], 2010).
Table 1: Percentage of Students Enrolled in Public Universities by Gender
20092006200019901980
Gender
32.836.942.154.364.5Male
67.263.157.945.735.5Female
100.0100.0100.0100.0100.0Total
Note: Adapted from Aminah (1994), MOE (2006a) & MOHE (2010)
As noted by Zalizan et al. (2001), gender differences in university enrolment and dropout
rates are symptomatic of gender disparities in achievement in schools. Thus far however,
the literature as well as educational policies in Malaysia including the National Education
Blueprint 2006-2010 (PIPP 2006-2010) (MOE, 2006b) and more recently, the National Key
Result Areas for Education (Education NKRA) (MOE, 2009b), have largely focused on ad-
dressing disparities in achievement related to race and socioeconomic status (urban versus
rural schools).
Hence, gender has not been seriously studied as a variable leading to disparities in aca-
demic achievement except in the context of equal attainment to education, where research
has shown it to be equitable (i.e. United Nations Children’s Education Fund [UNICEF],
2005). However, some have argued that gender may be a more viable way of improving
achievement. Noble, Brown and Murphy (2001) explained that it is more pragmatic to devise
strategies that targets improvement among genders rather than race and class, two variables
which are no less important but which are nonetheless more complex and sensitive in nature
and hence are more difficult to work around.
The Need for Addressing the Gender Gap
With the increasing global emphasis on credentialism, males need to perform well at the
school level in order to compete for places in university. If the gender gap in schools is not
quickly addressed, gender discrepancies in university enrolment will continue to widen even
16
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5. further. As a result, fewer high-paying jobs would be available to men leading to changes
in future workforce composition. Importantly as well, this would challenge traditional so-
ciocultural conventions as men may no longer be the main breadwinners of the family. In
addition, it may be harder for women to find spouses of similar education background should
this trend continue.
This is a concern even in the West, as Conlin (2003) points out, if men continue to fall
behind in education, they would be more likely to marry women who “outlearn” them. Such
sociocultural dictations are also prevalent in Malaysian society where even academicians
have voiced their concerns on this issue (Farabi, 2007):
One day professional working women will eventually marry men including those who
are not employed. Eventually, this will give rise to the phenomenon of men staying
home to take care of the children and home while the women go out to work. This
phenomenon is already happening now although this is contrary to our culture.
Nevertheless, concern over the gender gap should not be misconstrued as championing one
gender or the other. Female achievement should continue to be encouraged as well as that
of males’. More importantly, it must be recognised that any kind of gender gap would lead
to a loss of potential human capital. This is in direct contrast to Malaysia’s National Education
Philosophy declared in 1987, which states that an important goal of education is to produce
modal insan or quality human capital capable of driving the nation’s development (Rosnani,
2004). This idea continues to be strongly emphasised today and is among the main thrusts
of the PIPP 2006-2010 and Education NKRA. Therefore, the gender gap in Malaysia is
viewed as a serious threat that stands to deprive the nation of valuable human capital.
Gender Differences in Achievement: Standardised Tests and
Gender-Stereotyped Subjects
The two most apparent areas where gender differences in achievement can be seen are in
standardised tests and gender-stereotyped subjects. Studies in various countries (Smith, 2005;
Gillborn & Mirza, 2000) have reported that females generally outperformed males in tests
such as the GCSE and SAT. Similarly, nationwide results for the three compulsory standard-
ised tests in Malaysia, SPM (Malaysian Certificate of Examination), PMR (Lower Secondary
Assessment) and UPSR (Primary School Assessment) for 1996 to 2000 showed that females
scored better than males overall (Zalizan et al., 2001).
Research abroad has also shown that females have narrowed the gap in traditionally
masculine subjects such as mathematics and science but the gap in feminine subjects such
as languages, reading and writing (Conlin, 2003; Rowan et al., 2002) continues to widen
(Head, 1999; Maynard, 2002). Concurring with this, Malaysian females performed better
than males in science and mathematics in the SPM, PMR and UPSR (Zalizan et al., 2001)
and in the international 2003 Trends in Mathematics and Science Study (TIMMS) (Noor
Azina & Halimah (2009). However, males scored better than females in technical-based
subjects in the SPM (Zalizan et al., 2001). Hence, it would be inaccurate to say that females
are outperforming males in every aspect although research has shown the gender gap to be
most evident in standardised tests and gender-stereotyped subjects where females generally
perform better than males.
