GM 28,4. The current issue and full text archive of this journal is available at

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1 The current issue and full text archive of this journal is available at GM 28,4 188 Gender and careers: a study of persistence in engineering education in Bangladesh Samina M. Saifuddin, Lorraine S. Dyke and Maria Rasouli Sprott School of Business, Carleton University, Ottawa, Canada Abstract Purpose The goals of this study were to examine the utility of social cognitive career theory in a South Asian context, extend SCCT beyond its individualistic roots to include social and contextual variables, and explore the possible differential validity of SCCT predictors for men and women. Design/methodology/approach The study involved an in-class survey of Bangladeshi undergraduate engineering students including 209 women and 640 men. Findings Despite stronger relationships between persistence and two predictors social aspirations and self-efficacy for men, self-efficacy, the core construct of SCCT, was the most important predictor of persistence for both women and men thus supporting the applicability of SCCT in non-western contexts. Research limitations/implications Several new measures were developed for this study which provide a basis for future research but will require further validation. The results demonstrated the applicability of SCCT in a non-western context but the amount of variance explained was modest. Thus, additional research into context-specific factors affecting persistence is warranted. Practical implications The results suggest that interventions intended to enhance the participation of women in non-traditional fields such as engineering should focus on enhancing self-efficacy, potentially through creating a more supportive learning environment. Originality/value The current study is one of the first to assess the applicability of SCCT in a non-western context and to examine the differential validity of SCCT predictors for women and men. Keywords Gender, Careers, Social cognitive career theory, Sex differences, Persistence, Engineering education, South Asia, Bangladesh Paper type Research paper Gender in Management: An International Journal Vol. 28 No. 4, 2013 pp q Emerald Group Publishing Limited DOI /GM Introduction Most career theories and models have been developed from a North American perspective and emphasize individual attributes such as interests, career goals and self-efficacy (Leong and Brown, 1995; Leung, 1995). The generalizability of these career theories to other contexts and cultures has received little attention (Fitzgerald and Betz, 1994; Hackett et al., 1991). Similarly, diversity issues have most often been viewed through a Western lens (Jones et al., 2000; Syed, 2008) despite the important role that cultural context can play (Combs et al., 2005; Syed and Ozbilgin, 2009). Gender researchers specifically have been criticized for ignoring the different dynamics of gender inequality in different cultures (Syed and Pio, 2010). Engineering education in South Asia is an interesting context in which to study the gender dynamics of career choices. The engineering domain has historically been a male-dominated profession (Küskü et al., 2007) and it has been argued that its masculine image discourages women from studying or persisting in engineering programs (Wyer, 2003). Despite the implementation of numerous diversity strategies to

2 increase women s participation in engineering programs (Lagesen,2007), women s participation has increased in only a few countries (e.g. Norway) and women continue to be underrepresented in engineering programs in most nations (Hersh, 2000). In contrast to women s declining enrolment in engineering programs in Western countries such as the USA and Canada (Vegso, 2008; Engineers Canada, 2011), the number of women enrolled in engineering majors is on the rise in some South Asian countries like India (Simard, 2007) and Bangladesh (BANBEIS, 2010). The purpose of the present study is to examine the contribution of Western career models to our understanding of gender differences in career behaviours in the context of the increasing participation of women in engineering education in South Asia. Specifically, we examine the utility of social cognitive career theory (SCCT; Lent et al., 1994) in explaining male and female students intentions to persist in their engineering education in Bangladesh. This study adds to the small body of research that has examined the choice and persistence of engineering students in non-western cultures (Saifuddin et al., 2011). The opposing trends in female engineering education in South Asia and North America suggest that environmental factors may play a role in shaping these career choices (Saifuddin et al., 2011). Models which have been used to explain the declining interest in engineering amongst North American women may not fully capture the dynamics of career choice for the increasing number of women drawn to engineering careers in South Asia. Thus, we attempt to expand SCCT beyond its individualistic roots to incorporate more social and contextual factors. Finally, we explore the differential validity of SCCT predictors in explaining the persistence of women and men. We hope that a better understanding of why Bangladeshi men and women persist in engineering programs may broaden our understanding of the dynamics of gender inequality in non-western contexts. This paper begins with an overview of the Bangladeshi context followed by a discussion of the conceptual framework SCCT and our hypotheses. We then present our methods and the findings from our survey of men and women enrolled in undergraduate engineering programs. Finally we discuss the implications of our findings for utilizing Western theories to understand career behaviour in South Asia. Gender and careers 189 The Bangladeshi context Bangladesh is a patriarchal, patrilineal, and patrilocal society where women traditionally derive their role from family (Chowdhury, 2010). Bangladesh ranks 69th overall out of 135 countries in the World Economic Forum s Global Gender Gap Report but only 108th in educational attainment and 118th in economic participation and opportunity (Hausmann et al., 2011). Female participation in the labour force increased sharply from 16 percent in 1996 to 26 percent in 2003 (International Labour Office (ILO), 2008). Women s participation in the labour force and women s emergence into public spaces as economic agents has been made possible largely by two sectors: the garment industry and non-governmental organizations (Feldman, 2001). The Bangladesh Bureau of Statistics reports that the highest numbers of women are employed in agriculture (58.7 percent), followed by community, social, and personal services (20.1 percent), and manufacturing (17.3 percent; BBS, 2003). Although women s participation in the labour market has increased, women remain highly concentrated in the lower paying informal labour market (ILO, 2008). One of the reasons that fewer women are found in the formal labour market is that women who have university educations generally come from

3 GM 28,4 190 families with higher socio-economic status (SES). These women are more likely to be faced with social prejudices and taboos favouring marriage and motherhood over professional careers ( Jahan et al., 1998; Rahman, 2005). Living in a majority Muslim country, Bangladeshi women are subject to oppression and exploitation due to certain interpretations of Islam (Chowdhury, 2009). For instance, the income earned by women is generally controlled by male members of their family (Chowdhury, 2010). Gender sensitivity in the workplace is rare, combining work and family is challenging and fear of sexual harassment is prevalent (Jahan et al., 1998). Chowdhury (2010) suggests that a large number of the Bangladeshi women who have joined the labour force from middle and lower income families have done so to provide economic support for their families. This has helped to change male attitudes toward employed women and to expand educational and employment opportunities for women recently. Greater emphasis on education in Bangladesh in the last few decades has resulted in a steady increase in student enrolment in undergraduate programs (a 323 percent increase from 2001 to 2008; BANBEIS, 2010) including increasing female enrolment overall and in engineering programs specifically. Among the top ranked engineering and technology universities in Bangladesh in 2009, the proportion of women students was approximately 20 percent overall. This proportion is close to the percent of all undergraduate students in Bangladesh who are female (BANBEIS, 2010). Current female enrolment in engineering and technology in Bangladesh is significantly higher than it was in the past and similar to the percentage of total female enrolment in Bangladeshi universities. We explore this paradox of increasing participation in engineering education in a less egalitarian culture by examining an expanded model of SCCT. Conceptual framework SCCT (Lent et al., 1994, 2000) draws primarily from general social cognitive theory (Bandura, 1986) and research on career and academic self-efficacy (Betz and Hackett, 1981, 1983; Lent et al., 1984). Self-efficacy refers to people s judgments of their capabilities to organize and execute courses of action required to attain designated types of performances and outcome expectations refer to a judgment of the likely consequence a behavior will produce (Bandura, 1986, p. 391). Building on the constructs of self-efficacy and outcome expectations, social-cognitive career theory posits that individual variables such as gender and self-efficacy, in interaction with aspects of the environment such as social support, shape an individual s career behaviour including choice and persistence (Lent et al., 2000). We chose to focus specifically on persistence in completing undergraduate training as a key outcome in engineering careers. Persistence in an education context refers to an individual s intention to continue in the chosen major through university and earn the degree. It is particularly important to understand the predictors of persistence where differential barriers may be faced by women and men in the educational process as has been suggested in previous studies of engineering education (Brainard and Carlin, 1998; Hartman and Hartman, 2002). Following SCCT, intention to persist in a chosen major is expected to be a strong predictor of actual persistence behaviour. The majority of the research examining SCCT has focused on individual cognitive variables, paying less attention to environmental variables. In less individualistic cultures, however, environmental variables may play a larger role. To apply SCCT more

4 fully in the current study, our model builds upon the framework of SCCT and incorporates both environmental and individual cognitive factors. Specifically, we explored the extent to which social supports, a supportive learning environment, career aspirations, and engineering self-efficacy influence students intention to persist in engineering programs. Consistent with SCCT, we predict that each of these variables will have a positive impact on persistence. Further, we predict that these factors may have differential effects on the persistence behavior of women and men. Our model is summarized in Figure 1. Gender and careers 191 Social support Most of the studies using the SCCT framework have focused more on individual cognitive variables, overlooking one of the main premises of SCCT the effect of social and contextual variables. A key social variable affecting career choices is social support. Key types of social support include the support individuals receive from parents, peers, and teachers in their career choice and subsequent actions. Among different types of social support, parents support is considered to be one of the most important forms of support in a young person s life. Parents support can play an important role not only during childhood and early adolescence but also during late adolescence and early adulthood when it has been shown to influence young adults persistence in science-related majors (Ratelle et al., 2005). Auyeung and Sands (1997) found that parental influence played a more important role in students choice of major in Eastern countries (Hong Kong and Thailand) than in Western countries (Australia). In addition to parents support, the role of peers and teachers support in college students persistence in their program has been well documented in the career literature (Farmer, 1985; McWhirter et al., 1998; Turner and Lapan, 2002). Based on the above evidence, we predict that for all three types of social support: H1a. Social support will be positively related to persistence for both women and men. Social Supports Parent Teacher Peer Supportive Learning Environment Career Aspirations Social Personal Financial Persistence in the program Engineering Self-Efficacy Gender Figure 1. Persistence in undergraduate engineering program

