While degree enrollments continue to see an increase in female enrollment, there remains a distinct gender gap in STEM disciplines. In particular, the Technology and Computing space have always struggled to recruit and retain women. A similar trend is seen in employment, where approximately 25% of computing jobs are held by women. Within Brigham Young University's Information Technology program, we have struggled to achieve 10% female enrollment. This is unfortunate, as it is the universal opinion of our own faculty, supported by both internal and external research data that gender balance enables peak productivity. It is thus extremely unfortunate that elements of society are still struggling with mistaken gender stereotypes, and that this, coupled with occasional misogyny can dissuade young women from pursuing a career in computing. While this may not be the only cause, it is unacceptable. We have found (in line with other research) that strong faculty mentorship is an important factor in recruiting and retaining women in technology computing disciplines. This paper thus describes the approaches implemented by a cybersecurity research group of over 20 students in achieving a 2:3 female to male participation ratio within a program of less than 10% female enrollment. There have been significant immediate and long-term benefits to establishing this ratio in a research group. These include a measurable increase in research productivity from both genders, peer-to-peer mentoring, and a more complete perspective into the significance and impact of research overall. In the past four years, female students have participated in both pedagogical and technical research conferences, obtained research funding and developed entire courses. One particular effect of significance has been an increase in direct, targeted recruitment of women into the program - and subsequently from the program by employers. We anecdotally note also that women in cybersecurity command a higher average placement wage than men, although regret that to date, this data is not statistically significant due to insufficient data samples.
展开▼
