Acker, J. (1990). Hierarchies, jobs, bodies: A theory of gendered organizations. Gender & Society, 4(2), 139–158.
Appianing, J., & Van Eck, R. N. (2015). Gender differences in college students’ perceptions of technology-related jobs in computer science. International Journal of Gender, Science and Technology, 7(1), 2015.
Aylor, B. (2003). The impact of sex, gender, and cognitive complexity on the perceived importance of teacher communication skills. Communication Studies, 54(4), 496–509. https://doi.org/10.1080/10510970309363306
Ayre, M., Mills, J., & Gill, J. (2013). “Yes, I do belong”: The women who stay in engineering. Engineering Studies. https://doi.org/10.1080/19378629.2013.855781
Bakan, D. (1966). The duality of human existence: An essay on psychology and religion. Chicago: Rand McNally.
Barker, L. J., & Aspray, W. (2006). The state of research on girls and IT. In J. M. Cohoon, & W. Aspray (Eds.), Women and information technology: Research on underrepresentation (pp. 3–54). Cambridge: The MIT Press.
Barker, L. J., & Garvin-Doxas, K. (2004). Making visible the behaviors that influence learning environment: A qualitative exploration of computer science classrooms. Computer Science Education, 14(2), 119–145.
Barker, L. J., McDowell, C., & Kalahar, K. (2009). Exploring factors that influence computer science introductory course students to persist in the major. ACM SIGCSE Bulletin, 41, 282–286. Cambridge, MA: MIT Press.
Barker, L. J., O’Neill, M., & Kazim, N. (2014). Framing classroom climate for student learning and retention in computer science. In Proceedings of the 45th ACM technical symposium on Computer science education (pp. 319–324).
Bench, S. W., Lench, H. C., Liew, J., Miner, K., & Flores, S. A. (2015). Gender gaps in overestimation of math performance. Sex Roles, 72(11–12), 536–546. https://doi.org/10.1007/s11199-015-0486-9
Beyer, S. (1999). Gender differences in the accuracy of grade expectancies and evaluations. Sex Roles, 41(3/4), 279–296. https://doi.org/10.1023/A:1018810430105
Beyer, S. (2008). Predictors of female and male computer science students’ grades. Journal of Women and Minorities in Science and Engineering, 14(4), 377–409. https://doi.org/10.1615/JWomenMinorScienEng.v14.i4.30
Beyer, S. (2014). Why are women underrepresented in computer science? Gender differences in stereotypes, self-efficacy, values, and interests and predictors of future CS course-taking and grades. Computer Science Education, 24(2–3), 153–192. https://doi.org/10.1080/08993408.2014.963363
Blackburn, H. (2017). The status of women in STEM in higher education: A review of the literature 2007–2017. Science & Technology Libraries, 36(3), 235–273. https://doi.org/10.1080/0194262X.2017.1371658
Blum, L., & Frieze, C. (2005). The evolving culture of computing: Similarity is the difference. Frontiers: A Journal of Women Studies, 26(1) 110–125.
Bowman, N. A., Jarratt, L., Culver, K. C., & Segre, A. M. (2020). Pair programming in perspective: Effects on persistence, achievement, and equity in computer science. Journal of Research on Educational Effectiveness, 13(4), 731–758.
Braun, V., & Clarke, V. (2006). Using thematic analysis in psychology. Qualitative Research in Psychology. https://doi.org/10.1191/1478088706qp063oa
Brooks, J., McCluskey, S., Turley, E., & King, N. (2015). The Utility of Template Analysis in Qualitative Psychology Research. Qualitative Research in Psychology. https://doi.org/10.1080/14780887.2014.955224
Brotman, J. S., & Moore, F. M. (2008). Girls and science: A review of four themes in the science education literature. Journal of Research in Science Teaching, 45(9), 971–1002. https://doi.org/10.1002/tea.20241
Buse, K., Bilimoria, D., & Perelli, S. (2013). Why they stay: Women persisting in US engineering careers. Career Development International. https://doi.org/10.1108/CDI-11-2012-0108
Carlone, H. B., & Johnson, A. (2007). Understanding the science experiences of successful women of color: Science identity as an analytic lens. Journal of Research in Science Teaching, 44(8), 1187–1218. https://doi.org/10.1002/tea.20237
Cech, E., Rubineau, B., Silbey, S., & Seron, C. (2011). Professional role confidence and gendered persistence in engineering. American Sociological Review, 76(5), 641–666. https://doi.org/10.1177/0003122411420815
Ceci, S. J., Williams, W. M., & Barnett, S. M. (2009). Women’s underrepresentation in science: Sociocultural and biological considerations. Psychological Bulletin, 135(2), 218–261. https://doi.org/10.1037/a0014412
Charles, M., & Bradley, K. (2009). Indulging our gendered selves? Sex segregation by field of study in 44 countries. American Journal of Sociology, 114(4), 924–976. https://doi.org/10.1086/595942
Cheryan, S., Plaut, V. C., Davies, P. G., & Steele, C. M. (2009). Ambient belonging: How stereotypical cues impact gender participation in computer science. Journal of Personality and Social Psychology, 97(6), 1045–1060. https://doi.org/10.1037/a0016239
Cheryan, S., Plaut, V. C., Handron, C., & Hudson, L. (2013). The stereotypical computer scientist: Gendered media representations as a barrier to inclusion for women. Sex Roles, 69(1–2), 58–71. https://doi.org/10.1007/s11199-013-0296-x
Cheryan, S., Ziegler, S. A., Montoya, A. K., & Jiang, L. (2017). Why are some STEM fields more gender balanced than others? Psychological Bulletin, 143(1), 1–35. https://doi.org/10.1037/bul0000052
Correll, S. J. (2001). Gender and the career choice process: The role of biased self-assessments. American Journal of Sociology, 106(6), 1691–1730. https://doi.org/10.1086/321299
Crotty, M. (1998). The foundations of social research: Meaning and perspective in the research process. Sage.
Cundiff, J. L., Vescio, T. K., Loken, E., & Lo, L. (2013). Do gender-science stereotypes predict science identification and science career aspirations among undergraduate science majors? Social Psychology of Education, 16(4), 541–554. https://doi.org/10.1007/s11218-013-9232-8
Dempsey, J., Snodgrass, R. T., Kishi, I., & Titcomb, A. (2015). The emerging role of selfperception in student intentions. In Proceedings of the 46th ACM technical symposium on computer science education (pp. 108–113). New York: ACM.
Dickhäuser, O., & Meyer, W.-U. (2006). Gender differences in young children’s math ability attributions. Psychology Science, 48(1), 3–16.
Diekman, A. B., Brown, E. R., Johnston, A. M., & Clark, E. K. (2010). Seeking congruity between goals and roles: A new look at why women opt out of science, technology, engineering, and mathematics careers. Psychological Science, 21(8), 1051–1057. https://doi.org/10.1177/0956797610377342
Dingel, M. J. (2006). Gendered experiences in the science classroom. In J. M. Bystydzienski, & S. R. Bird (Eds.), Removing barriers: Women in academic science, technology, engineering, and mathematics (pp. 161–178). Bloomington, IN: Indiana University Press.
Donnelly, K., Twenge, J. M., Clark, M. A., Shaikh, S. K., Beiler-May, A., & Carter, N. T. (2016). Attitudes toward women’s work and family roles in the United States, 1976–2013. Psychology of Women Quarterly, 40(1), 41–54. https://doi.org/10.1177/0361684315590774
Drury, B. J., Siy, J. O., & Cheryan, S. (2011). When do female role models benefit women? The importance of differentiating recruitment from retention in STEM. Psychological Inquiry, 22(4), 265–269. https://doi.org/10.2307/23208703
DuBow, W. M., & Ashcraft, C. (2016). Male allies: Motivations and barriers for participating in diversity initiatives in the technology workplace. International Journal of Gender, Science and Technology, 8(2), 160–180.
Eagly, A. H., Wood, W., & Diekman, A. B. (2000). Social role theory of sex differences and similarities: A current appraisal. In T. Eckes, & H. M. Trautner (Eds.), The developmental social psychology of gender (pp. 123–174). Mahwah, NJ: Erlbaum.
Else-Quest, N. M., Hyde, J. S., & Linn, M. C. (2010). Cross-national patterns of gender differences in mathematics: A meta-analysis. Psychological Bulletin, 136(1), 103–127. https://doi.org/10.1037/a0018053
Fouad, N., Fitzpatrick, M., & Liu, J. P. (2011). Persistence of women in engineering careers: A qualitative study of current and former female engineers. Journal of Women and Minorities in Science and Engineering. https://doi.org/10.1615/JWomenMinorScienEng.v17.i1.60
Fouad, N. A., Singh, R., Cappaert, K., Chang, W., & hsin, & Wan, M. . (2016). Comparison of women engineers who persist in or depart from engineering. Journal of Vocational Behavior. https://doi.org/10.1016/j.jvb.2015.11.002
Frieze, C., & Blum, L. (2002). Building an effective computer science student organization: The Carnegie Mellon women@ SCS action plan. ACM SIGCSE Bulletin, 34(2), 74–78.
Frieze, C., & Quesenberry, J. L. (2019). How computer science at CMU is attracting and retaining women. Communications of the ACM, 62(2), 23–26.
Frieze, C., Quesenberry, J. L., Kemp, E., & Velázquez, A. (2012). Diversity or difference? New research supports the case for a cultural perspective on women in computing. Journal of Science Education and Technology, 21(4), 423–439.
Frymier, A. B., & Houser, M. L. (2000). The teacher-student relationship as an interpersonal relationship. Communication Education, 49(3), 207–219. https://doi.org/10.1080/03634520009379209
Garvin-Doxas, K., & Barker, L. J. (2004). Communication in computer science classrooms: Understanding defensive climates as a means of creating supportive behaviors. Journal on Educational Resources in Computing (JERIC), 4(1), 2-es.
Gelernter, D. (1999). Women and science at Yale. The Weekly Standard. Retrieved from http://www.weeklystandard.com/women-andscience-at-yale/article/11423.
Georgiou, S. N., Stavrinides, P., & Kalavana, T. (2007). Is Victor better than Victoria at maths? Educational Psychology in Practice, 23(4), 329–342. https://doi.org/10.1080/02667360701660951
Giannakos, M. N., Pappas, I. O., Jaccheri, L., & Sampson, D. G. (2017). Understanding student retention in computer science education: The role of environment, gains, barriers and usefulness. Education and Information Technologies, 22(5), 2365–2382. https://doi.org/10.1007/s10639-016-9538-1
Gürer, D., & Camp, T. (2002). An ACM-W literature review on women in computing. ACM SIGCSE Bulletin, 34(2), 121. https://doi.org/10.1145/543812.543844
Hafner, K. (2012). Giving women the access code. The New York Times. Retrieved from http://www.nytimes.com/2012/04/03/science/giving-women-the-access-code.html?pagewantedall&_r0.
Hartmann, T., & Klimmt, C. (2006). Gender and Ccomputer games: Exploring females’ dislikes. Journal of Computer-Mediated Communication, 11(4), 910–931. https://doi.org/10.1111/j.1083-6101.2006.00301.x
He, J., & Freeman, L. A. (2010). Understanding the formation of general computer self-efficacy. Communications of the Association for Information Systems, 26(1), 225–244. https://doi.org/10.17705/1CAIS.02612
Higher Education Statistics Agency. (2018). Higher Education Student Statistics: UK, 2016/17 - Summary. Cheltenham: HESA. Retreived: https://www.hesa.ac.uk/news/11-01-2018/sfr247-higher-education-studentstatistics.
Hirshfield, L. E. (2015). I just did everything physically possible to get in there. Social Currents, 2(4), 324–340. https://doi.org/10.1177/2329496515603727
Hirshfield, L. E. (2010). “She won’t make me feel dumb”: Identity threat in a male-dominated discipline. International Journal Of Gender, Science and Technology, 2(1), 5–24.
HMC. (2021) Harvey Mudd College website. Retreived: https://www.hmc.edu/.
Husserl, E. (1970). The crisis of European sciences and transcendental phenomenology. Evanston IL: Northwestern University Press.
John, W. S., & Johnson, P. (2000). The pros and cons of data analysis software for qualitative research. Journal of Nursing Scholarship, 32(4), 393–397.
Joint Council for Qualifications. (2018). GCSEs 2018. London: JCQ. Retreieved: https://www.jcq.org.uk/wpcontent/uploads/2018/12/GCSE-full-course-results-summer-2018.pdf.
Joshi, A., Neely, B., Emrich, C., Griffiths, D., & George, G. (2015). Gender research in AMJ: An overview of five decades of empirical research and calls to action. In Academy of Management Journal (Vol. 58, Issue 5, pp. 1459–1475). https://doi.org/10.5465/amj.2015.4011
King, N. (2004). Using templates in the thematic analysis of text. In C.Cassell, & G.Symon (Eds.), Essential guide to qualitative methods in organizational research. London: Sage.
Kumar, A. N. (2012). A study of stereotype threat in computer science. In Proceedings of the 17th ACM annual conference on Innovation and technology in computer science education (pp. 273–278).
Lehman, K. J., Sax, L. J., & Zimmerman, H. B. (2016). Women planning to major in computer science: Who are they and what makes them unique? Computer Science Education, 26(4), 277–298. https://doi.org/10.1080/08993408.2016.1271536
Lenhart, A., Smith, A., Anderson, M., Duggan, M., & Perrin, A. (2015). Teens, technology and friendships. Washington D.C.: Pew Research Center.
Leslie, L. M., Mayer, D. M., & Kravitz, D. A. (2013). The Stigma of Affirmative Action: A Stereotyping-Based Theory and Meta-Analytic Test of the Consequences for Performance. Academy of Management Journal, 57(4), 964–989. https://doi.org/10.5465/amj.2011.0940
Lincoln, Y. S., & Guba, E. G. (1990). Judging the quality of case study reports. International Journal of Qualitative Studies in Education, 3(1), 53–59. https://doi.org/10.1080/0951839900030105
Madsen, S. R., Townsend, A., & Scribner, R. T. (2019). Strategies that male allies use to advance women in the workplace. Journal of Men’s Studies, 106082651988323.https://doi.org/10.1177/1060826519883239
Margolis, J., & Fisher, A. (2002). Unlocking the clubhouse: Women in computing. Boston: MIT press.
Margolis, J., Fisher, A., & Miller, F. (2000). The anatomy of interest: Women in undergraduate computer science. Women’s Studies Quarterly, 28(1/2), 104–127.
Master, A., Cheryan, S., & Meltzoff, A. N. (2016). Computing whether she belongs: Stereotypes undermine girls’ interest and sense of belonging in computer science. Journal of Educational Psychology, 108(3), 424–437. https://doi.org/10.1037/edu0000061
Master, A., Cheryan, S., Moscatelli, A., & Meltzoff, A. N. (2017). Programming experience promotes higher STEM motivation among first-grade girls. Journal of Experimental Child Psychology, 160, 92–106. https://doi.org/10.1016/J.JECP.2017.03.013
McCartney, R., Boustedt, J., Eckerdal, A., Sanders, K., Thomas, L., & Zander, C. (2016). Why computing students learn on their own: Motivation for self-directed learning of computing. ACM Transactions on Computing Education, 16(1), 1–18. https://doi.org/10.1145/2747008
McLachlan, S., & Hagger, M. S. (2010). Effects of an autonomy-supportive intervention on tutor behaviors in a higher education context. Teaching and Teacher Education, 26(5), 1204–1210. https://doi.org/10.1016/j.tate.2010.01.006
Menekse, M., Zheng, X., & Anwar, S. (2020). Computer science students’ perceived needs for support and their academic performance by gender and residency: An exploratory study. Journal of Applied Research in Higher Education. https://doi.org/10.1108/JARHE-07-2019-0194
Merriam, S. B., & Grenier, R. S. (2019). Introduction to qualitative research. In S. B. Merriam, & R. S. Grenier (Eds.), Qualitative research in practice: Examples for discussion and analysis (2nd ed., pp. 3–18). San Francisco: Josey Bass.
Meyers-Levy, J., & Loken, B. (2015). Revisiting gender differences: What we know and what lies ahead. Journal of Consumer Psychology, 25(1), 129–149. https://doi.org/10.1016/J.JCPS.2014.06.003
Miller, D. T., Effron, D. A., & Zak, S. V. (2009). From moral outrage to social protest: The role of psychological standing. In D. R. Bobocel, A. C. Kay, M. P. Zanna, & J. M. Olson (Eds.), The Psychology of justice and legitimacy: The Ontario symposium (Vol. 11, pp. 103–123). New York: Psychological Press.