5 GM 28,4 192 A number of scholars have suggested that women need more social support than men to persist in male-dominated majors (Ahuja, 2002; Adya and Kaiser, 2005). A study by Lent et al. (2005) suggested that perceived social support was significantly higher for women than men in pursuit of engineering studies although women and men did not differ significantly in their experiences across most social cognitive variables. Women may require extra social support to help them overcome the barriers to women s participation in engineering programs. This would imply that social support may play a particularly important role in women s persistence in engineering. Therefore, we predict that: H1b. Social support will be more strongly related to the persistence of women than men. Supportive learning environment Existing evidence points out the potential importance of a supportive learning environment in the persistence of students in engineering majors. The literature on persistence in non-traditional academic majors suggests that classroom experiences (e.g. classroom climate, interactions with faculty, staff, and peers) as well as out-of-classroom experiences (e.g. ability to find satisfactory co-ops or internships) together create an overall learning environment which influences persistence. A positive learning environment increases the likelihood of persistence (Adelman, 1998; Cabrera et al., 2001). On this basis, we predict that: H2a. A supportive learning environment will be positively related to persistence for both women and men. Previous research has indicated that many women experience a chilly climate in engineering programs and that this less supportive climate can constitute a barrier to women s participation in engineering education (Brainard and Carlin, 1998). This analysis suggests that a supportive climate may play a critical role in encouraging women in engineering careers. A study by Hartman and Hartman (2002) found that perceptions of a supportive learning environment impact both the recruitment and persistence of women in science, technology, engineering, and math fields. Based on the existing evidence, we predict that: H2b. A supportive learning environment will be more strongly related to the persistence of women than men. Career aspirations According to Ali and Sauders (2009), within SCCT, career aspirations can be viewed as distal goal mechanisms, by which students organize and sustain their career-related behaviours in the absence of immediate reinforcement. Career aspirations may reflect the social, personal, and financial goals that individuals aspire to achieve in the future (Dyke et al., 2007). Somers et al. (2004) found that students with higher career aspirations were more likely to persist in their college program than students with lower career aspirations. Therefore, we predict that for all three types of aspirations: H3a. Higher career aspirations will be positively related to persistence for both women and men.

6 Using the framework of SCCT, Farmer et al. (1995) found that persistence in science, math, and technology majors for men was related to the level of career aspirations. In contrast, the study indicated that, for women, persistence was related to the number of math and science related courses undertaken in high school. These results are congruent with the notion that external barriers may prevent women from following through on their career aspirations in engineering programs. Faced with external barriers, the link between women s aspirations and their persistence in an engineering career may be attenuated. We therfore hypothesize: H3b. Career aspirations will be more strongly related to the persistence of men than women. Gender and careers 193 Self-efficacy Self-efficacy refers to a person s belief in his or her ability to successfully perform a given task or behavior (Betz and Hackett, 1981). Self-efficacy has repeatedly been shown to be a significant predictor of choice, persistence, and intention to pursue an engineering and technology-related career (Betz and Hackett, 1983, 2006; Fouad et al., 2002; Lent et al., 2008, 2011). Higher levels of self-efficacy are related to greater persistence in college majors (Lent et al., 1984, 1986; Restubog et al., 2010) and lower academic program turnover (Restubog et al., 2010). Since self-efficacy is about the feelings of being efficacious in a specific context, Betz and Hackett (1983) have strongly suggested that task specific efficacy constructs are better predictors of behaviours than more general efficacy measures. Given the existing theory and evidence, we hypothesize: H4a. Engineering self-efficacy will be positively related to persistence for both women and men. Self-efficacy may be especially important for those women pursuing non-traditional career choices such as engineering. Betz and Hackett (1981) found significant and consistent gender differences with regard to self-efficacy in traditional and non-traditional occupations. Male undergraduate students reported equivalent self-efficacy for traditional and non-traditional occupations, whereas females undergraduate students reported substantially lower self-efficacy expectations for non-traditional occupations (e.g. engineering) compared to traditional occupations (e.g. hygienist). This evidence suggests that male-dominated domains such as engineering may provide little encouragement to women (Sagebiel and Dahmen, 2006). In this environment, women are only likely to persist if they have a strong sense of self-efficacy. Therefore, we predict that: H4b. Self-efficacy will be more strongly related to the persistence of women than men. In addition to our focal constructs, we included SES as a control variable. Although the original model of SCCT did not include SES, Lent et al. (1994) noted that SES can play a role in the learning experiences of individuals and subsequently influence their self-efficacy. SES has been found to be an important determinant of women s choice of non-traditional careers (Fouad and Brown, 2000; Salami, 2007; Tang et al., 1999). As reported by Lareau (2003) children from higher SES families are exposed to more professional career choices which in later years may translate into opting for non-traditional careers. Yet some studies (Farmer et al., 1995; Jackson et al., 1993) have

