Gender differences in academic performance among undergraduates at the University of Jordan: are they real or stereotyping?
Article Type:
Academic achievement (Demographic aspects)
Sex differences (Psychology) (Educational aspects)
Khwaileh, Faisal M.
Zaza, Haidar I.
Pub Date:
Name: College Student Journal Publisher: Project Innovation (Alabama) Audience: Academic Format: Magazine/Journal Subject: Education Copyright: COPYRIGHT 2011 Project Innovation (Alabama) ISSN: 0146-3934
Date: Sept, 2011 Source Volume: 45 Source Issue: 3
Event Code: 310 Science & research
Organization: University of Jordan
Geographic Scope: Jordan Geographic Code: 7JORD Jordan

Accession Number:
Full Text:
The grade point averages (GPAs) of the University of Jordan undergraduate students from 2002 to 2007 were studied to determine gender differences in academic performance over the above mentioned period. Students' records (17,522 females, 8,600 males) were obtained from the registrar's unit. The data were analyzed to reveal the role of gender on the students' academic achievement. The results of the study showed that female undergraduate students were found to outperform male undergraduates in their GPAs. This result is contrary to the general Jordanian stereotypical beliefs about female academic performance in higher education. Implications and recommendations based on the results of this study were also introduced.


Gender differences have become on the hotlist of critical issues around the world. Hausmann, Tyson, & Zahidi (2009) reported that there is no country in the world that has yet reached equality between women and men in different critical areas such economic participation or education.

In Jordan, gender stereotyping is still prevalent in almost all aspects of life (A1bedour, 2004; Nabulsi, 2002). The phenomenon of gender differences is not only observed in the daily life matters but also in textbooks and teachers' attitudes (The World Bank, 2005). While we see males dealing with complex and difficult tasks of life matters inside and outside the house, we see, on the other hand, girls handling the relatively easy and less demanding tasks or things at home. A1bedour (2004) noted that there are different gender roles within the Jordanian family. One of the most important differences observed by Al-bedour was that while the male member is allowed to perform several activities concerning the family, it is restricted for the female member to do the same things. For example, parents allow the male member to participate in decision making, and to make little contributions to the house work but it is restricted for females to participate in decision making; nevertheless, they take the heavy load of home chores. Moreover, Al-bedour reported that the status of the mother and the father, the type of work they have, the age and level of education of parents, and the income of the family, in addition to the number of family members are all reasons that affect the male or female to pursue university education (p. 134).

According to the World Bank (2005), the Jordanian society developed a very rigid picture that certain characteristics such as "references to kindness, love, sensitivety, and intersest in caring for familty" are always linked to females (p. 31). A1waqfi's (1997) study arrived at similar findings in which he found that females in the Jordanian socity are generally more affectionate and more sensitive. Results of other studies in other Arab couuntries (e.g. Alsadah, 1993) confim the findings of Jordanian studies in witch they agree that school textbooks still present women in the traditional roles, and that their roles are overwhelmingly concentrated in the teaching, training, and service jobs.

The common traditional stereotypical beliefs about women performance are that women seem to work less hard than men, and that female students achieve lower scores in school stages in general, and high school in particular, and that girls who fail at school usually get married at early ages. The United Nations (n. d., cited in Social Institutions and Gender Index) estimated "that 8 % of Jordanian girls between 15 and 19 years of age were married, divorce or widowed"

Another common traditional stereotype is that some demanding majors (i.e., Medicine, Engineering, Dentistry, Pharmacy, etc.) that afford very good careers in Jordan are almost males' jobs, while softer majors (i.e., Psychology, Education, Languages, Social Sciences, etc.) that don't offer good careers are mainly open for females. For all of the abovementioned reasons, it is worth mentioning that studying the gender differences is important because it influences the society's views about the roles of females in the society, females' self-confidence and ambitions, and the effect of stereotyping in education. In particular, this might help in shedding light on the belief whether academic performance is really affected by gender differences or it is just a stereotyping.

Literature Review

In a society like Jordan, the gender differences issue is a critical one to discuss; one reason is that the Jordanian society is a developing one and it is open to all changes in the whole world. Fast changes and contradictions have become two major emerging characteristics of the Jordanian society as it is the case for many other countries of the world. Unfortunately, few studies tackled these issues except for some masters' theses that discussed the topic from an academic perspective at the school level. As for studies conducted around the world about gender differences, the results of these studies are contradicted. While the majority of the studies found out that females outperformed males, others found the opposite; on the other hand, other researchers found no differences at all between males and female concerning their academic achievement and success. The reasons behind these agreements or disagreements are varied according to the variables and predictors of every research study.

In Nigeria, Afuwape and Oludipe (2008) studied the integrated science achievement of graduating pre-service teachers for a period of three years. The sample of the study included 253 (126 males and 127 females) pre-service teachers in a college of education in Nigeria. The findings of the study revealed that there was no significant difference in academic performance in integrated science between males and females, and that for each year male students had higher mean scores than female students.

