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Research Article

In-school and/or out-of-school computer science learning influence on CS career interests, mediated by having role-models

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Received 15 Feb 2023, Accepted 29 Nov 2023, Published online: 26 Dec 2023

References

  • Amazon Future Engineer. (2021). Amazon employees share their stories to spark student curiosity in tech. [Online]. Available: https://www.aboutamazon.com/news/community/amazon-employees-share-their-stories-to-spark-student-curiosity-in-tech
  • Armoni, M., & Gal-Ezer, J. (2014). High school computer science education paves the way for higher education: The Israeli case. Computer Science Education, 24(2–3), 101–122. https://doi.org/10.1080/08993408.2014.936655
  • Ashcraft, C., Eger, E., & Friend, M. (2012). Girls in IT: The facts. National Center for Women & IT. Boulder, CO.
  • Ball, C., Huang, K. T., Cotten, S. R., & Rikard, R. V. (2017). Pressurizing the STEM pipeline: An expectancy-value theory analysis of youths’ STEM attitudes. Journal of Science Education and Technology, 26(4), 372–382. https://doi.org/10.1007/s10956-017-9685-1
  • Beaubouef, T., & Mason, J. (2005). Why the high attrition rate for computer science students: Some thoughts and observations. ACM SIGCSE Bulletin, 37(2), 103–106. https://doi.org/10.1145/1083431.1083474
  • Bettinger, E. P., & Long, B. T. (2005). Do faculty serve as role models? The impact of instructor gender on female students. American Economic Review, 95(2), 152–157. https://doi.org/10.1257/000282805774670149
  • Betz, M., & O'Connell, L. (1992). The role of inside and same‐sex influencers in the choice of nontraditional occupations. Sociological inquiry, 62(1), 98–106.
  • Braswell, K., & Rankin, Y. A. (2023). Intech: Designing intersectional learning experiences for black girls. Interactions, 30(1), 66–69. https://doi.org/10.1145/3575868
  • Clevey, L. (2018). Comparing the impacts of mentors vs. role models across domains: A meta-analysis. Eastern Michigan University.
  • Codding, D., Alkhateeb, B., Mouza, C., & Pollock, L. (2021). From professional development to pedagogy: Examining how computer science teachers conceptualize and apply culturally responsive pedagogy. Journal of Technology & Teacher Education, 29(4), 497–532.
  • Code.org. (2022). Teachers guide: Engaging your students in CS Journeys. [Online]. Available: https://code.org/files/csjourneys/csjourneys-teacherguide.pdf
  • Decker, A., & McGill, M. M. (2019). A systematic review exploring the differences in reported data for pre-college educational activities for computer science, engineering, and other STEM disciplines. