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“CodePlus”—Measuring Short-Term Efficacy in a Non-Formal, All-Female CS Outreach Programme

Published:17 October 2020Publication History
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Abstract

The provision of all-female computer science outreach programmes is a common strategy used to foster greater interest in the subject for high school aged girls. Based on key factors that affect girls’ interest in computer science (CS), outreach programmes often share much in their approach. Nonetheless, there is criticism from a research perspective concerning how programmes evaluate their efficacy, and how the role of pedagogy is under-explored. This article describes the design of CodePlus, a non-formal CS outreach programme based in an Irish University, Trinity College Dublin, and the methods by which the programme is evaluated. This article aims to contribute to this area by reporting on a social constructivist pedagogical model for all-female CS outreach activities, evaluated with a structured research approach. The results from the large sample size (n=856) are positive, with participants showing statistically significant changes in key attitudinal and intentional variables concerning girls’ interest in studying computer science.

References

  1. Christine Alvarado, Zachary Dodds, and Ran Libeskind-Hadas. 2012. Increasing women’s participation in computing at Harvey Mudd College. ACM Inroads 3, 4 (2012), 55--64.Google ScholarGoogle ScholarDigital LibraryDigital Library
  2. Shaki Asgari, Nilanjana Dasgupta, and Jane G. Stout. 2012. When do counterstereotypic ingroup members inspire versus deflate? The effect of successful professional women on young women’s leadership self-concept. Personality Social Psychology Bulletin 38, 3 (2012), 370--383.Google ScholarGoogle ScholarCross RefCross Ref
  3. Alexander W. Astin and Helen S. Astin. 1992. Undergraduate Science Education: The Impact of Different College Environments on the Educational Pipeline in the Sciences. Final Report. California University.Google ScholarGoogle Scholar
  4. Albert Bandura. 1977. Self-efficacy: Toward a unifying theory of behavioral change. Psychological Review 84, 2 (1977), 191.Google ScholarGoogle ScholarCross RefCross Ref
  5. Lecia Jane Barker, Charlie McDowell, and Kimberly Kalahar. 2009. Exploring factors that influence computer science introductory course students to persist in the major. In ACM SIGCSE Bulletin, Vol. 41. ACM, 153--157.Google ScholarGoogle ScholarDigital LibraryDigital Library
  6. Tim Bell, Frances Rosamond, and Nancy Casey. 2012. Computer Science Unplugged and Related Projects in Math and Computer Science Popularization. Springer, 398--456.Google ScholarGoogle Scholar
  7. Tessa Berg, Alexander Sharpe, and Emma Aitkin. 2018. Females in computing: Understanding stereotypes through collaborative picturing. Computers and Education 126 (2018), 105--114.Google ScholarGoogle ScholarCross RefCross Ref
  8. Deborah L. Best, John E. Williams, Jonathan M. Cloud, Stephen W. Davis, Linda S. Robertson, John R. Edwards, Howard Giles, and Jacqueline Fowles. 1977. Development of sex-trait stereotypes among young children in the United States, England, and Ireland. Child Development (1977), 1375--1384.Google ScholarGoogle Scholar
  9. Sylvia Beyer. 1999. The accuracy of academic gender stereotypes. Springer Link 40, 9--10 (1999), 787--813.Google ScholarGoogle Scholar
  10. Sylvia Beyer. 2008. Gender differences and intra-gender differences amongst management information systems students. Journal of Information Systems Education 19, 3 (2008).Google ScholarGoogle Scholar
  11. Sylvia Beyer, Kristina Rynes, Michelle Chavez, Kelly Hay, and Julie Perrault. 2002. Why are so few women in computer science?. In American Psychological Association Annual Meeting. ERIC.Google ScholarGoogle Scholar
  12. Sylvia Beyer, Kristina Rynes, Julie Perrault, Kelly Hay, and Susan Haller. 2003. Gender differences in computer science students. ACM SIGCSE Bulletin 35, 1 (2003), 49--53.Google ScholarGoogle ScholarDigital LibraryDigital Library
  13. T. Brown. 2008. Design thinking. In Harvard Business Review, Vol. 86, 84.Google ScholarGoogle Scholar
  14. Leah Buechley, Mike Eisenberg, Jaime Catchen, and Ali Crockett. 2008. The LilyPad Arduino: Using computational textiles to investigate engagement, aesthetics, and diversity in computer science education. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems. ACM, 423--432.Google ScholarGoogle ScholarDigital LibraryDigital Library
  15. Jake Rowan Byrne, Katriona O’Sullivan, and Kevin Sullivan. 2017. An IoT and wearable technology hackathon for promoting careers in computer science. IEEE Transactions on Education 60, 1 (2017), 50--58.Google ScholarGoogle ScholarCross RefCross Ref
  16. Simon Cassidy and Peter Eachus. 2002. Developing the computer user self-efficacy (CUSE) scale: Investigating the relationship between computer self-efficacy, gender and experience with computers. Journal of Educational Computing Research 26, 2 (2002), 133--153.Google ScholarGoogle ScholarCross RefCross Ref
  17. Stephen J. Ceci and Wendy M. Williams. 2009. The Mathematics of Sex: How Biology and Society Conspire to Limit Talented Women and Girls. Oxford University Press.Google ScholarGoogle Scholar
  18. Sapna Cheryan, Benjamin J. Drury, and Marissa Vichayapai. 2013. Enduring influence of stereotypical computer science role models on women’s academic aspirations. Psychology of Women Quarterly 37, 1 (2013), 72--79.Google ScholarGoogle ScholarCross RefCross Ref
  19. Sapna Cheryan, Allison Master, and Andrew N. Meltzoff. 2015. Cultural stereotypes as gatekeepers: Increasing girls’ interest in computer science and engineering by diversifying stereotypes. Frontiers in Psychology 6 (2015), 49.Google ScholarGoogle ScholarCross RefCross Ref
  20. Sapna Cheryan, Victoria C. Plaut, Caitlin Handron, and Lauren Hudson. 2013. The stereotypical computer scientist: Gendered media representations as a barrier to inclusion for women. Sex Roles 69, 1–2 (2013), 58--71.Google ScholarGoogle ScholarCross RefCross Ref
  21. J. Cohen. 1988. Statistical Power Analysis for the Behaviors Science (2nd ed.). Laurence Erlbaum Associates, Hillsdale, New Jersey.Google ScholarGoogle Scholar
  22. Shelley J. Correll. 2004. Constraints into preferences: Gender, status, and emerging career aspirations. American Sociological Review 69, 1 (2004), 93--113.Google ScholarGoogle ScholarCross RefCross Ref
  23. Annemieke Craig, Vashti Galpin, Rosemary Paradis, Eva Turner, and Moderator, Ursula Martin. 2002. What is computing? The perceptions of university computing students. In Proceedings of the Grace Hopper Celebration of Women in Computing Conference (GHC’02).Google ScholarGoogle Scholar
  24. Jessica L. Cundiff, Theresa K. Vescio, Eric Loken, and Lawrence Lo. 2013. Do gender-science stereotypes predict science identification and science career aspirations among undergraduate science majors? Social Psychology of Education 16, 4 (2013), 541--554.Google ScholarGoogle ScholarCross RefCross Ref
  25. Adrienne Decker, Monica M. McGill, and Amber Settle. 2016. Towards a common framework for evaluating computing outreach activities. In Proceedings of the 47th ACM Technical Symposium on Computing Science Education. ACM, 627--632.Google ScholarGoogle ScholarDigital LibraryDigital Library
  26. Jill Denner, Linda Werner, Lisa O’Connor, and Jill Glassman. 2014. Community college men and women: A test of three widely held beliefs about who pursues computer science. Community College Review 42, 4 (2014), 342--362.Google ScholarGoogle ScholarCross RefCross Ref
  27. Oliver Dickhäuser and Joachim Stiensmeier-Pelster. 2003. Gender differences in the choice of computer courses: Applying an expectancy-value model. Social Psychology of Education 6, 3 (2003), 173--189.Google ScholarGoogle ScholarCross RefCross Ref
  28. P. Eachus and S. Cassidy. 1996. The development of the computer user self-efficacy scale. Available at http://www.york.ac.uk/inst/ctipsych/web/CiP96CD/EACHUS/XHTML/QUESTNNR.HTM [Google Scholar] 1 (1996), 2003.Google ScholarGoogle Scholar