Felder et al. (1994) studied the factors that help to determine a student's success or failure at the university. To do so, he conducted a 4-year longitudinal study that included 87 men and 34 women at North Carolina State University in which he examined gender differences in students' academic performance, persistence in chemical engineering, and attitudes toward their education and themselves. The researchers concluded that although the pre-engineering academic credentials of women entering college often exceeded those of men, these women did not score any higher in technical classes than men. The findings of the study showed that women students also attributed poor performance to their lack of ability, while men usually attributed it to lack of hard work or being treated unfairly. The critical question of why these women earned lower grades in chemical engineering courses and exhibit lower confidence levels of themselves could not be answered with any real degree of certainty.

Liu and Wang (2005) conducted a study in which they investigated the decline of students' academic self concept of high school students. The purpose of the study was to find if there was any grade or gender effect on adolescent's academic self-concept in the Singapore society. Six hundred and fifty six students participated in the study. The results of the study showed that there was a significant effect for gender with female students having significantly higher perceived academic effort (academic self-concept subscale) than their male counterparts.

Smith (2004) conducted a study at Brunel University in which she found that women consistently outperformed men in a Geography course even though they had started their coursers with almost identical A-level results. She also found that female students were more conscientious, less likely to miss lectures and more likely to believe that their marks reflected their ability than their male peers, that was because they felt that the good grades were their "insurance policy" for success. Moreover, the results of the study showed that female students were also more likely to seek and receive support from staff.

Downing et al. (2008) investigate the relationships between gender, A-level scores, and scores on the learning and study strategies inventory (LASSI) of undergraduate students. The participants for this study were selected at random from the overall LASSI sampling exercise and males and females were compared using the LASSI scales at a Hong Kong University. The findings of the study showed that gender differences in cognitive functioning and achievement do not always favor one sex over the other. However, the literature related to intelligence testing suggests that males outperform females on tests of visuospatial ability, and mathematical reasoning whereas females do better on tests involving memory and language use. Moreover, the results of the study showed that while there was a relationship between gender, A-level scores and scores (LASSI) of undergraduate students, little practical information was provided at the cognitive level. In contrast, the data from LASSI allowed a more detailed and practical metacognitive analysis suggesting significant gender differences in certain areas of self-perceived performance, with females demonstrating significantly higher levels of self-regulation and a more positive attitude to academic study than their male counterparts. Also, the analysis of the data produced by the LASSI indicated that there were significant differences in self-perceived metacognition between the genders.

Ismail and Othman (2006) investigated the effect of students' gender and past performance on their performance during the first year of the university. Data about students were collected from male and female students from three faculties, namely, Faculty of Economics and Administration, Faculty of Economics and Accounting and Faculty of Arts and Social Sciences. Research results showed that female students were found to have better results than their male counterparts and that gender played an important rule in influencing success in the university.

The increasing diversity between university students has seen a concomitant interest in factors predicting academic success. In a two-year correlation study, Sheard (2009) conducted a study in which he examined whether age, gender (demographic variables), and hardiness (cognitive/emotional variable) differentiate and predict university final degree grade point average (GPA) and final-year dissertation mark. Data for the study were reported from a total of 134 university undergraduate students. The researcher distributed questionnaires during the first week of the second year of undergraduate study and gave consent for their academic progress to be tracked. Final degree GPA and dissertation mark were the academic performance criteria. The results of the study showed that mature-age students achieved higher final degree GPA compared to young undergraduates. Also, female students significantly outperformed their male counterparts in each measured academic assessment criteria. Female students also reported a significantly higher mean score on hardiness "commitment" compared to male students. "Commitment" was the most significant positive correlate of academic achievement. Final degree GPA and dissertation mark were significantly predicted by commitment and gender respectively.

In an attempt to investigate the key determinants of degree performance, Barrow, Reilly and Woodfield (2009) conducted a study that used data drawn from three recent cohorts of undergraduates at the University of Sussex. The primary purpose of the study was to examine the gender dimension to degree performance. The results of the study showed that the average "good" degree rate for female students was found to be superior to the male rate. Also, the modest raw gender differential in first class degree rates favored women but was found to be attributable to their better endowments, particularly pre-entry qualifications. However, it was found that the largest differential favoring women was in classification where almost all of the difference was attributable to differentials in coefficient treatment rather than endowments (or characteristics).

Darwazeh (1998) conducted a study in which she investigated some of the learner variables that may have an influence on university academic achievement in a distance versus a conventional education setting. A random sample of 250 male and female students was taken from the three branches of A1-Quds Open University in Palestine. In contrast, a random sample of 250 male and female students was taken from A1-Najah National University (conventional education) in order to match the sample taken from A1-Quds Open University in their specialization (Literature, Science, Education, and Business Administration), and academic level (freshmen, sophomores, juniors, and seniors). The results of the study revealed that the university academic achievement for the distance learning group was significant for several variables among which was the gender (in favor of females) but this same variable was not significant at all for the conventional group.