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AINUDDIN DAHLAN, MD NOOR, SYED MUSTAFA, SAID HASHIM, ZULKIFLI
6. Causes of the Gender Gap: Sociocultural and Biological Arguments
The causes for the gender gap have been discussed extensively in the West. Some researchers
attribute this to sociocultural factors while others allay this to biological factors. Briefly, the
sociocultural view underlines such factors as the feminization of schools (Francis, 2000;
Maynard, 2002) which alludes to external faults for males’ underachievement such as the
lack of male teachers in schools, promoting a biased curriculum and instruction as well as
assessment methods that favour females’ learning styles more than males’.
Moreover, achievement motivation may also differ between genders resulting from social-
isation into traditional gender identities. Many cultures generally raise females to be more
obedient, responsible and take schoolwork seriously whereas males are given a higher degree
of autonomy, freedom to do as they like and view schoolwork as a generally feminine rather
than masculine pursuit (Maynard, 2002; Francis, 2000). A local study reported that boys
from less fortunate families helped their parents earn a living and this affected their school
attendance (Zainah, 2007). They were also reinforced into traditional gender roles where
their parents are less restrictive of them compared to their female siblings. Hence, these
factors may influence their attitudes towards schooling.
Technological advances in neuroscience has made it possible to consider a biological ex-
planation for gender differences in achievement. Researchers have discovered that male and
female brains are not only structured differently but also function differently, therefore
making them inherently more proficient in certain tasks, such as females’ advantage in verbal
abilities and males’ in spatial and mathematical abilities (Havers, 1995; Noble et al, 2001;
Gurian & Stevens, 2004). Hence from the biological viewpoint, males and females are seen
as being innately “wired” to process the world and behave differently whereas differences
in testosterone levels may also make males more aggressive and impulsive (Gurian, 2002).
Thus for example, lengthy lectures may not engage males well and while females may also
not favour this, their lower levels of testosterone enable them to better tolerate this mode of
instruction.
Learning Styles: Accommodating Gender Differences
As discussed, socioculturally and biologically, males and females not only behave differently
but also approach learning in different ways. Consequently, efforts should be made to meet
both genders’ learning needs. Thus the premise of this study is that the gender gap can be
narrowed by meeting the learning needs of both genders and one way to do this is by consid-
ering students’ learning styles. The literature on the effects of matching learning styles and
achievement have indeed been inconclusive. However, several studies have found that mis-
matching may result in low grades, disinterest in learning and could even lead to students
giving up and dropping out of school (Felder & Silverman, 1988; Godleski 1984; Oxford et
al. 1991; Smith & Renzulli 1984 as cited in Felder & Henriques, 1995).
Moreover, some studies have also found that learning styles differ according to gender
(Bolliger & Supanakorn, 2010; Isman & Gundogan, 2009; Wehrwein, Lujan & DiCarlo,
2007; Zalizan et al., 2001). Educators therefore anticipate positive outcomes in matching
gender differences in learning styles (Grossman & Grossman, 1994). In addition, awareness
of their own learning styles may allow students to be more actively engaged in their learning
(Pritchard, 2005). In addition, an appealing attribute of learning styles theory is that it assumes
18
THE INTERNATIONAL JOURNAL OF LEARNING
7. regardless of innate intelligence, that almost anyone can learn provided that instruction cor-
responds to their preferred way of learning.
In Malaysia, Robiah (1996, as cited in Asiah, 1999) notes that although accounting for
different learning styles in the planning of teaching is encouraged locally, it is only in principle
as in reality, teachers’ understanding of learning styles is very poor. Zalizan et al. (2001)
reported similar findings whereby teachers surveyed said they did not consciously take stu-
dents’ learning styles differences into consideration when teaching.
Research Questions
The following are this study’s research questions:
1. Is there a difference in academic achievement between genders?
2. Is there a difference in male and female achievement in traditionally gender-stereotyped
subjects (Malay Language, English, mathematics and science)?
3. Is there a difference in learning styles between genders?
4. To what extent can gender and learning styles predict achievement?
Method
Respondents
The respondents for this study were 411 randomly selected Form Four students (average 16
years of age) from four government secondary schools in Kuala Lumpur. Overall, there were
186 males (45%) and 225 female (55%) respondents, from both Arts and Science stream
classes. In terms of ethnicity, the majority of respondents were Malays at 77% (317), followed
by Chinese at 16% (66), Indians at 5% (19) and ‘Others’ at 2% (9).
Measure of Academic Achievement
Respondents’ self-reported PMR results were obtained to determine gender differences in
achievement. Since PMR results are represented by letter grades, it is the norm to consider
only the total number of As obtained as a benchmark of excellent achievement. The number
of subjects taken in the PMR usually range from 8 to 9, thus respondents were categorized
into two categories: high achievers (those who obtained 6 As and above) and low achievers
(5 As and below).
Instrument
Respondents’ learning styles were assessed using Felder and Soloman’s (1991) 44-item Index
of Learning Styles (ILS), which the researcher adapted into a bilingual version (Malay
Language and English). The instrument and scoring key were obtained from the developer’s
website after declaring its non-commercial use. Each subscale: Active-Reflective, Sensing-
Intuitive, Visual-Verbal and Sequential-Global were represented by 11 dichotomous items.
Two pilot tests were conducted to assess the reliability of the subscales and overall instrument.
19
AINUDDIN DAHLAN, MD NOOR, SYED MUSTAFA, SAID HASHIM, ZULKIFLI
8. As with previous studies (Felder & Spurlin, 2005; Litzinger, Lee, Wise & Felder., 2007), a
= 0.5 or greater was used as the level of acceptability.
After the second pilot study, the instruments’ overall reliability improved to α = 0.56
where all scales except the Sequential-Global subscale exceeded the 0.5 acceptability limit.
This is consistent with the findings of other studies where this subscale is always reported
to be lower than the others (Felder & Spurlin, 2005; Litzinger et al., 2007). In fact, the alpha
value obtained for the Sequential-Global subscale in this study was higher than the value
reported by Van Zwanenberg et al. (Felder & Spurlin, 2005). Hence, there was an acceptable
degree of confidence in adapting this version of the instrument for the study.
Table 2: Cronbach’s Alpha Coefficients from Two Pilot Studies
SourceNSeq-GloVis-VerSen-IntAct-Ref
Pilot study 2330.460.500.670.70
Pilot study 140-.0460.420.560.45
Felder and Soloman’s Learning Styles Model
Felder and Soloman (1993) assume that students vary in terms of the learning styles and
learning strategies that they use. All learners are thought to have some degree of each of the
four dimensions present within them and thus, knowledge of these learning styles and
strategies are important for students and teachers alike in order to maximize the teaching
and learning process.
Processing: Active and Reflective Learners
This subscale refers to students’ preferred degree of involvement in dealing with learning
tasks. Active learners prefer being actively engaged in the learning task such as through
practical application of what has been learnt, through group discussions etc. whereas Reflect-
ive learners like to think things through first before jumping into any practical application
and prefer to work alone rather than in groups (Felder and Soloman, 1993).
Perception: Sensing and Intuitive Learners
This subscale refers to students’ approaches to problem-solving and their tolerance for fac-
tual learning. Sensors enjoy learning facts and are better at memorizing them. They also
prefer using well-established methods to solve problems and dislike complications and sur-
prises. Thus, they are not big risk takers. Conversely, Intuitors are less tolerant of learning
that requires repetition, routine and memorization of facts. However, they are innovative
and better able to grasp new concepts, discovering possibilities and relationships (Felder
and Soloman, 1993).
Input: Visual and Verbal Learners
The ability for students to retain information is influenced by the way the information is
presented. Thus, this subscale purports that some learners prefer more visual modes of in-
20
THE INTERNATIONAL JOURNAL OF LEARNING
9. formation intake such as through charts and diagrams etc. whereas others appreciate more
verbal explanations (Felder and Soloman, 1993).
Understanding: Sequential and Global Learners
This subscale is concerned with the ways learners organize or comprehend information.
Sequentials learn by establishing logical connections from one piece of information to another
whereas Global learners do not immediately see the relationships between materials. Globals
put pieces together randomly and will suddenly “get it”. Thus, Global learners are able to
connect things in novel ways whereas Sequential learners are more methodological in their
approach (Felder and Soloman, 1993).
Analysis
The data was analysed using SPSS. Gender differences in achievement was examined via
crosstabulation (high vs. low achievers) and t-test (mean number of As), whereas gender
differences in the four selected subjects and learning styles were assessed using crosstabula-
tion. Binary logistic regression was conducted to determine the predictive effects of gender
and learning styles on achievement.
