Gender Differences in Engineering Classrooms: Sugar and Spice and Everything Nice?

The purpose of this paper is to examine ways in which pedagogy and gender of instructor impact the development of self-regulated learning strategies as assessed by the Motivated Strategies for Learning Questionnaire (MSLQ) in male and female undergraduate engineering students. One hundred seventy-six students from four universities participated in the study. Within-group analyses found significant differences with regard to pedagogy, instructors’ gender, and student gender on the learning strategies and motivation subscales as operationalized by the MSLQ. Pedagogy was operationalized as two general formats: lecture plus active learning techniques or problem-base/project-based learning. Male and females students reported significant post-test differences with regard to the gender of instructor and the style of pedagogy. The results of this study showed a pattern where more positive responses for students of both genders were found with the same-gendered instructor. The results also suggested that male students responded more positively to project and problem based courses with changes evidenced in motivation strategies and resource management. Female students showed decreases in motivation and resource management in these two types of courses. It is important to note that both of the instructors of problem-based and project-based courses were male, thus the result may be an interaction of the instructors’ gender with pedagogy. Further, both male students and female students reported increases in lecture with active learning courses. Implications of these findings include the importance of female students having the opportunity to develop positive relationships with female faculty members to increase retention rates among female students in science, technology, engineering and mathematics (STEM) fields. SELF-REGULATED LEARNING, GENDER DIFFERENCES, ENGINEERING EDUCATION 3 Gender Differences in Engineering Education: Sugar and Spice and Everything Nice? Statistics examining undergraduate education, graduate education and the work force consistently show major disparities between the numbers of males and females in the fields of science, technology, engineering and mathematics (STEM). There is no dispute that women are underrepresented in science, technology, engineering and math (STEM) fields. For example, the National Center for Education Statistics found that in the year 2008, the percentage of bachelor’s degrees (in any field) earned by women was 57.3% and the percentage of bachelor’s degrees earned by males (in any field) was 42.7% (http://nces.ed.gov). Despite the fact that more female students are earning bachelor’s degrees than male students overall, in engineering the ratio remains significantly skewed with 69,724 males receiving a bachelor’s degree in engineering and only 14,129 female students earning such a degree (http://nces.ed.gov). If one considers that the number of bachelor’s degrees in engineering awarded to females in 1966 was only 146(National Science Foundation, 2010), the 2008 distribution represents nearly a ten thousand percent increase for female engineering graduates. However, the actual percentage of female awardees in the distribution has only changed from 0.1% to 1.6% in the past forty years (National Science Foundation, 2010). What can account for this discrepancy and slow rate of change? The question is one that has been debated by researchers for the past forty years, with no single cause rising to the top as more salient than another. Researchers have examined many factors in search of an explanation for why there are so few women in STEM fields. One possibility is that parents inadvertently encourage their daughters to focus on subjects that are ‘traditionally’ more feminine, such as reading or writing (Eccles-Parsons, Adler & Kaczala, 1982). Another is the lack of female role models in STEM fields (Blickenstaff, 2005). Others have focused their attention on the ‘chilly climate’ reported by some female students in university-level courses (Warrington & Younger, 2005). In addition to SELF-REGULATED LEARNING, GENDER DIFFERENCES, ENGINEERING EDUCATION 4 the explanatory factors listed above, many others exist for these differences including biological factors (Sadker & Sadker, 1994), poor academic preparation (Cole, 1997), and low levels of self-confidence (Brainard & Carlin, 1998). While it is important to determine the underlying causes for these discrepancies in attracting and retaining females to STEM fields, it may be enlightening to examine how pedagogical approaches in engineering college classrooms affect motivation and the use of learning strategies that would allow both male and female students to derive maximum benefit from their experience. The purpose of this study is to examine how different types of engineering learning environments contribute to the development of lifelong learning skills among engineering undergraduates, with a specific focus on the interaction of instructor’s gender with that of the student and within particular pedagogies. The independent variables of instructor gender and pedagogical style were specifically targeted and the questions asked were whether male and female students respond differently to different learning environments or to the gender of their instructors. Examining differences associated with the cognitive, behavioral, motivational and contextual factors that lead to the development of self-regulated learning should lead to a greater understanding of the learning environments that promote the development of these necessary skills and the role that gender plays in this development. Selfregulated learning (SRL) is a process in which the learner is an active participant in his or her own learning process (Pintrich, 2004). Self-regulated learners select their own goals, select and organize learning strategies, and monitor their own effectiveness. According to Boekarts, Pintrich and Zeidner (2000), there are four assumptions of self-regulated learning models. The first assumption is that learners are active participants in constructing meaning from information available in the environment in combination with what they already know. SRL models assume that students use prior knowledge as well as external resources to formulate their own learning strategies and goals. The second assumption of SRL models is that learners SELF-REGULATED LEARNING, GENDER DIFFERENCES, ENGINEERING EDUCATION 5 can control and regulate aspects of their thinking, motivation, behavior and in some instances their environment. While this regulation of thinking, motivation, and behavior is not always possible due to situational constraints, SRL models argue that there is often the potential for students to monitor, control and regulate these aspects. The third assumption of SRL models is the goal, criterion or standard assumption (Pintrich, 2004). This assumption presumes that learners compare their progress toward a goal against some criterion and this comparison informs the learners of the status of their progress. This comparison allows learners to monitor whether the learning process should continue as is or whether the learning process needs to be adjusted or changed. Finally, SRL models assume that self-regulatory activities are mediators between personality and cultural characteristics and performance or eventual achievement