Due to the fact that different variables, methods and procedures, types of samples and data collection, sampling, etc. studies usually do not come up with similar findings. On the contrary, some studies sometimes come up with contradicted results. Mattox (1997) for example came up with different findings opposed to all of the pervious studies that privilege females over males in academic success. She conducted her study in a way that she compared between the academic performance of male and female students in high school elective science course. The data for this study were drawn from the grade books of six teachers of elective science courses and consisted of the grades earned by the students during one academic year. The number of students enrolled in the course, the average grade, standard deviation of grades, and pooled standard deviation were recorded. The results of the study showed that the average grade in elective science classes differed between males and females; however, the two-sample t-test applied to the data did not support this conclusion, that is to say, no differences in academic performance due to gender.

Clemons (2008) conducted a study in which she examined the relationships among students' self-perception, attitudes toward school, study and organizational skills, achievement motivation, attributable style, gender, parental involvement and style, parental income and parental level of education, and students' academic performance or achievement. Using previous research in motivation and gifted achievement a model was developed to represent the relationships among the student and parent variables and achievement. Structural equation modeling techniques were used to examine the model. Achievement levels were measured using students' math and language arts scaled scores on the Stanford-9 achievement test, as well as their average GPA in math and language arts over three semesters. The remaining variables were measured using Likert-type survey instruments. A non-probability sample of 369 students was drawn from six school districts located in Arkansas, Utah, and Virginia. Students were sixth through ninth graders who had been identified as intellectually gifted by their school district, excluding students identified as gifted learning disabled. The findings of the study indicated that there were no meaningful gender differences on any of the indicator variables. Students' socioeconomic status was found to have the strongest relationship with academic achievement followed by achievement motivation, study and organizational skills, and parental involvement and responsiveness.

Berkant (2009) investigate whether students' meaningful causal thinking abilities vary with their academic achievement levels, reading comprehension abilities, and gender or not. The sample of the study consisted of 124 ninth grade students attending a secondary school in Adana City Seyhan District during 2008/2009 academic year. The Meaningful Causal Thinking Evaluation Test, the Biology Academic Achievement Test, and the Reading Comprehension Test (IOWA) were used to collect the data. The results of the study showed that there were significant relationships between meaningful causal thinking and academic achievement, and between meaningful causal thinking and reading comprehension. On the other hand, no significant difference was found between male and female students' meaningful causal thinking abilities. It is concluded that students' academic achievement levels and reading comprehension scores are significant predictors of their meaningful causal thinking ability, but their gender was not. An individual carries all these characteristics in the same cognitive structure and probably uses them in coordination when he/she needs. Therefore, educational activities can be designed based on the relationship between meaningful causal thinking and academic achievement, and between meaningful causal thinking and reading comprehension.

Sue and Abe (1988) conducted a study in which they examined some predictors that affect academic success for 4,113 Asian American students and 1,000 white students who enrolled as freshmen on any of the eight University of California campuses during fall 1984. The predictors were: (1) high school grade point average (GPA); (2) Scholastic Aptitude Test (SAT)verbal score; (3) SAT-mathematical score; (4) English Composition Test score; and (5) Level I or Level II Mathematics Test score. These predictors were measured against the following variables: (1) ethnicity; (2) major; (3) language spoken; and (4) gender. The findings of the study showed that almost all of the predictors were statistically significant for academic success; however, no major sex differences were found among the students.

Lin and Overbaugh (2009) investigated the context of hybrid instruction in a study that was designed to explore whether gender has an influence on learners' preferences for synchronous or asynchronous modes of computer-mediated communication, and whether this decision impacts learners' self-efficacy towards knowledge acquisition. The participants were 180 teacher-education students (151 females and 29 males) enrolled in a hybrid (blend of traditional classroom instruction and online learning activities) foundations course at a United States research university with a proportionally high percentage of full-time commuters and/or distance enrollees. The findings of the study showed that, regardless of gender, two-thirds of the participants preferred asynchronous modes over synchronous ones. In addition, gender was weakly related to the participants' self efficacy in both modes. Linear regression indicated that self efficacy, in turn, was weakly related to academic performance.