7 GM 28,4 194 found no effect of SES on persistence for men or women. It is possible that SES plays an important role in the choice of non-traditional academic majors but it may not be an important factor in persistence in a major. Once in the program, proximal factors (e.g. meeting personal expectations, self-efficacy, workload, etc.) may have more influence on persistence behaviour ( Jackson et al., 1993). In light of the potential confounding effects of SES, it is treated as a control variable in the proposed model of persistence. Method With the permission of instructors, questionnaires were distributed in undergraduate engineering classes in five Bangladeshi universities. Participation was voluntary. Students responded to the surveys in class and returned them to the researcher immediately. All surveys were completed in English in approximately 30 min. Measures The majority of the studies aimed at identifying the factors influencing students choice of and persistence in engineering majors have been conducted in a Western context. Due to the lack of validated measures for the South Asian context, we adapted items from various existing measures as well as developed measures specifically for this study. To evaluate the suitability of the adapted measures, factor analyses were conducted. Principal axis factoring with varimax rotation was used and factors with Eigen values greater than 1 were retained. Items with a factor loading below 0.3 were excluded. Items with significant loadings on a factor were summed to create the final scales. Cronbach s a was calculated to assess the reliability of multi-item scales. In the interests of brevity, only the factors and items which were retained are presented below. Details of the original scales are available from the authors. All of the items measuring the independent variables were assessed on five point scale with responses ranged from strongly disagree (score of 1) through neither agree nor disagree (score of 3) to strongly agree (score of 5). Persistence in the program. The dependent variable was measured by asking students, how confident are you that you will keep your chosen engineering major through university? Responses ranged from Not at all confident; I am already planning to change my major (score of 1) through There is about a 50 percent chance that I ll change my major (score of 3) to I am very confident that I will keep my current choice as my major (score of 5). Social support. As expected, factor analysis extracted three social support factors social support from parents, teachers, and peers. The total variance explained was 39 percent. Parents support consisted of four items with a ¼ A sample item was the influence of parents and family members is important for generating interest in engineering. Teachers support consisted of three items with a ¼ A typical item was My teachers inspired my interest in engineering major. Peers support consisted of three items with a ¼ A sample item was My friends encouraged me in my choice of major. Supportive learning environment. A supportive learning environment was measured with eight items developed for this study. All items loaded on one factor which accounted for 44 percent of the total variance. Cronbach s a was The items measured students perceptions of a supportive learning environment both

8 in the classroom and outside of it. A sample item related to positive interactions with other engineering students. Career aspirations scale. Career aspirations were measured with a 14-item scale adopted from Dyke et al. (2007). Factor analysis resulted in three factors social, personal, and financial aspirations which accounted for 51 percent of the variance. The social aspirations subscale consisted of seven items with a ¼ An example was Being surrounded by stimulating people. The personal aspirations subscale consisted of five items with a ¼ An example was Being able to learn and develop new skills. The financial aspirations subscale consisted of two items with a ¼ A sample items was Earning a salary that provides me with a comfortable lifestyle. Engineering self-efficacy. Engineering self-efficacy was measured with four items from the longitudinal assessment of engineering self-efficacy (LEASE Marra and Bogue, 2006) plus one additional item abilities and talents fit the requirements of the engineering degree. The final five-item scale for engineering self-efficacy had a ¼ 0.70 and accounted for 48 percent of the variance. A sample item was I can succeed in an engineering program. Socio-economic status. Following previous research (Nam and Boyd, 2004), SES was measured as a combination of parents educational scores and annual family income. The questionnaire asked for annual family income and information on the educational attainment of the participants parents (father and mother). Both parents educational attainment and annual family income were transformed into standard z-scores. The SES variable was created by averaging the z-scores. Gender and careers 195 Participants A total of 849 students responded to the survey from different engineering majors. One-quarter (n ¼ 209) were female. The sample represented all four years in the undergraduate program although representation from first year students was comparatively low (8 percent). A x 2 -test indicated that there were no significant gender differences in the distribution of respondents across program years. The mean age of respondents was 21 years. Income data, categorized using Khan s (2010) norms for Bangladesh, indicated that 22 percent of the respondents belonged to the low income group, 56 percent of the respondents fell into the mid-income group and 22 percent of the respondents belonged to the high-income group. Analysis In examining group differences such as those between men and women, three different types of differences are possible. First, there may be differences in the mean levels of predictor variables. Taking the relationship between education and salary as an example, women may have more education than men but this does not tell us whether the relationship between education and salary is the same for both genders. A second possibility is that there are differences in the degree of relationship between the two variables, that is, differential validity of the predictors. For instance, education might explain more of the variance in salary for women than for men. And finally, differences may exist in the form of the relationship. For example, education might be related to salary in a linear fashion for women but in a non-linear fashion for men. Differences in the form of relationship are generally tested using interactions in hierarchical multiple regression. Differences in the degree of relationship, however, cannot be determined using