Results and Discussion
Gender Differences in Academic Achievement
When high achievers were compared to non-high achievers by gender, the chi-square obtained
was significant χ2
(1, N=411) = 6.25, p =.015. Among the high achievers, a larger percentage
were female (11.2%) compared to male (5.1%). However, this was also true for low
achievers where 40.1% were male and 43.6% female. Consequently, further analysis was
carried out where based on total number of As, the t-test found there was a significant differ-
ence in achievement between genders, t(409)=-2.05, p =.040 where females (M=2.63) had
a higher mean than males (M=2.11). These findings concur with that of Aminah (1994) and
Zalizan et al. (2001), and hence supports the notion that a gender gap does exist.
21
AINUDDIN DAHLAN, MD NOOR, SYED MUSTAFA, SAID HASHIM, ZULKIFLI
10. Table 3: Gender differences in total number of As obtained in the PMR
Gender Differences in Malay Language, English, Mathematics and Science
Female respondents obtained the majority of As in all the four subjects although significant
gender differences were observed in Malay Language achievement only, χ2
(1, N=411) =
13.12, p =.000. Out of the total respondents, 37.5% managed to obtain an A in this subject
with the majority being female (24.8%). Although females also obtained most of the As in
English, mathematics and science, these differences were not statistically significant.
This implies that generally, male and female achievement are similar in these subjects. It
supports the notion that females are narrowing the gap in subjects traditionally regarded as
male fortes (i.e. science and mathematics), where they perform as well as or even better than
their male counterparts (Head, 1999; Gaine & George, 1999; Gillborn & Mirza, 2000). In
this study, females obtained the majority of As in both these subjects.
The findings are also in agreement with previous literature (Head, 1999; Conlin, 2003;
Rowan et al., 2002; PIRLS, 2006) that state while the gap in traditionally male subjects are
narrowing, there continues to be a wide discrepancy in traditionally female subjects such as
languages. Not only did females obtain more As than males in English and English Language
in this study, but for the latter, the difference was statistically significant. The difference
was not as pronounced for English perhaps because Malaysian students in general have not
mastered the language well (Nor Hashimah, Norsimah & Kesumawati, 2008).
Gender Differences in Learning Styles
No significant differences in learning styles were found between genders. Overall, the ma-
jority of respondents preferred Active (79%), Visual (77%) and Sequential (73%) learning
styles. This is consistent with Boondao, Hurst and Sheard (2008) who found that both eastern
and western students in an Australian university also preferred Active, Visual and Sequential
styles. Therefore, most students preferred an active rather than passive learning environment.
Importantly, this suggests a mismatch between students’ preferences and the way lessons
22
THE INTERNATIONAL JOURNAL OF LEARNING
11. are carried out in Malaysian schools, which has been criticised for being passive, promoting
memorisation and rote learning as the result of an exam-oriented system (Wong, 2004;
Collin, 2008).
Students’ preference for visual material could be partly attributed to the fact that students
today have contact with technology such as television, mobile phones and computers at an
earlier age. Roslinda (2006) found that computer use (for studying and leisure activities)
among Malaysian students has increased with the development of technology today. Thus,
these factors could influence students’ visual inclinations.
In terms of Sequential learning style, Felder (1998) explains that learning by sequence,
in logical linear steps and mastering the material as is (i.e. without much interpretation or
deep understanding) is common in formal education systems. Thus, students may be encour-
aged to adopt this approach in exam-oriented cultures such as Malaysia. Boondao et al.
(2008) also reported that while both eastern and western students were Sequential, however,
eastern students had a higher degree of surface and achievement approaches as well as mo-
tivation.
However, the percentages were less defined for the Sensing-Intuitive subscale where 51%
were Sensing (25% male and 26% female) while 49% were Intuitive (20% male and 29%
female). These results are only partially supported by the biological view (Gurian et al.,
2001; Gurian, 2002; Gurian & Stevens, 2004). This is because while Sensors prefer real
world problems and lab work, they are also described as preferring to memorize facts besides
having a high tolerance for repetitive work and details, which according to the biological
viewpoint are characteristic of girls. Similarly, that more girls are Intuitors contradicts the
biological viewpoint as girls are said to be more tolerant of memorizing and routine rather
than less tolerant of these modes of learning.
Extent to which Academic Achievement is Predicted by Gender and
Learning Styles
Table 4 shows that only 8.5% of the variation in achievement is explained by the variables
entered in the model. While this finding is significant, it suggests that other factors not ac-
counted for in the model may contribute to achievement. Nevertheless, in testing lack of fit,
the p-value of .947 (Table 5) showed that the logistic model fits the data well and probability
of correct classification is 83.5%, thus generating an error rate of 16.5%.
Table 4: Model Summary
Nagelkerke R SquareCox & Snell R Square-2 log likelihoodStep
.085.050343.1851
Table 5: Hosmer and Lemeshow test
Sig.dfChi-squareStep
.94782.7891
23
AINUDDIN DAHLAN, MD NOOR, SYED MUSTAFA, SAID HASHIM, ZULKIFLI
12. Three of the five variables entered into the model were found to be significant predictors of
achievement. The dependent variable was coded 1 for low achievers and 2 for high achievers
(Garson, 2009) whereas gender was coded 1 for male and 2 for female. Each learning style
subscale was also recoded. For example, in the Active-Reflective subscale, 1 represented
reflective and 2 for active.
As illustrated in Table 6, the model showed that the likelihood of becoming a high achiever
is increased 2.329 times by being female rather than male, 1.988 times more by being
Sensing rather than Intuitive and 2.482 times more by being Visual rather than Verbal.
Table 6: Variables in the Equation
Exp(B)Sig.dfWaldSEB
2.329.00418.343.293.845GenderStep 1 (a)
.605.10912.575.313-.502AR
1.988.01615.851.284.687SI
2.482.01915.527.387.909VV
.904.7421.108.307-.101SQ
.061.000126.063.549-2.801Constant
Conclusion and Recommendations
Firstly, this study found the majority of high achievers to be females, hence concurring with
previous research (Aminah, 1994; Zalizan et al., 2001). Females also obtained a significantly
higher mean than males in terms of total number of As in the PMR, supporting the notion
that a gender gap does exist in schools. Secondly, the results were in agreement with existing
literature where it was found that females performed better than males in all the four subjects.
This suggests that while females are catching up in traditionally male associated subjects
(science and mathematics), males however are not showing similar progress in female related
subjects (English and Malay Language).
These two findings suggests that gender differences in achievement at the school level
may be among the factors leading to the gender imbalance in university enrolment. Therefore,
in order to increase the numbers of males entering universities, steps must be taken to ensure
that they are performing on par with females in schools and especially in national standardised
tests such as the SPM which is the main criteria for entry into university. In particular,
measures should be introduced to increase males’ performance in female-related subjects,
perhaps by incorporating more reading materials that appeal to males.
Third, although no gender differences were found in learning styles, where the majority
of students were Active, Visual and Sequential learners, it appears that there is a mismatch
between students’ preferences for learning and how they are being taught in schools, at least
in terms of promoting an active learning environment. Finally, it was observed that being
female, Sensing and Visual increased the likelihood of achievement.
Hence, not only could accommodation of certain learning styles enhance learning but also
increase achievement. This requires the serious attention of teachers, especially trainee
teachers because as discussed, learning styles is not consciously practised in classrooms
today (Robiah, 1996 as cited in Asiah, 1999; Zalizan et al., 2001). Thus, teacher training
24
THE INTERNATIONAL JOURNAL OF LEARNING
13. colleges and university education faculties need to incorporate learning styles as a core part
of their syllabus. For example, the use of learning styles in lessons could be included as a
key component in the evaluation of trainee teachers when they are undergoing their practicum
training in schools.
In conclusion, the evidence of a gender gap in Malaysian schools as suggested by this
study calls for the swift attention and action of educators. It is hoped that accommodating
certain learning styles that have been found to increase the likelihood of academic achievement
(in this case, Sensing and Visual), would be one of the ways to help bridge the gender gap
and subsequently create more gender-balanced classrooms, thereby ensuring that the education
system meets its goal of nurturing quality human capital among both males and females
which will ensure the nation’s continued development.
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About the Authors
Nadia Ainuddin Dahlan
Nadia Ainuddin Dahlan is a lecturer at the Faculty of Education, MARA University of
Technology, Malaysia. Courses she has taught at the faculty include Educational Psychology,
Educational Sociology, Educational Testing and Assessment as well as Professional Devel-
opment. She received her undergraduate degree in Psychology (Industrial and Organisational)
and masters degree in Educational Psychology from the International Islamic University
Malaysia. Among her interested research areas include Educational Psychology, Social
Psychology, Early Childhood Education, Inclusive Education, Gender Studies and Educa-
tional Testing.