It can be summed up that literature on gender differences in higher education reveals mixed results. While some studies show the males' advantage over females in academic success, the mainstream of these studies revealed the opposite. Nevertheless, some studies showed that gender has no effect at all on academic success but other variables have. These contradicted results may due to many reasons. This particular study is different from almost all of the previous studies because it did not tackle one particular university course as most studies did; instead, it involved all the courses required for graduation. Also, this study was not limited to a specific sample of students; instead it investigated all undergraduate students (26, 122) enrolled in the university in different stages of studying (freshmen, sophomores, juniors, and seniors). On the other hand, while most studies were limited in terms of time needed to conduct the experiment, this study investigated the students' achievement for a time span lasted from 2002 until 2007. In comparison with other literature review studies, this study is different in terms of number of subjects under investigation. That is to say, while some studies investigated students' performance in one or two courses, this study took all students' GPAs in all courses required for the BA degree. For all these reasons, this study is considered different from all previous studies and its findings are expected to be valuable because they will add additional valid and reliable results to the literature under investigation.

Purpose of the Study

The main purpose of this study is to find out whether gender differences exist in GPA among undergraduates in higher education at the University of Jordan or not. To achieve this purpose, the researchers sought to answer the following question:

Are there gender differences in academic performance among undergraduates in the University of Jordan?


Data and Sample

Data for this study was extracted from the undergraduates' records compiled by the registrar's unit of Jordan University saved as a longitudinal database in a computer center for 2002-2007 academic years. The original data included all 29,762 complete students' records in a common file format (Excel file) that contains all the necessary demographic information (student's name, faculty, area of study and GPA). Table 1 presents the descriptive statistics of the sample based on year of graduation and gender.

The study sample included 26,122 students (17,522 female, 8,600 male). The researchers excluded international, private admittance and completion program students (those constitute 8.7% of the population) because they come from different countries and have different socio-cultural backgrounds. The researchers also excluded students who were admitted not through the university entrance criteria (Tawjihi) but via an alternative mechanism (who constitute 3.5% of the population).

Statistical Analysis

Data analysis was performed using the statistical computer package (SPSS(c)). Descriptive statistics were also used. The analysis also included one way ANOVA which was used to test significance of differences between female undergraduates and male undergraduates GPAs by years, while t-tests were carried out to test the significance of differences between female undergraduates' and male undergraduates' GPAs in different areas of the study.

Delimitations of the Study

The results of this study are going to be generalized to the population of public Jordanian universities because all students admitted to the public universities system are subject to the same criteria.


Undergraduates' GPAs distribution by Gender

The GPAs distribution of female and male undergraduates as shown in Figure 1 reveals that female undergraduates have higher GPAs than male undergraduates' in all years from 2002 to 2007.


Gender differences in GPA among undergraduates in each year

Examination of the means for the six years regarding GPAs showed that GPAs were significantly different (F (5, 26120) = 7.045; p < .05). Upon this result, the null hypothesis (male and female undergraduates' have equal GPAs means across all years) was rejected. Thus, testing the differences for each year separately using t test (Levene's test for homogeneity of variances) was examined. Levene's test (W) was significant in the years "2002, 2005, 2006, 2007" respectively (W = 10.57, p =.001; W = 4.280, p = .039; W = 19.38, p =.000; W = 5.20, p = .023). Consequently, the not assumed equal variances oft-test in these years were interpreted. The results of this t-test as shown in Table 2 reveals that there were significant differences between the average GPAs for male and female in each year. The females had significantly higher GPAs than the males. The effect size" 2" (Eta-squared) obtained was .64, .46, .44, .55, .61, .67 respectively, implying that one can account for 44% ~67% of the variance for any student's GPA if gender is known.

Gender Differences in GPA by area of study

For more clarification, t tests were carried out to test possible differences between females and males' GPAs in different areas of the study. The results as shown in Table 3 were significant for the GPAs average in favor to female undergraduates in most areas of the study. Of the 74 areas of the study, 7 were discarded because they were cancelled at Jordan University in 2000, 46 were significant and only in 21 areas of study there were no significant differences in the GPAs regarded gender. Levene's test for homogeneity of variances was examined. The results of these tests indicated that the GPAs did not satisfy the assumption of homogeneity of variance. Thus, the Mann-Whitney U tests were employed to analyze the data again in these areas of study. The results were similar to those of the t-tests, revealing that female undergraduates' had statistically higher GPAs compared to the male undergraduates'.


The results of this study showed that female undergraduates had higher GPAs than male undergraduates. These findings agree with previous studies (Bridgeman & Wendler, 1991; Odell, 1989; Wainer & Steinberg, 1992) which pointed out that female students mostly obtained higher GPAs. These results could due to the fact that in the Jordanian cultural context, females are always encouraged to spend their free time studying at home or the university library; however, male students are usually free to leave the home at any time and spend less time in studying. Moreover, female students feel that they really have something to prove when they go to the university and succeed, also to prove to their families that they worked hard and that they did not waste their time and effort at the university. In the Jordanian culture, girls may feel pretty much doomed to be housewives if they do not make success through college, not that there is anything wrong with being a housewife, but according to many women, being successful worker gets more freedom compared to being just a housewife.