9 GM 28,4 196 hierarchical regression incorporating product terms (Arnold, 1982). Instead differences in the degree of relationship need to be examined by testing for differences in correlation coefficients between groups (Arnold, 1982). Since our gender hypotheses relate to differences in the degree or strength of the relationships between persistence and the predictors, we tested the differences between correlation coefficients using Fisher s z-test. Results Means for all study variables are shown separately for women and men in Table I. Male and female students showed similarly high intentions to persist in their program (means of 4.3 out of five). On average, female students came from families with higher SES, had higher personal and financial aspirations, and reported lower peer support. Women and men reported a similarly supportive learning environment and equal levels of engineering self-efficacy. Correlations of all study variables are reported separately for women (Table II) and men (Table III). As shown in Table II, for female students, a supportive learning environment, personal aspirations, and engineering self-efficacy were significantly and positively related to intention to persist in their engineering program. For male students (Table III), perceived peer support, a supportive learning environment, all three aspirations social, personal, and financial and engineering self-efficacy were significantly and positively related to intention to persist in their engineering program. Taken together, these results provide support for the hypothesized effects of both a supportive learning environment (H2a) and engineering self-efficacy (H4a) for both women and men. Only partial support is indicated for H1a and H3a regarding the positive impact of social support and aspirations respectively. In order to assess the differential validity of the model variables, that is the relevance of each independent variable in predicting male and female engineering students persistence, the correlations between the dependent and independent variables were compared for women and men. To test for significant differences in the degree or strength of the relationship for men and women, a one-tailed Fisher z-test of the difference between the sub-group correlations was calculated (Arnold, 1982). The correlation coefficients between persistence and the predictors for both women and men are shown in Table IV along with significance of the difference between them. Female Male Significance (two-tailed) Table I. Gender differences in means Persistence in engineering program SES *** Parent support Teacher support Peer support *** Supportive learning environment Social aspiration Personal aspiration * Financial aspiration * Engineering self-efficacy Note: Significant at: * p, 0.05, ** p, 0.01 and *** p, 0.001

10 Mean SD (1) (2) (3) (4) (5) (6) (7) (8) (9) (1) Persistence (2) SES (3) Par Supp * (4) TeachrSupp * (5) Peer support * * (6) Supp LENV * * * * (7) Soc Asp * (8) Per Asp * * * (9) Fin Asp * * * (10) Eng SE * * * * * Note: Correlation is significant at: * 0.01 level (two-tailed) Gender and careers 197 Table II. Correlations analysis for women

11 GM 28,4 198 Table III. Correlations analysis for men Mean SD (1) (2) (3) (4) (5) (6) (7) (8) (9) (1) Persistence (2) SES (3) Par Supp (4) TeachrSupp ** (5) Peer support * ** ** ** (6) Supp LENV ** ** ** ** (7) Soc Asp ** ** ** ** ** (8) Per Asp ** * ** ** (9) Fin Asp * * ** ** ** ** (10) Eng SE ** ** ** ** ** ** Note: Correlation is significant at: * 0.05 and ** 0.01 levels (two-tailed)

12 Independent variables Female Male Significance (one tailed) Parent support Teacher support Peer support * Supportive learning environment ** ** Social aspiration ** * Personal aspiration ** ** Financial aspiration * Engineering self-efficacy ** ** * Note: * p, 0.05, ** p, 0.01 and *** p, Gender and careers 199 Table IV. Degree of relationship persistence in engineering program The results of the Fisher z-tests shown in Table IV reveal that social support and a supportive learning environment did not have differential impacts for women and men. Thus, H1b and H2b were not supported. Personal and financial aspirations also did not have a differential impact for men and women, however, social aspirations had a significantly stronger impact on men s persistence compared to women s. These results provide partial support for H3b which suggested that aspirations would have a stronger impact on men s persistence. In contrast to H4b, the effect of self-efficacy on persistence was higher for men than for women. Given the gender differences in the degree of relationship between some of the predictors and persistence, we ran separate hierarchical multiple regression analyses for women and men in order to examine the relative contribution of the predictors to persistence (see Table V for the results). In step 1 SES was entered into the model as a control variable. Social support and a supportive learning environment, as proximal contextual constructs, were added to the model in steps 2 and 3 and the individual variables of career aspirations and engineering self-efficacy were added in steps 4 and 5 respectively. The regression analysis for female students indicated that SES (step 1) and social supports (step 2), did not contribute significantly to the variance in persistence, thus providing no support for H1a for female students. In step 3, a supportive learning environment accounted for 3.6 percent of the variance in persistence ( p, 0.05); however, this relationship did not hold once other variables were included in the later steps of the analysis. Thus, H2a was not supported for women. Career aspirations (step 4) did not contribute significantly to the explanation of intentions to persist so H3a was not supported for women. Engineering self-efficacy accounted for 4 percent of the variance in persistence ( p, 0.01), thus supporting H4a for women. In the final model, only one significant predictor self-efficacy (b ¼ 0.24, p, 0.01) remained and the model accounted for 12.4 percent of the variance in intention to persist. Based on the final regression model, only H4a was supported for female students. Similar to the regression results for female students, the regression results for male students (see Table V for details) indicated that SES (step 1) and social supports (step 2) did not contribute significantly to persistence in engineering majors. Thus, H1a was rejected for male students. Once again, a supportive learning environment accounted for significant variance in step 3 (4.4 percent, p, 0.001), but was not significant in the final model. Thus, H2a was also rejected for men. Career aspirations (step 4) added

13 GM 28,4 200 Table V. Hierarchical regression results Step and statistic Female Male Step 1 R 2 model Step 1 b SES Step 2 R 2 model Step 2 b SES Step 2 b Parent support Step 2 b Teacher support Step 2 b Peer support Step 2 DR Step 3 R 2 model * *** Step 3 b SES Step 3 b Parent support Step 3 b Teacher support Step 3 b Peer support Step 3 b Supportive learning environment ** *** Step 3 DR * *** Step 4 R 2 model * *** Step 4 b SES Step 4 b Parent support Step 4 b Teacher support Step 4 b Peer support Step 4 b Supportive learning environment * *** Step 4 b Social aspiration Step 4 b Personal aspiration * *** Step 4 b Financial aspiration Step 4 DR *** Step 5 R 2 model *** *** Step 5 b SES Step 5 b Parent support Step 5 b Teacher support Step 5 b Peer support Step 5 b Supportive learning environment Step 5 b Social aspiration Step 5 b Personal aspiration ** Step 5 b Financial aspiration Step 5 b Engineering self-efficacy ** *** Step 5 DR ** *** Notes: Significant at: * p, 0.05, ** p, 0.01 and *** p, 0.001; standardized regression weights (b) are reported significantly to the explanatory power of the model in step 4 (3.5 percent, p, 0.001) and personal aspirations remained significant in the final model, providing partial support for H3a for men. Engineering self-efficacy (b ¼ 0.36; p, 0.001) made the strongest contribution to the model explaining an additional 10.5 percent of the variance in persistence ( p, 0.001) in step 5. Overall, 19.3 percent of the variance in the persistence of men was explained by the two significant predictors: engineering self-efficacy (b ¼ 0.36, p, 0.001) and personal aspirations (b ¼ 0.15, p, 0.01). Based on the final model, H4a was supported, H3a was partially supported, and the remaining hypotheses were rejected for male students.

14 Discussion The goals of the current study were to examine the utility of Western career models specifically SCCT in a South Asian context and to extend SCCT beyond its individualistic roots to include social and contextual variables. Further, we were interested in exploring the possible differential validity of SCCT predictors for men and women pursuing engineering careers in South Asia. In general, the results supported the value of SCCT and the key role that individual SCCT variables self-efficacy and outcome expectations (here measured as career aspirations) play in predicting career behaviours such as persistence in undergraduate education. Social and contextual variables did not add significantly to the explanatory power of the model despite being tested in the less individualistic culture of Bangladesh. Thus, the results provide support for the generalizability of SCCT. The results also suggest that some SSCT predictors have differential validity for women and men. Specifically, social aspirations and engineering self-efficacy were more highly related to persistence for men than for women. This is an interesting finding as it is contrary to previous theorizing that a strong sense of self-efficacy is required for women to pursue non-traditional careers such as engineering (Sagebiel and Dahmen, 2006). Further these results suggest that researchers need to be cautious in pooling data from women and men when testing models of career behaviour. While women reported lower levels of peer support, none of the social support variables (parents, peers or teachers) had a significant impact on the persistence of either women or men. One possible explanation for the lack of impact of social support is that only those students who have strong social support choose to enter challenging fields such as engineering. The mean scores do not, however, support this interpretation as the average level of perceived social support for men and women across the three categories of support is 3.17 out of five. A more contextual explanation is that in Bangladesh engineering majors are viewed as very prestigious and admission is extremely competitive. Thus, there is a strong norm that students who win admission follow through with the program regardless of the support they receive (Saifuddin et al., 2011). Both men and women reported modest levels of support from their learning environment (means of 3.21 and 3.18 respectively, out of five). Contrary to previous research (Hartman and Hartman, 2002), a supportive learning environment was no more important to women than to men. A supportive learning environment was significantly correlated with the persistence of both women and men; however, when self-efficacy was included in the model, a supportive learning environment was no longer significant. A supportive learning environment and self-efficacy were positively related for both women and men (r ¼ 0.41 and r ¼ 0.33 respectively). Taken together, these results suggest that the effects of a supportive learning environment may operate through increasing self-efficacy which in turn drives persistence. These results are consistent with Byars-Winston et al. (2010) study which found no direct relationship between a supportive learning environment and persistence among engineering students. There were significant gender differences in aspirations. Interestingly, women reported higher personal and financial aspirations than men, and similar social aspirations. These findings contrast with Cross and Linehan s (2006) assertion that Gender and careers 201