Miller, C. C. (2015). Women in tech: Making computer science more inviting: A look at what works. The New York Times. Retrieved from http://www.nytimes.com/2015/05/22/upshot/making-computerscience-moreinviting-a-look-at-what-works.html?abt0002&abg0.
Mullan, K. (2018). Technology and children’s screen-based activities in the UK: The story of the millennium so far. Child Indicators Research, 11(6), 1781–1800.
Office for National Statistics. (2019). Employment and employment types. London: ONS. https://www.ons.gov.uk/employmentandlabourmarket/peopleinwork/employmentandemployeetypes.
Ohannessian, C. M. (2015). A longitudinal examination of the relationship between technology use and substance use during adolescence. In S. L. Blair, P. N. Claster, & S. M. Claster (Eds.), Technology and Youth: Growing Up in a Digital World (Vol. 19, pp. 293–313). Emerald Group Publishing Limited. https://doi.org/10.1108/S1537-466120150000019010
Östberg, V. (2003). Children in classrooms: Peer status, status distribution and mental well-being. Social Science & Medicine, 56(1), 17–29.
Park, L. E., Young, A. F., Troisi, J. D., & Pinkus, R. T. (2011). Effects of everyday romantic goal pursuit on women’s attitudes toward math and science. Personality and Social Psychology Bulletin, 37(9), 1259–1273. https://doi.org/10.1177/0146167211408436
Peters, K., Ryan, M., Haslam, S. A., & Fernandes, H. (2012). To belong or not to belong: Evidence that women’s occupational disidentification is promoted by lack of fit with masculine occupational prototypes. Journal of Personnel Psychology, 11(3), 148–158. https://doi.org/10.1027/1866-5888/a000067
Price, J. (2010). The effect of instructor race and gender on student persistence in STEM fields. Economics of Education Review, 29(6), 901–910. https://doi.org/10.1016/J.ECONEDUREV.2010.07.009
Ramsey, L. R., Betz, D. E., & Sekaquaptewa, D. (2013). The effects of an academic environment intervention on science identification among women in STEM. Social Psychology of Education, 16(3), 377–397. https://doi.org/10.1007/s11218-013-9218-6
Reeve, J., & Jang, H. (2006). What teachers say and do to support students’ autonomy during a learning activity. Journal of Educational Psychology, 98, 209–218.
Reeve, J. (2016). Autonomy-supportive teaching: What it is, how to do it. In W. C. Liu, J. C. K. Wang, & R. M. Ryan (Eds.), Building autonomous learners (pp. 129–152). New York: Springer. https://doi.org/10.1007/978-981-287-630-0_7
Reynolds, R., & Leeder, C. (2017). Information uses and learning outcomes during guided discovery in a blended e-learning game design program for secondary computer science education. Hawaii International Conference on System Sciences 2017 2076–2085.
Riegle-Crumb, C., Peng, M., & Buontempo, J. (2019). Gender, competitiveness, and intentions to pursue STEM fields. International Journal of Gender, Science and Technology, 11(2), 234–257.
Rosson, M. B., Carroll, J. M., & Sinha, H. (2011). Orientation of undergraduates toward careers in the computer and information sciences. ACM Transactions on Computing Education, 11(3), 1–23. https://doi.org/10.1145/2037276.2037278
Ryan, R. M., & Deci, E. L. (2000). Self-determination theory and the facilitation of intrinsic motivation, social development, and well-being. American Psychologist, 55, 68–78.
Sáinz, M., & Eccles, J. (2012). Self-concept of computer and math ability: Gender implications across time and within ICT studies. Journal of Vocational Behavior, 80(2), 486–499. https://doi.org/10.1016/J.JVB.2011.08.005
Sallee, M. W. (2011). Performing masculinity: Considering gender in doctoral student socialization. Journal of Higher Education, 82(2), 187–216. https://doi.org/10.1080/00221546.2011.11779091
Saunders, M. N. K., & Townsend, K. (2016). Reporting and justifying the number of interview participants in organization and workplace research. British Journal of Management, 27(4), 836–852. https://doi.org/10.1111/1467-8551.12182
Schepens, A., Aelterman, A., & Vlerick, P. (2009). Student teachers’ professional identity formation: Between being born as a teacher and becoming one. Educational Studies, 35(4), 361–378. https://doi.org/10.1080/03055690802648317
Sen, A. (1992). Inequality reexamined. Clarendon Press.