  29. Jacquelynne S. Eccles, Bonnie Barber, and Debra Jozefowicz. 1999. Linking Gender to Educational, Occupational, and Recreational Choices: Applying the Eccles et al. Model of Achievement-related Choices. AmerIcan Psychological Association, Journal article linking gender to educational, occupational, and recreational choices: Applying the Eccles et al. model of achievement-related choices, 153--192.Google ScholarGoogle Scholar
  30. Allan Fisher, Jane Margolis, and Faye Miller. 1997. Undergraduate women in computer science: Experience, motivation and culture. In ACM SIGCSE Bulletin, Vol. 29. ACM, 106--110.Google ScholarGoogle ScholarDigital LibraryDigital Library
  31. Mark Graham. 2011. Time machines and virtual portals: The spatialities of the digital divide. Progress in Development Studies 11, 3 (2011), 211--227.Google ScholarGoogle ScholarCross RefCross Ref
  32. Sandy Graham and Celine Latulipe. 2003. CS girls rock: Sparking interest in computer science and debunking the stereotypes. In ACM SIGCSE Bulletin, Vol. 35. ACM, 322--326.Google ScholarGoogle ScholarDigital LibraryDigital Library
  33. Agueda Gras-Velazquez, Alexa Joyce, and Maïté Debry. 2009. Women and ICT: Why are Girls Still Not Attracted to ICT Studies and Careers. Technical Report. European Schoolnet EUN Partnership AISBL.Google ScholarGoogle Scholar
  34. Denise Gürer and Tracy Camp. 2001. Investigating the Incredible Shrinking Pipeline for Women in Computer Science. Technical Report. National Science Foundation.Google ScholarGoogle Scholar
  35. Nancy Hafkin and H. Hodame. 2002. Gender, ICTs and Agriculture. Technical Report. International Union for Conservation of Nature and Natural Resources (World Conservation Union).Google ScholarGoogle Scholar
  36. Brian Hanks, Sue Fitzgerald, René McCauley, Laurie Murphy, and Carol Zander. 2011. Pair programming in education: A literature review. Computer Science Education 21, 2 (2011), 135--173.Google ScholarGoogle ScholarCross RefCross Ref
  37. Catherine Hill, Christianne Corbett, and Andresse St. Rose. 2010. Why So Few? Women in Science, Technology, Engineering, and Mathematics. American Association of University Women.Google ScholarGoogle Scholar
  38. Jung Won Hur, Carey E. Andrzejewski, and Daniela Marghitu. 2017. Girls and computer science: Experiences, perceptions, and career aspirations. Computer Science Education 27, 2 (2017), 100--120.Google ScholarGoogle ScholarCross RefCross Ref
  39. Yasmin Kafai, Kylie Peppler, and Robbin Chapman. 2009. The Computer Clubhouse: A Place for Youth. eScholarship, University of California.Google ScholarGoogle Scholar
  40. Henry F. Kaiser. 1974. An index of factorial simplicity. Psychometrika 39, 1 (1974), 31--36.Google ScholarGoogle ScholarCross RefCross Ref
  41. Maria Kallia and Sue Sentance. 2018. Are boys more confident than girls?: The role of calibration and students’ self-efficacy in programming tasks and computer science. In Proceedings of the 13th Workshop in Primary and Secondary Computing Education. ACM, 16.Google ScholarGoogle ScholarDigital LibraryDigital Library
  42. Matthew A. Kraft. 2018. Interpreting effect sizes of education interventions. Brown University Working Paper.Google ScholarGoogle Scholar
  43. Catherine Lang, Julie Fisher, Annemieke Craig, and Helen Forgasz. 2015. Outreach programmes to attract girls into computing: How the best laid plans can sometimes fail. Computer Science Education 25, 3 (2015), 257--275.Google ScholarGoogle ScholarCross RefCross Ref
  44. Kittipong Laosethakul and Thaweephan Leingpibul. 2010. Why females do not choose computing? A lesson learned from China. Multicultural Education & Technology Journal (2010).Google ScholarGoogle Scholar
  45. Richard T. Lapan, Angela Adams, Sherri Turner, and Jeanne M. Hinkelman. 2000. Seventh graders’ vocational interest and efficacy expectation patterns. Journal of Career Development 26, 3 (2000), 215--229.Google ScholarGoogle ScholarCross RefCross Ref
  46. John Lawlor, Claire Conneely, Elizabeth Oldham, Kevin Marshall, and Brendan Tangney. 2018. Bridge21: Teamwork, technology and learning. A pragmatic model for effective twenty-first-century team-based learning. Education Technology, Pedagogy 27, 2 (2018), 211--232.Google ScholarGoogle ScholarCross RefCross Ref