As for the gender differences, the results of the study revealed that there are significant differences between the females' and males' GPAs in 46 areas of specialization of the study in favor of female students. The results also showed that the other 21 areas of specialization of the study were not statistically significant different, due to the small number of students in these area of the study or because the sample size was unequal. At the national level, Sugden (2009) commented on a study conducted by the Higher Education Policy Institute in which she stated that female students of all ages and social ethnic groups now out strip male undergraduates in almost every subject including law and medicine and that they are also more likely to go to leading universities and achieve better grades.

Moreover, the findings of this study also agree with previous research findings (A1waqfi, 1997; Leonard & Jiang, 1999) which found out that females mostly perceive themselves as being more competent, having more positive attitudes towards completion higher education, possessing better study skills and having the feeling of being more efficacious. Smith (2004) argued that most women feel that getting good grades is the most important part of university life. To achieve such a goal, they believe that they need to work harder because they will compete in a male-dominated environment. Therefore, good grades become the "insurance policy" for success. Men, on the other hand, feel that it is not necessary to study hard; they tend to put going and playing sports and participating in university activities among their higher priorities than preparing for academic work. Therefore, male students become more likely than women to miss lectures because they believe that other things (i.e., playing sports, shopping, partying, making friendship, participating in on-campus activities, etc.) are the most important part of the university life.

In Jordan, women are starting to gain dominance in most areas of society. These differences could be due to the change in traditional beliefs in the society about women because of the success they achieve at the academic level. Therefore, we nowadays find that many of the majors at most colleges (particularly Medicine and Architecture) which are highly prestigious in the society started to have a majority of female, and this is contrary to the traditional stereotypical beliefs that girls go to the softer majors (i.e., Education, Psychology, English., etc). Thus, perhaps gender differences in academic performance tend to appear in such level of education, when enrolled female students at university increase their job opportunities in the future (WB, 2005). Consequently, the marriage chances will be better and more for females who complete their studies at the university than those who do not. Another reason, some families in Jordan society deal hardly with female when they failed, so the female students' tend to be more successful in the university to avoid stress from the family and society. So, we can say that the Jordanian society started to change their traditional beliefs about women by encouraging female students to complete their higher education.

The results allow us to conclude that the differences between male and female in academic performance are as clear and evident as the results obtained in research on academic performance in higher education, generally. Our challenge in the education context is an attempt to make an effort to correct the misconceptions about women performance in higher education.


The findings of this study indicated that female students had higher mean GPAs than male students at significant rate over the six years from 2002 to 2007. A significant effect size was detected for GPAs in all of the years of the study. Statistical evidence from most areas across all years in this study indicated that there were significant differences in GPAs between male and female students in favor of female students in all areas of study. Contrary to the stereotypical beliefs about women in the local society, the findings of the study suggest that although enrollment in higher education has greatly increased in Jordan, there remains a steady and significant difference gap between males and females in higher education. This implies that gender differences in academic performance in higher education in Jordan are real not stereotyping, and that these differences do not explain all aspects of gender gap in the Jordanian society, but do indicate a need for additional research and attention by those involved in decision making in higher education.


Afuwape, M. & Oludipe, D. (2008). Gender differences in integrated science achievement among pre service teachers in Nigeria. Educational Research and Review, 3 (7), 242-245. Retrieved on June 20 2010 from: Afuwape%20and%20Oludipe.pdf

Alsadah, H. (1993). Women's role in school books in the primary educational system in Bahrain. Paper presented at the Arab Curriculum between Planning and Implementation. Mohammad AlKhames University, Morocco (in Arabic)

Al-bedour, T. (2004). Gender roles which the youth develop within the Jordanian family. Unpublished master thesis, University of Jordan, Amman, Jordan. (in Arabic)

Al-waqfi, M. (1997). Gender differences in linguistic forms with particular reference to Jordan women's expressions of politeness. Unpublished master thesis, Yarmouk University, Irbid, Jordan.

Barrow, M., Reilly, B., Woodfield, R. (2009). The determinants of undergraduate degree performance. How important is gender? British Educational Research Journal, 35(4), pp. 575-597.

Berkant, H. (2009). An investigation of students' meaningful causal thinking abilities in terms of academic achievement, reading comprehension and gender. Educational Sciences: Theory and Practice, 9(3), pp. 1149-1165.

Bridgeman, B. & Wendler, C. (1991). Gender differences in predictors of college mathematics performance and in college mathematics course grades. Journal of Educational Psychology 83 (2), 275-284.

Clemons, T. (2008). Underachieving gifted students: A social cognitive model. National Research Center on the Gifter and Talented, University of Virginia, Charlottesville, Virginia. ED 505383.

Clifton, R., Perry, R., Roberts, L., & Peter, T. (2008). Gender, psychosocial dispositions, and the academic achievement of college students. Research in Higher Education, 49(8), 684-703.

