ABSTRACT
This paper aims to provide some insight into the experiences and challenges faced by a cohort of homogeneously male final year students in a third level computing degree programme. It looks at their perceptions of how this homogeneity impacts them. Despite a large volume of research into the gender imbalance in STEM, studies of the male perspective have largely been absent from the literature.
The study originally intended to examine their perceptions on how the gender imbalance impacted their education. However, the resulting research gave voice to a number of concerns. This work focuses on the concerns surrounding the industry they are entering, as well as potential outcomes of the imbalanced learning environment. This work in particular seeks to look at how the normative masculinity experienced by the students in third level that could be seen to disadvantage or hurt women also constrains the men experiencing them.
- Andrea M Atkin, Ruth Green, and Laura McLaughlin. 2002. Patching the leaky pipeline. Journal of College Science Teaching 32, 2 (2002), 102.Google Scholar
- Donald A Barr, Maria Elena Gonzalez, and Stanley F Wanat. 2008. The leaky pipeline: Factors associated with early decline in interest in premedical studies among underrepresented minority undergraduate students. Academic Medicine 83, 5 (2008), 503--511.Google ScholarCross Ref
- David N Beede, Tiffany A Julian, David Langdon, George McKittrick, Beethika Khan, and Mark E Doms. 2011. Women in STEM: A gender gap to innovation. (2011).Google Scholar
- Ernest L Boyer and Carnegie Foundation for the Advancement of Teaching. 1990. Campus life: In search of community. (1990).Google Scholar
- Virginia Braun and Victoria Clarke. 2006. Using thematic analysis in psychology. Qualitative research in psychology 3, 2 (2006), 77--101.Google Scholar
- Marian Carr. 2010. Is Gender Stereotyping Having an Adverse Effect on Career Choices in the Video/Computer Games Industry. UK: University of Huddersfield (2010).Google Scholar
- Arthur W Chickering and Linda Reisser. 1993. Education and Identity. The Jossey-Bass Higher and Adult Education Series. ERIC.Google Scholar
- Jacob Clark Blickenstaff. 2005. Women and science careers: leaky pipeline or gender filter? Gender and education 17, 4 (2005), 369--386.Google Scholar
- Victoria Clarke and Virginia Braun. 2013. Teaching thematic analysis: Overcoming challenges and developing strategies for effective learning. The psychologist 26, 2 (2013), 120--123.Google Scholar
- Sue Clegg and Deborah Trayhurn. 2000. Gender and computing: Not the same old problem. British educational research journal 26, 1 (2000), 75--89.Google Scholar
- Robert W Connell and James W Messerschmidt. 2005. Hegemonic masculinity: Rethinking the concept. Gender & society 19, 6 (2005), 829--859.Google Scholar
- Wendy L. Cukier. 2003. Constructing the IT skills shortage in Canada: the implications of institutional discourse and practices for the participation of women. In CPR. Google ScholarDigital Library
- Marjorie L DeVault. 1999. Liberating method: Feminism and social research. Temple University Press.Google Scholar
- Alan Durndell and Karen Thomson. 1997. Gender and computing: a decade of change? Computers & Education 28, 1 (1997), 1--9. Google ScholarDigital Library
- Robert Elliott and Ladislav Timulak. 2005. Descriptive and interpretive approaches to qualitative research. A handbook of research methods for clinical and health psychology 1, 7 (2005), 147--159.Google Scholar
- D Gammal and C Simard. 2013. Women technologists count: Recommendations and best practices to retain women in computing. (2013).Google Scholar
- Judith Kegan Gardiner. 2002. Masculinity studies and feminist theory. Columbia University Press.Google Scholar
- Flis Henwood. 2000. From the woman question in technology to the technology question in feminism: Rethinking gender equality in IT education. European Journal of Women's Studies 7, 2 (2000), 209--227.Google ScholarCross Ref
- Catherine Hill, Christianne Corbett, and Andresse St Rose. 2010. Why so few? Women in science, technology, engineering, and mathematics. ERIC.Google Scholar
- Karen Holtzblatt, Aruna Balakrishnan, Troy Effner, Emily Rhodes, and Tina Tuan. 2016. Beyond The Pipeline: Addressing Diversity In High Tech. In Proceedings of the 2016 CHI Conference Extended Abstracts on Human Factors in Computing Systems. ACM, 1063--1068. Google ScholarDigital Library
- Mirra Komarovsky. 2004. Dilemmas of masculinity: A study of college youth. Vol. 7. Rowman Altamira.Google Scholar