  47. Richard Lippa. 1998. Gender-related individual differences and the structure of vocational interests: The importance of the people--things dimension. Journal of Personality Social Psychology 74, 4 (1998), 996.Google ScholarGoogle ScholarCross RefCross Ref
  48. Jane Margolis and Allan Fisher. 2003. Unlocking the Clubhouse: Women in Computing. MIT Press.Google ScholarGoogle Scholar
  49. Martina R. M. Meelissen and Marjolein Drent. 2008. Gender differences in computer attitudes: Does the school matter?Computers in Human Behavior 24, 3 (2008), 969--985.Google ScholarGoogle Scholar
  50. Heather Metcalf. 2010. Stuck in the pipeline: A critical review of STEM workforce literature. InterActions: UCLA Journal of Education and Information Studies 6, 2 (2010).Google ScholarGoogle ScholarCross RefCross Ref
  51. Marina Papastergiou. 2008. Are computer science and information technology still masculine fields? High school students’ perceptions and career choices. Computers and Education 51, 2 (2008), 594--608.Google ScholarGoogle ScholarDigital LibraryDigital Library
  52. Don Passey. 2017. Computer science (CS) in the compulsory education curriculum: Implications for future research. Education and Technologies, Information 22, 2 (2017), 421--443. DOI:https://doi.org/10.1007/s10639-016-9475-zGoogle ScholarGoogle ScholarDigital LibraryDigital Library
  53. Elizabeth Patitsas, Michelle Craig, and Steve Easterbrook. 2014. A historical examination of the social factors affecting female participation in computing. In Proceedings of the 2014 Conference on Innovation and Technology in Computer Science Education. ACM, 111--116.Google ScholarGoogle ScholarDigital LibraryDigital Library
  54. Inna Pivkina, Enrico Pontelli, Rachel Jensen, and Jessica Haebe. 2009. Young women in computing: Lessons learned from an educational and outreach program. SIGCSE Bulletin 41, 1 (2009), 509--513. DOI:https://doi.org/10.1145/1539024.1509042Google ScholarGoogle ScholarDigital LibraryDigital Library
  55. Ashley Robinson, Manuel A. Pérez-Quiñones, and Glenda Scales. 2016. African-American middle school girls: Influences on attitudes toward computer science. Computing in Science and Engineering 18, 3 (2016), 14--23.Google ScholarGoogle ScholarDigital LibraryDigital Library
  56. Alan Rogers. 2007. Non-formal Education: Flexible Schooling or Participatory Education? Vol. 15. Springer Science & Business Media.Google ScholarGoogle Scholar
  57. Els Rommes, Geertjan Overbeek, Ron Scholte, Rutger Engels, and Raymond De Kemp. 2007. ’I’m not interested in computers’: Gender-based occupational choices of adolescents. Information, Community Society 10, 3 (2007), 299--319.Google ScholarGoogle ScholarCross RefCross Ref
  58. Lynda Ross. 2010. Computer Science: Where (and Why) Have All the Women Gone? Technical Report. Athabasca University.Google ScholarGoogle Scholar
  59. Minna Salminen-Karlsson. 2009. Women who learn computing like men: Different gender positions on basic computer courses in adult education. Journal of Vocational Education and Training 61, 2 (2009), 151--168.Google ScholarGoogle ScholarCross RefCross Ref
  60. Reshma Saujani. 2016. Teach girls bravery, not perfection. TED Talks.Google ScholarGoogle Scholar
  61. Klaus Schwab. 2017. The Fourth Industrial Revolution. Currency.Google ScholarGoogle Scholar
  62. M. F. Shoffner and D. J. Dockery. 2015. Promoting interest in and entry into science, technology, engineering, and mathematics careers. American Psychological Association Handbook of Career Intervention 2 (2015), 125--137.Google ScholarGoogle Scholar
  63. Katie A. Siek, Kay Connelly, Amanda Stephano, Suzanne Menzel, Jacki Bauer, and Beth Plale. 2006. Breaking the geek myth: Addressing young women’s misperceptions about technology careers. Learning and Technology, Leading with 33, 7 (2006), 19--22.Google ScholarGoogle Scholar
  64. Louise Soe and Elaine K. Yakura. 2008. What’s wrong with the pipeline? Assumptions about gender and culture in IT work. Women’s Studies 37, 3 (2008), 176--201.Google ScholarGoogle Scholar
  65. Ellen Spertus. 1991. Why are There So Few Female Computer Scientists? MIT. Retrieved March 10, 2019 from https://dspace.mit.edu/bitstream/handle/1721.1/7040/AITR-1315.pdf?sequence=2.Google ScholarGoogle Scholar