Darwazeh, A. (1998). Variables affecting university academic achievement in a distance versus a conventional education setting. A paper presented at the National Convention of the Association for Educational Communication and Technology (AECT), St. Louis, MO.

Dayio lu, M. & Turut-A ik, S. (2007). Gender differences in academic performance in a large public university in Turkey. Higer Education, 53(2), 255-277. doi: 10.1007/s10734-005-2464-6.

Downing, K., Chan, S., Downing, W., Kwong, T. & Lain, T. (2008). Measuring gender differences in cognitive functioning. Multicultural Education & Technology Journal, 2(1), pp. 4-18.

Education.stateuniversity. (n.d). Jordan-Higher Education, Retrieved May 6, 2009, from HIGHEREDUCATION.html

Felder, R. M. et al. (1994). Gender differences in student performance and attitudes. A longitudinal study of Engineering student performance and retention. North Carolina State University, Report No. NCSU- 94A. (ED368553).

Hausmann, R., Tyson, L. & Zahidi, S. (2009). The global gender gap report. A report published by the World Economic Forum, Geneva, Switzerland. Retrieved May 28, 2009, from

Ismail, N. & Othman, A. (2006). Comparing university academic performances of HSC students at the three art-based faculties. International Education Journal, 7(5), pp. 668-675.

Leonard, D. K., & Jiang, J. (1999). Gender bias and the college predictors of the SATs: A cry of despair, Research in Higher Education, 40(4). 375-407. Retrieved March 6, 2009 from 8x5870j21/fulltext.pdf

Lin, S. Y., Overbaugh, R. C. (2009). Computer-mediated discussion, self-efficacy and gender. British Journal of Educational Technology, 40(6), pp. 999-1013.

Liu, W. C., Wang, C. K. (2005). Academic self-concept: A cross-sectional study of grade and gender differences in a Singapore secondary school. Asia Pacific Education Review, 6(1), pp. 20-27.

Mattox, D. 1997. A Study of the academic performance of male students compared to female students in secondary elective science courses. Unpublished masters' thesis at Salem-Teikyo University, Salem: West Virginia.

Nabulsi, T. M. (2002). Development of gender stereotypes and gender role orientations among Jordanian children and adolescents: personality traits, academic and vocational interests. Unpublished master thesis, University of Jordan. Amman: Jordan. (In Arabic)

Odell, K. S. (1989). Gender differences in the educational and occupational expectations of rural Ohio youth. Research in Rural Education, 5 (3), 37-41. Retrieved on March 3, 2010 from:,n3,p37-41,Odell.pdf

Public universities. (n.d). Ministry of Higher Education, Retrieved May 28, 2009, from

Sheard, M. (2009). Hardiness commitment, gender, and age differentiate university academic performance. British Journal of Educational Psychology, 79 (1), pp. 189-204.

Smith, F. (2004). "It's not all about grades": Accounting for gendered degree results in Geography at Brunel University. Journal of Geography in Higher Education, 28(2), pp.167-178.

Social Institutions and Gender Index (SIGI). (n.d.). Gender equality and social institutions in Jordan. Retrieved May 28, 2010, from

Sue, S. & Abe, J. (1988). Predictors of academic achievement among Asian American and white students. College Board Report No. 88-11. College Entrance Examination Board, New Your, NY. (ED303555).

Sugden, J. (2009, June 8). Women are achieving better grades at university, study finds. Timesonline, Retrieved March 8, 2010 from: article6451515.ece

The World Bank. (2005). The economic advancement of women in Jordan: a country gender assessment, social and economic development group Middle East and North Africa Region (MENA). Retrieved May 27, 2009 from /INTMNAREGTOPGENDER/Resources/JordanCGA2009.pdf

Wainer, H. & Steinberg, L. S. (1992) Sex differences in performance on the mathematics section of the Scholastic Aptitude Test: A bidirectional validity study, Harvard Educational Review, 62 (2), 323-336.
Table 1: Distribution of sample by year of graduation and gender


                Females                  Males
Year                                                      Total
        Number   % within year   Number   % within year

2002     2521        67.5         1213        32.5        3734
2003     2588        68.5         1192        31.5        3780
2004     3058        66.3         1556        33.7        4614
2005     3612        66.1         1855        33.9        5467
2006     4320        67.4         2094        32.6        6414
2007     1423        67.3         690         32.7        2113
Total   17522        67.1         8600        32.9        26122

Table 2: Students' GPAs means, standard deviations and t-values
based on year of graduation

Year   Gender    Mean     SD       T        df      [[eta].sup.2]