- Christine A Mallozzi and Sally Campbell Galman. 2014. Guys and 'the rest of us': tales of gendered aptitude and experience in educational carework. Gender and Education 26, 3 (2014), 262--279.Google ScholarCross Ref
- Jane Margolis and Allan Fisher. 2003. Unlocking the clubhouse: Women in computing. MIT press.Google Scholar
- Judith Newton. 2002. MASCULINITY STUDIES: THE LONGED FOR PROFEMINIST MOVEMENT FOR ACADEMIC MEN? Masculinity Studies and Feminist Theory (2002), 176.Google Scholar
- Nelly Oudshoorn, Els Rommes, and Marcelle Stienstra. 2004. Configuring the user as everybody: Gender and design cultures in information and communication technologies. Science, Technology, & Human Values 29, 1 (2004), 30--63.Google ScholarCross Ref
- Michael Parsons and Emily R Ward. 2001. The roaring silence: Feminist revisions in the educational policy literature. Review of Policy Research 18, 2 (2001), 46--64.Google ScholarCross Ref
- Ernest T Pascarella and Patrick T Terenzini. 1991. How college affects students. Vol. 1991. Jossey-Bass San Francisco.Google Scholar
- Mark Pulsford. 2014. Constructing men who teach: research into care and gender as productive of the male primary teacher. Gender and Education 26, 3 (2014), 215--231.Google ScholarCross Ref
- Deirdre Raftery and Maryann Valiulis. 2008. Gender balance/Gender bias: issues in education research. (2008).Google Scholar
- Emma Renold. 2001. Learning the'hard'way: Boys, hegemonic masculinity and the negotiation of learner identities in the primary school. British journal of Sociology of Education 22, 3 (2001), 369--385.Google ScholarCross Ref
- Wendy L Richman, Sara Kiesler, Suzanne Weisband, and Fritz Drasgow. 1999. A meta-analytic study of social desirability distortion in computer-administered questionnaires, traditional questionnaires, and interviews. Journal of Applied Psychology 84, 5 (1999), 754.Google ScholarCross Ref
- Cecilia Ridgeway. 1991. The social construction of status value: Gender and other nominal characteristics. Social Forces 70, 2 (1991), 367--386.Google ScholarCross Ref
- Sally Robinson. 2002. Pedagogy of the opaque: Teaching masculinity studies. Masculinity Studies and Feminist Theory: New Directions (2002), 141--60.Google Scholar
- Robert M Schapiro. 1995. Liberatory pedagogy and the development paradox. Convergence 28, 2 (1995), 28.Google Scholar
- NeilSelwyn. 2007. Hi-tech= guy-tech? An exploration of undergraduate students? gendered perceptions of information and communication technologies. Sex Roles 56, 7-8 (2007), 525--536.Google Scholar
- Mary Thom. 2001. Balancing the Equation: Where Are Women and Girls in Science, Engineering and Technology?. ERIC.Google Scholar
- Roli Varma. 2010. Why so few women enroll in computing? Gender and ethnic differences in students' perception. Computer Science Education 20, 4 (2010), 301--316.Google ScholarCross Ref
- Marcus Weaver-Hightower. 2003. The ?boy turn? in research on gender and education. Review of educational research 73, 4 (2003), 471--498.Google Scholar
- Jonathan Woetzel et al. 2015. The power of parity: How advancing women's equality can add $12 trillion to global growth. Technical Report.Google Scholar
- Frehiwot W Wuhib and Sharon Dotger. 2014. Why so few women in STEM: The role of social coping. In Integrated STEM Education Conference (ISEC), 2014 IEEE. IEEE, 1--7.Google ScholarCross Ref
- Lyn Yates. 1999. The'facts of the case': gender equity for boys as a public policy issue. Sage.Google Scholar
Index Terms
- Observations of computing students on the homogeneity of their classrooms
Recommendations
Using Social Cognitive Career Theory to Understand Why Students Choose to Study Computer Science
ICER '18: Proceedings of the 2018 ACM Conference on International Computing Education ResearchThe aim of this research is to use Social Cognitive Career Theory (SCCT) to identify and understand reasons why students choose to study Computer Science (CS) at university. SCCT focuses on students' prior experience, social support, self-efficacy and ...
Gender Equity in Computing: International Faculty Perceptions and Current Practices
ITiCSE '16: Proceedings of the 2016 ITiCSE Working Group ReportsIn many countries serious effort has been put into developing and running programs that encourage girls to enjoy learning programming. At school level, many girls have done very well in these experiences, but despite their confidence and enthusiasm for ...
Computer science issues in high school: gender and more....
ITiCSE '09Computer Science (CS) seems to be one of the few remaining disciplines almost entirely dominated by men, especially among university faculty and in the hi-tech industry. This phenomenon is prevalent throughout the western world. In Israel, we observed ...
Comments