15 GM 28,4 202 women hold themselves back in technology-related fields by limiting their aspirations. While women had higher means on some aspirations, social aspirations were more highly correlated with men s persistence than with women s persistence. This finding did not hold, however, in the final model. The only aspirations which were significant in the final model were personal aspirations and these were significant for men only. The prospect of doing work that they enjoy, making a contribution to society, learning new skills, obtaining a personal sense of acomplishment, and taking positions with increased responsibility contributed to men s intention to persist in their engineering degree. Neither men s nor women s persistence was influenced by what they aspired to achieve in terms of social rewards (e.g. making their family proud, gaining prestige and having authority), nor in terms of their aspirations for financial rewards. These results may reflect the Bangladeshi context in which educational majors are chosen not according to student interests but through standardized testing of abilities ( Jahan et al., 1998). Another potential contextual explanation for the disconnect between women s aspirations and their persistence relates to the age cohort of the students. The ages of are perceived as the prime marriage time for women in Bangladesh. Given the patriarchal nature of the society (Chowdhury, 2010), female students higher aspirations levels may not have translated into persistence due to other factors not explored in this study such as gender stereotypes or family norms. As in previous research (Concannon and Barrow, 2009; Lent et al., 2005), men and women reported equal levels of engineering self-efficacy. Separate hierarchical regressions for women and men indicated that higher self-efficacy resulted in greater persistence for both. Again, these results are consistent with previous findings (Lent et al., 2011; Restubog et al., 2010; Schaefers et al., 1997; Singh and Fouad, 2011). Contrary to our hypothesis, however, self-efficacy had a stronger impact on men s persistence than on that of women. This result is the opposite of Cancannon and Barrow s (2010) finding that women s self-efficacy beliefs accounted for more variance in intentions to persist in engineering programs than did those of men. It is possible that this result reflects minor differences in the measures and models applied in the two studies; however, it may also reflect differences in the Bangladeshi vs American context. As suggested previously, it may be that Bangladeshi women s persistence is influenced by other variables not considered in this study such as gender roles and family expectations. In fact, the results provide some support for this conjecture as the final model explained only 12 percent of the variance in female peristence while explaining 19 percentofthevarianceinmalepersistence. There were significant gender differences with respect to SES in the current study. Female students came from families with higher SES compared to male students. Echoing earlier findings, however, SES was not a significant predictor of persistence for women or men (Farmer et al., 1995; Jackson et al., 1993). About 78 percent of the respondents in this study belonged to middle- or high-income groups. Thus, as suggested by Adya and Kaiser (2005), the relative homogeneity of the sample may have limited the effects of SES in the present study. Limitations and suggestions for future research Most of the existing literature on sex differences in engineering careers has been conceptual or qualitative in nature. As a result, there were no previously validated scales for some of the variables measured in the current study (e.g. supportive learning environment and career aspirations). The scales used in the present study were based on