2002   Female   2.8085   .456
                                16.10 *   2511.22       0.64
       Male     2.5605   .432

2003   Female   2.8471   .471
                                14.03 *    3778         0.46
       Male     2.6159   .469

2004   Female   2.8419   .470
                                14.89 *    4612         0.44
       Male     2.6254   .458

2005   Female   2.8412   .488
                                16.98 *   3809.89       0.55
       Male     2.6076   .478

2006   Female   2.8137   .479
                                20.07 *   4343.18       0.61
       Male     2.5660   .455

2007   Female   2.8413   .481
                                12.75 *   1441.42       0.67
       Male     2.5681   .452

* P < 0.05

Table 3: T-values based on area of study

     Area of study               female                 Male

                           N    Mean     SD      N    Mean     SD

              Business    294   2.623   0.477   163   2.318   0.322

        Foundations of    599   2.845   0.468    88   2.621   0.481

           Archaeology    115   2.779   0.424    80   2.440   0.372

 Public Administration    208   2.416   0.363    93   2.216   0.244

          Land Water &     60   2.594   0.407    21   2.259   0.236

            Counseling    261   2.822   0.465    35   2.567   0.445

         Orthotics and     29   2.853   0.382    22   3.012   0.491
        Prosthetics **

             Economics    394   2.682   0.453   201   2.391   0.401

          Agricultural    186   2.647   0.347    57   2.258   0.317
         Economics and

          Agricultural      3   2.233   0.175     9   2.111   0.140
         Economics and
       Agribusiness **

     Animal Production     22   2.600   0.335    59   2.371   0.347

 Horticulture and Crop     48   2.584   0.341    21   2.471   0.384

      Plant Protection     91   2.761   0.415    41   2.417   0.347

               History    195   2.558   0.417    40   2.417   0.381

Clinical Laboratory **    143   2.996   0.512     9   2.680   0.575

     Special Education    391   2.941   0.474   309   2.507   0.394

    Physical Education    509   2.667   0.402   278   2.480   0.351

             Marketing    249   2.712   0.424   217   2.391   0.337

      Nutrition & Food    352   2.956   0.433    30   2.789   0.423

               Nursing    343   3.060   0.508   676   2.618   0.451

             Financing    224   2.794   0.525   128   2.614   0.480

             Geography    474   2.684   0.407   106   2.367   0.341

               Geology    188   2.599   0.378    46   2.464   0.340

           Mathematics    415   2.994   0.463    69   2.612   0.491

              Pharmacy    557   2.993   0.546   267   2.680   0.529

              Medicine    198   3.107   0.435   266   3.055   0.459

         Physiotherapy    216   3.058   0.431    39   3.011   0.466

     Area of study              female                  Male

                           N    Mean     SD      N    Mean     SD

          Occupational     73   2.859   0.367    10   2.777   0.376
            Therapy **

     Actuarial Science     98   2.588   0.491    60   2.652   0.440

               Biology    343   2.683   0.458    33   2.429   0.439

      Political Sconce    286   2.793   0.425   274   2.459   0.336

 Islamic Jurisprudence    514   2.892   0.472   163   2.613   0.473

         Philosophy **     38   2.875   0.365     1   2.402

        Visual Arts **     49   2.859   0.408    15   2.801   0.458

       Theater Arts **      3   2.825   0.353     3   2.750   0.607

               Physics    207   2.737   0.475    77   2.451   0.431

                   Law    637   2.811   0.452   648   2.473   0.392

             Chemistry    396   2.833   0.462    73   2.543   0.456

      English Language    771   2.907   0.479    80   2.701   0.543

       Applied English     48   3.054   0.424     1   2.963
           Language **

       Arabic Language    769   2.894   0.478   202   2.518   0.409

       French Language    203   2.883   0.535    27   2.355   0.410

       Spanish/English    368   2.811   0.515    30   2.708   0.528

       Germany/English    195   2.940   0.494    41   2.628   0.483

      Italian /English    246   2.866   0.508    26   2.546   0.428

            Accounting    271   2.998   0.546   371   2.567   0.494

 Agriculture Recourses    117   2.561   0.392    35   2.299   0.299
       and Environment

              Music **      6   2.879   0.334     2   2.990   0.371

Industrial Engineering    233   2.965   0.339   217   2.711   0.365

Electrical Engineering     61   2.914   0.302   325   2.899   0.422

  Chemical Engineering    216   2.818   0.432    50   2.647   0.525

     Civil Engineering    246   2.801   0.425   250   2.565   0.457

            Mechanical     30   2.498   0.320   314   2.643   0.400

      Plant Protection     32   2.547   0.345    26   2.381   0.375
              Computer    455   3.096   0.491   427   2.679   0.494
   Information Systems

