Gender and IT Education Conference, Indiana University, 2007 Gender & IT Education Being The Same Isn’t Enough Impact of Male and Female Mentors on Computer Self-Efficacy of College Students in IT-Related Fields Principal Investigators: Debbie Goh Christine Ogan Manju Ahuja Susan C. Herring Jean C. Robinson

Gender and IT Education Conference, Indiana University, 2007 Purpose of Study Establish relationship between gender, mentoring & computer self- efficacy Why self-efficacy? Why mentoring?

Gender and IT Education Conference, Indiana University, 2007 Self-Efficacy “People’s beliefs or expectations about their ability to accomplish certain tasks or demonstrate certain behaviors successfully” (Bandura, 1977) Self-efficacy influences –Choice –Effort –Perseverance Influenced by –Success –Comparison with others –Feedback –Physiological & affective states

Gender and IT Education Conference, Indiana University, 2007 Computer Self-Efficacy Judgment of one’s capability to use a computer to perform computing tasks (Compeau & Higgins, 1995) –Tasks refer to “jobs” and not just a specific action. –Higher computer self-efficacy  more likely to believe you can do difficult computer tasks; have less anxiety.

Gender and IT Education Conference, Indiana University, 2007 Mentoring and C.S.E. Studies repeatedly show women report lower computer self-efficacy than men Women need positive experience with computers –Success, positive feedback, comparison with others similar to themselves Mentoring and role modeling by female faculty can offer this

Gender and IT Education Conference, Indiana University, 2007 Mentoring A “developmental relationship” between an experienced supervisor and a less experienced protégé. Mentoring functions: career and psychosocial (Kram, 1984) Career: sponsorship, exposure, coaching, assignment of challenging work Psychosocial: role modeling, counseling, friendship, enhance sense of competence and identity

Gender and IT Education Conference, Indiana University, 2007 Research Qn & Hypotheses RQ: What is the relationship between mentoring and computer self-efficacy? H1: Students with more mentoring will have higher C.S.E. H2: Male students with male mentors will have greater C.S.E. than male and female students with female mentors. H3: Female students with female mentors will have greater C.S.E. than male and female students with male mentors. H4: Male students with male mentors and female students with female mentors will have similar C.S.E.

Gender and IT Education Conference, Indiana University, 2007 Method Web-based survey of 5 universities –IUB, U. Buffalo, U. Illinois Urbana- Champagne, U. Michigan Ann Arbor & Dearborn, U. Washington –CS, IS, Informatics, IST, Library & Info Sciences –1,768 respondents –52% male, 34% female

Gender and IT Education Conference, Indiana University, 2007 Computer Self-Efficacy Measures 1.How appealing is the challenge of solving problems with computers to you? 2.How comfortable are you working with computers? 3.How would you rate your programming skills compared to other students in your major? 4.How comfortable do you feel trying new things on the computer? 5.When there is a problem with a computer program that you can’t immediately solve, how likely is it that you will stick with it until you have the answer? 6.How easily do you learn computer languages? 7.How would you rate the grades you generally get in computer programming classes? 8.How would you rate your self-confidence when it comes to working with computers?

Gender and IT Education Conference, Indiana University, 2007 Mentoring Measures 1.Recommended you for challenging assignments that present opportunities to learn new skills. 2.Recommended you for assignments that helped you meet other students in your department or school. 3.Recommended you for assignments that involved personal contact with professors in other department. 4.Helped you finish assignments/tasks or meet deadlines that otherwise would have been difficult to complete. 5.Gone out of his/her way to promote your career interest. 6.Informed you about what is going on at higher levels in the schools or how external conditions are influencing the school. 7.Conveyed feelings of respect for you as an individual. 8.Conveyed empathy for the concerns and feelings you have discussed with him/her. 9.Encourage you to talk openly about anxiety and fears that detract from your studies. 10.Shared personal experiences relevant to your problems. 11.Shared history of his/her career with you. 12.Encouraged you to think about graduate school. 13.Served as a role model. 14.Displayed attitudes and values about the field similar to your own. 15.Recommended you for fellowships, scholarships or internships.

Gender and IT Education Conference, Indiana University, 2007 Statistical Analyses Regression –Extent of mentoring (IV) –Sex (IV) –Age (IV) –Class standing (IV) –When student first used computers (IV) –Time spent on computers as teens (IV) –Perception of mentors’ race (IV) –Computer self-efficacy (DV) Three-way ANOVA on extent of mentoring, sex of students (M,F), sex of mentors (M, F, M&F, None)

Gender and IT Education Conference, Indiana University, 2007 Results Predictors of computer self-efficacy

Gender and IT Education Conference, Indiana University, 2007 Results ANOVA shows significant main effects from all three variables Sex of students had largest main effect, followed by sex of mentors, then extent of mentoring. Students who received less mentoring reported lower self- efficacy

Gender and IT Education Conference, Indiana University, 2007 Results Mean computer self-efficacy of students with different mentoring influence

Gender and IT Education Conference, Indiana University, 2007 Summary Predictors of computer self-efficacy: –Extent of mentoring –Gender of students –Time spent on computers as teens Students with faculty mentoring had higher computer self-efficacy. Women have lower computer self-efficacy than men. –Link to shrinking pipeline? Gender of mentors influences computer self-efficacy.

Gender and IT Education Conference, Indiana University, 2007 Are Women Poor Mentors? Presence is weak – only 108 out of 1,175 students had female mentors Stereotypes of women in science prejudice students against female faculty Female faculty are more likely to have lower ranks, fewer achievements, smaller reputations Overload of academic and non- academic responsibilities

Gender and IT Education Conference, Indiana University, 2007 Being the same isn’t enough Simply adding women in IT will not solve the problem Need to tackle existing biases and constraints that impedes effective mentoring by female faculty