Sevin, R., & DeCamp, W. (2016). From playing to programming: The effect of video game play on confidence with computers and an interest in computer science. Sociological Research Online, 21(3), 14–23.
Sherf, E. N., Tangirala, S., & Weber, K. C. (2017). It is not my place! Psychological standing and men’s voice and participation in gender-parity initiatives. Organization Science, 28(2), 193–210. https://doi.org/10.1287/orsc.2017.1118
Shrewsbury, C. M. (1993). What is feminist pedagogy? Women’s Studies Quarterly, 21(3/4), 8–16.
Sinclair, J., & Kalvala, S. (2015). Exploring societal factors affecting the experience and engagement of first year female computer science undergraduates. Proceedings of the 15th Koli Calling Conference on Computing Education Research - Koli Calling ’15, 107–116. https://doi.org/10.1145/2828959.2828979
Sinclair, J., Butler, M., Morgan, M., & Kalvala, S. (2015). Measures of student engagement in computer science. Proceedings of the 2015 ACM Conference on Innovation and Technology in Computer Science Education - ITiCSE ’15, 242–247. https://doi.org/10.1145/2729094.2742586
STEM Women. (2021). Percentage of women in STEM. Retrieved: https://www.stemwomen.co.uk/blog/2021/01/women-in-stem-percentages-of-women-in-stem-statistics.
Tamres, L. K., Janicki, D., & Helgeson, V. S. (2002). Sex differences in coping behavior: A meta-analytic review and an examination of relative coping. Personality and Social Psychology Review, 6(1), 2–30. https://doi.org/10.1207/S15327957PSPR0601_1
Tellhed, U., Bäckström, M., & Björklund, F. (2018). The role of ability beliefs and agentic vs. communal career goals in adolescents’ first educational choice. What explains the degree of gender-balance? Journal of Vocational Behavior, 104, 1–13. https://doi.org/10.1016/J.JVB.2017.09.008
Thomas, L. (2013). Self-directed learning in computing and the path to employment. York: The Higher Education Academy, STEM Series.
Vekiri, I. (2013). Users and experts: Greek primary teachers’ views about boys, girls, ICTs and computing. Technology, Pedagogy and Education, 22(1), 73–87. https://doi.org/10.1080/1475939X.2012.753779
Weiler, K. (1991). Freire and a feminist pedagogy of difference. Harvard Educational Review, 61(4), 449–475.
Werner, L., McDowell, C., & Denner, J. (2013). A first step in learning analytics: Pre-processing low-level Alice logging data of middle school students. Journal of Educational Data Mining, 5(2), 11–37.
WISE. (2017). Statistics.
Woodfield, R. (2012). Gender and employability patterns amongst UK ICT graduates: Investigating the leaky pipeline. In R. Pande & T. van der Weide (Eds.), Globalization, Technology Diffusion and Gender Disparity: Social Impacts of ICTs (pp. 184–199). IGI Global. https://doi.org/10.4018/978-1-4666-0020-1.ch016
Yates, J., & Skinner, S. (2021). How do female engineers conceptualise career advancement in engineering: a template analysis. Career Development International, ahead-of-print(ahead-of-print). https://doi.org/10.1108/CDI-01-2021-0016
Ying, K. M., Crompton, K., Pezzullo, L. G., Blanchard, J., Ahmed, M., & Boyer, K. E. (2019). In their own words: Gender differences in student perceptions of pair programming. SIGCSE 2019 - Proceedings of the 50th ACM Technical Symposium on Computer Science Education, 1053–1059. https://doi.org/10.1145/3287324.3287380
Ying, K. M., Rodríguez, F. J., Dibble, A. L., & Boyer, K. E. (2021). Understanding women’s remote collaborative programming experiences: The relationship between dialogue features and reported perceptions. Proceedings of the ACM on Human-Computer Interaction, 4(CSCW3), 1–29.
Zander, C., Boustedt, J., Eckerdal, A., McCartney, R., Sanders, K., Moström, J. E., & Thomas, L. (2012). Self-directed learning: Stories from industry. Proceedings of the 12th Koli Calling International Conference on Computing Education Research - Koli Calling ’12, 111–117. https://doi.org/10.1145/2401796.2401810