  66. Dorian Stoilescu and Gunawardena Egodawatte. 2010. Gender differences in the use of computers, programming, and peer interactions in computer science classrooms. Computer Science Education 20, 4 (2010), 283--300.Google ScholarGoogle ScholarCross RefCross Ref
  67. Jane G. Stout, Nilanjana Dasgupta, Matthew Hunsinger, and Melissa A. McManus. 2011. STEMing the tide: Using ingroup experts to inoculate women’s self-concept in science, technology, engineering, and mathematics (STEM). Journal of Personality Social Psychology 100, 2 (2011), 255.Google ScholarGoogle ScholarCross RefCross Ref
  68. Milagros Sáinz and Jacquelynne Eccles. 2012. Self-concept of computer and math ability: Gender implications across time and within ICT studies. Journal of Vocational Behavior 80, 2 (2012), 486--499.Google ScholarGoogle ScholarCross RefCross Ref
  69. Mo-Yin S. Tam and Gilbert W. Bassett, Jr. 2006. The gender gap in information technology. Removing Barriers: Women in Academic Science, Technology, Engineering, Mathematics (2006), 119--133.Google ScholarGoogle Scholar
  70. Brendan Tangney, Elizabeth Oldham, Claire Conneely, Stephen Barrett, and John Lawlor. 2010. Pedagogy and processes for a computer programming outreach workshop—The bridge to college model. IEEE Transactions on Education 53, 1 (2010), 53--60.Google ScholarGoogle ScholarDigital LibraryDigital Library
  71. Sherri L. Turner, Julia L. Conkel, Michael Starkey, Rachel Landgraf, Richard T. Lapan, Jason J. Siewert, Allison Reich, Michelle J. Trotter, Eric R. Neumaier, and Ju-Ping Huang. 2008. Gender differences in Holland vocational personality types: Implications for school counselors. Professional School Counseling 11, 5 (2008), 2156759X0801100505.Google ScholarGoogle Scholar
  72. 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 ScholarGoogle ScholarCross RefCross Ref
  73. Anna Vitores and Adriana Gil-Juárez. 2016. The trouble with ’women in computing’: A critical examination of the deployment of research on the gender gap in computer science. Journal of Gender Studies 25, 6 (2016), 666--680.Google ScholarGoogle ScholarCross RefCross Ref
  74. Linda L. Werner, Brian Hanks, and Charlie McDowell. 2004. Pair-programming helps female computer science students. Journal on Educational Resources in Computing 4, 1 (2004), 4.Google ScholarGoogle ScholarDigital LibraryDigital Library
  75. Michele A. Whitecraft and Wendy M. Williams. 2010. Making Software: What Really Works, and Why We Believe It. O’Reilly Media, Inc., 221--238.Google ScholarGoogle Scholar
  76. Gayna Williams. 2014. Are you sure your software is gender-neutral? ACM Interactions 21, 1 (2014), 36--39.Google ScholarGoogle ScholarDigital LibraryDigital Library
  77. Billy Wong. 2016. ‘I’m good, but not that good’: Digitally-skilled young people’s identity in computing. Computer Science Education 26, 4 (2016), 299--317.Google ScholarGoogle ScholarCross RefCross Ref
  78. Anita Williams Woolley, Christopher F. Chabris, Alex Pentland, Nada Hashmi, and Thomas W. Malone. 2010. Evidence for a collective intelligence factor in the performance of human groups. Science 330, 6004 (2010), 686--688.Google ScholarGoogle ScholarCross RefCross Ref
  79. Carolyn Zahn-Waxler. 2000. The development of empathy, guilt, and internalization of distress: Implications for gender differences in internalizing and externalizing problems. Anxiety, Depression, Emotion (2000), 222--265.Google ScholarGoogle ScholarCross RefCross Ref

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        cover image ACM Transactions on Computing Education
        ACM Transactions on Computing Education  Volume 20, Issue 4
        December 2020
        146 pages
        EISSN:1946-6226
        DOI:10.1145/3428081
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        Publication History

        • Published: 17 October 2020
        • Revised: 1 July 2020
        • Accepted: 1 July 2020
        • Received: 1 March 2019
        Published in toce Volume 20, Issue 4

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