Dr. Nor Azian Md Noor
Nor Azian is an assistant professor at the Institute of Education, International Islamic Uni-
versity Malaysia. She has vast experience teaching in the field of educational psychology at
both the undergraduate and postgraduate levels.
Sharifah Muzlia Syed Mustafa
In the field of teaching for more than 10 years, Sharifah Muzlia is currently a lecturer at the
Faculty of Education, MARA University of Technology, Malaysia where she teaches courses
on psychology, sociology and counselling. Among her research interests include the fields
of motivation and stress.
Khadijah Said Hashim
Khadijah is a lecturer at the Faculty of Education, MARA University of Technology,
Malaysia. Courses she has taught include educational psychology and educational sociology
whereas for graduating students, she has taught professional development and current issues
in education. Her areas of interest include educational psychology, special education and
gender studies.
Voviana Zulkifli
Voviana has more than 5 years' teaching experience in Teaching English as a Second Lan-
guage (TESL). A lecturer at the Faculty of Education, MARA University of Technology,
Malaysia, her fields of interest include second language acquisition (SLA), writing, listening
and speaking.
27
AINUDDIN DAHLAN, MD NOOR, SYED MUSTAFA, SAID HASHIM, ZULKIFLI
16.
17. EDITORS
Mary Kalantzis, University of Illinois, Urbana-Champaign, USA.
Bill Cope, University of Illinois, Urbana-Champaign, USA.
EDITORIAL ADVISORY BOARD
Michael Apple, University of Wisconsin, Madison, USA.
David Barton, Lancaster University, Milton Keynes, UK.
Mario Bello, University of Science, Cuba.
Manuela du Bois-Reymond, Universiteit Leiden, Leiden, The Netherlands.
Robert Devillar, Kennesaw State University, Kennesaw, USA.
Daniel Madrid Fernandez, University of Granada, Spain.
Ruth Finnegan, Open University, Milton Keynes, UK.
James Paul Gee, University of Wisconsin, Madison, USA.
Juana M. Sancho Gil, University of Barcelona, Barcelona, Spain.
Kris Gutierrez, University of California, Los Angeles, USA.
Anne Hickling-Hudson, Queensland University of Technology, Kelvin Grove, Australia.
Roz Ivanic, Lancaster University, Lancaster, UK.
Paul James, RMIT University, Melbourne, Australia.
Carey Jewitt, Institute of Education, University of London, London, UK.
Andeas Kazamias, University of Wisconsin, Madison, USA.
Peter Kell, University of Wollongong, Wollongong, Australia.
Michele Knobel, Montclair State University, Montclair, USA.
Gunther Kress, Institute of Education, University of London, London, UK.
Colin Lankshear, James Cook University, Cairns, Australia.
Kimberly Lawless, University of Illinois, Chicago, USA.
Sarah Michaels, Clark University, Worcester, USA.
Jeffrey Mok, Miyazaki International College, Miyazaki, Japan.
Denise Newfield, University of Witwatersrand, Johannesburg, South Africa.
Ernest O’Neil, Ministry of Education, Sana’a, Yemen.
José-Luis Ortega, University of Granada, Granada, Spain.
Francisco Fernandez Palomares, University of Granada, Granada, Spain.
Ambigapathy Pandian, Universiti Sains Malaysia, Penang, Malaysia.
Miguel A. Pereyra, University of Granada, Granada, Spain.
Scott Poynting, Manchester Metropolitan University, Manchester, UK.
Angela Samuels, Montego Bay Community College, Montego Bay, Jamaica.
Michel Singh, University of Western Sydney, Sydney, Australia.
Helen Smith, RMIT University, Melbourne, Australia.
Richard Sohmer, Clark University, Worcester, USA.
Brian Street, University of London, London, UK.
Giorgos Tsiakalos, Aristotle University of Thessaloniki, Thessaloniki, Greece.
Salim Vally, University of Witwatersrand, Johannesburg, South Africa.
Gella Varnava-Skoura, National and Kapodistrian University of Athens, Athens, Greece.
Cecile Walden, Sam Sharpe Teachers College, Montego Bay, Jamaica.
Nicola Yelland, Victoria University, Melbourne, Australia.
Wang Yingjie, Beijing Normal University, Beijing, China.
Zhou Zuoyu, Beijing Normal University, Beijing, China.
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