16 the existing literature and generally demonstrated reasonable reliability. Thus, the present study provides a number of sound preliminary measures for future researchers to use. Nevertheless, further development and testing of important predictors such as social support, supportive learning environment and career aspirations, is warranted. In this study, we examined sex differences rather than sex role orientation. Conceptualizing gender from this perspective is problematic because it imposes a uniformity assumption, i.e. all women are alike (Eagly, 1995). To guard against this potentially problematic assumption, Lent and Hackett (1987) have recommended studying gender salience or sex role orientation rather than biological sex. Given the strongly patriarchal nature of Bangladeshi society, there may be less variability in gender salience or sex role orientation than in Western countries. Nevertheless, future research should explore the impact of the psycho-social dimensions of sex-role on career behaviours in non-western contexts. The current study was cross-sectional. Longitudinal studies on persistence in engineering programs would help to better understand issues of causality. For instance, it makes sense logically to surmise that a supportive learning environment leads to enhanced self-efficacy (rather than the reverse), however, cross-sectional data cannot support causal inferences. The amount of variance explained by the models was modest, especially for women. This suggests that other variables which play a critical role in the persistence intentions of Bangladeshi undergraduate engineering students might have been overlooked in the current study. Future researchers may consider including in the model such additional individual variables as personality measures, outcome expectations, interests, and goals to further investigate the predictors of persistence. Contextual factors such as the marriage expectations of female students may also help us to better understand persistence in engineering for Bangladeshi students. Mellström (2009) argues that due to the individualist orientation of Western culture, researchers in a Western context overemphasize personal factors. The present study examined contextual variables social supports and a supportive learning environment but these variables were not significant in the final models. While an attempt was made to expand upon the models used in many SCCT studies, the variables selected for inclusion in this study were mainly drawn from theories of women s career development that are anchored in the context of Western countries. Thus, there may be other variables, relevant to the Bangladeshi context, which have been overlooked. One potential avenue for future research is to conduct exploratory qualitative studies in a South Asian context to identify important cultural assumptions that affect gender dynamics and which may not have been identified in Western research. Mellström (2009) also argues that in order to understand the predictors of women s choice and persistence in non-western contexts, it is important to examine gender and technology from an intersectional perspective including a variety of factors such as class, sex, national context, market demand, etc. Undoubtedly, future research can benefit from an intersectional analysis of diversity. Nevertheless, the current study is one of the first to examine SCCT one of the best-known career theories in a non-western context. It is hoped that this study will motivate researchers to conduct more cross-cultural studies in this field. In conclusion, self-efficacy, the core construct of social learning theory (Bandura, 1986) and SCCT (Lent et al., 1994) was found to be the most important Gender and careers 203

17 GM 28,4 204 predictor of both men s and women s persistence in engineering undergraduate programs in Bangladesh. This finding provides support for the applicability of SCCT beyond the Western context. However, other elements of SCCT including some career aspirations and contextual factors such as social support and a supportive learning environment were not supported. Further, some of the findings, which are inconsistent with those of previous Western research, highlight the importance of also understanding the cultural assumptions which underlie gender dynamics in different contexts. The results suggest that more research in non-western contexts will be needed to fully understand gender differences in career behaviours in fields such as engineering. References Adelman, C. (1998), Women and Men of the Engineering Path: A Model For Analyses of Undergraduate Careers, US Department of Education Sciences, Washington, DC. Adya, M. and Kaiser, K.M. (2005), Early determinants of women in IT workforce: a model of girls career choices, Information, Technology, and People, Vol. 18 No. 3, pp Ahuja, M.K. (2002), Women in the information technology profession: a literature review, synthesis and research agenda, European Journal of Information Systems, Vol. 11, pp Ali, S.R. and Sauders, J.L. (2009), The career aspirations of rural Appalachian high school students, Journal of Career Assessment, Vol. 17 No. 2, pp Arnold, J.H. (1982), Moderator variables: a clarification of conceptual, analytic, and psychometric issues, Organizational Behaviour and Human Performance, Vol. 29 No. 2, pp Auyeung, P. and Sands, J. (1997), Factors influencing accounting students career choice: a cross-cultural validation study, Accounting Education, Vol. 6 No. 1, pp BANBEIS (2010), University Education Bangladesh Bureau of Educational Information and Statistics, available at: (accessed February 10, 2011). Bandura, A. (1986), Social Foundation of Thoughts and Action: A Social Cognitive Theory, Prentice-Hall, Englewood Cliffs, NJ. BBS (2003), Labour Force Survey 2003, Bangladesh Bureau of Statistics, Dhaka. Betz, N.E. and Hackett, G. (1981), The relationship of career related self-efficacy expectations to perceived career options in college women and men, Journal of Counselling Psychology, Vol. 28, pp Betz, N.E. and Hackett, G. (1983), The relationship of mathematics self-efficacy expectations to the selection of science-based college majors, Journal of Vocational Behavior, Vol. 23, pp Betz, N.E. and Hackett, G. (2006), Career self-efficacy theory: back to the future, Journal of Career Assessment, Vol. 14 No. 1, pp Brainard, S.G. and Carlin, L. (1998), A six-year longitudinal study of undergraduate women in engineering and science, Journal of Engineering Education, Vol. 87 No. 4, pp Byars-Winston, A., Estrada, Y., Howard, C., Davis, D. and Zalapa, J. (2010), Influence of social cognitive and ethnic variables on academic goals of underrepresented students in science and engineering: a multiple-groups analysis, Journal of Counseling Psychology, Vol. 57 No. 2, pp