  Business Information     92   2.861   0.444    73   2.469   0.368

     Area of study              female                  Male

                           N    Mean     SD      N    Mean     SD

       Child Education    455   2.741   0.455    10   2.390   0.292

             Dentistry    264   2.998   0.381   133   2.926   0.400

             Sociology    343   2.666   0.441    63   2.371   0.303

      Computer Science    333   2.921   0.513   400   2.583   0.470

            Psychology    308   2.735   0.432    55   2.529   0.414

      Hearing & Speech
              Sciences     22   2.853   0.491     1   2.817

     Classroom Teacher    892   2.856   0.447    95   2.629   0.391

        Field Teacher/      1   2.782             1   2.256
        Vocational (a)

        Field Teacher/     36   2.664   0.333     5   2.492   0.232
           Science (a)

        Field Teacher/    397   2.724   0.406    29   2.571   0.382
           English (a)

        Field Teacher/

  Islamic Religion (a)     22   2.786   0.394     4   2.211   0.155

        Field Teacher/
    Social Studies (a)     91   2.467   0.368    26   2.285   0.216

Field Teacher/ Math (a)    44   2.738   0.446     4   2.351   0.248

  Field Teacher/Arabic
          Language (a)    175   2.666   0.410    54   2.448   0.289

            Management     49   2.743   0.471    29   2.574   0.561
            Systems **

              Computer     84   3.152   0.463   212   2.858   0.541

          Architecture    184   2.872   0.372    59   2.809   0.454

          Mechatronics     55   3.050   0.244   193   2.779   0.447

     Area of study           Df         t         U

              Business    437.589    8.104 *

        Foundations of      685       4.19 *

           Archaeology      193       5.78 *

 Public Administration    253.785    5.616 *

          Land Water &     60.920    4.553 *

            Counseling      294       3.07 *

         Orthotics and       49       -1.30      268
        Prosthetics **

             Economics      593       7.68 *

          Agricultural      241       7.54 *
         Economics and

          Agricultural       10        1.24       8
         Economics and
       Agribusiness **

     Animal Production       79       2.67 *

 Horticulture and Crop       67        1.22

      Plant Protection      130       4.64 *

               History      233        1.98

Clinical Laboratory **      150        1.78     405.5

     Special Education    696.207    13.237 *

    Physical Education    637.789    6.787 *

             Marketing    460.214    9.075 *

      Nutrition & Food      380       2.04 *

               Nursing    619.749    13.617 *

             Financing      350       3.20 *

             Geography    178.615    8.344 *

               Geology      232        2.21

           Mathematics      482       6.28 *

              Pharmacy      822       7.77 *

              Medicine      462        1.23

         Physiotherapy      253        0.61

     Area of study           Df         t         U

          Occupational       81        0.66      320
            Therapy **

     Actuarial Science      156       -0.83

               Biology      374       3.06 *

      Political Sconce    539.188    10.317 *

 Islamic Jurisprudence      675       6.57 *

         Philosophy **       37        1.28       5

        Visual Arts **       62        0.47      328

       Theater Arts **       4         0.19       4

               Physics      282       4.62 *

                   Law    1251.519   14.299 *

             Chemistry      467       4.95 *

      English Language     92.252    3.265 *

       Applied English       47        0.21      18
           Language **

       Arabic Language    359.636    11.202 *

       French Language     38.852    6.044 *

       Spanish/English     33.657     1.023

       Germany/English      234       3.69 *

      Italian /English      270       3.09 *

            Accounting    546.640    10.264 *

 Agriculture Recourses     72.434    4.219 *
       and Environment

              Music **       6       -0.40 *      5

Industrial Engineering      448       7.64 *

Electrical Engineering    109.283     0.336

  Chemical Engineering     65.249    2.132 *

     Civil Engineering      494       5.95 *

            Mechanical      342       -1.92

      Plant Protection       56        1.76
              Computer      880      12.57 *
   Information Systems

  Business Information      163       6.07 *

     Area of study           Df         t         U

       Child Education     9.988     3.715 *

             Dentistry      395        1.75

             Sociology    116.326    6.572 *

      Computer Science    680.959     9.221

            Psychology      361       3.28 *

Hearing & Speech
Sciences    21        0.07      10

     Classroom Teacher    121.873    5.322 *

        Field Teacher/       0
        Vocational (a)

        Field Teacher/       39        1.11
           Science (a)

        Field Teacher/      424        1.97
           English (a)

        Field Teacher/

  Islamic Religion (a)       24       2.84 *

        Field Teacher/
    Social Studies (a)     70.429    3.166 *

Field Teacher/ Math (a)      46        1.70

  Field Teacher/Arabic
          Language (a)    124.690    4.360 *

            Management       76        1.43     527.5
            Systems **

              Computer    176.609     4.691

          Architecture     84.400     0.967

          Mechatronics    164.900    5.895 *

(a) : areas of study were cancelled at University of Jordan in 2000.

* P < 0.05

** Mann-Whitney U tests were employed to analyze the data again.

Empty cells refers that area of study is new or long time needed
to GPA available
Gale Copyright:
Copyright 2011 Gale, Cengage Learning. All rights reserved.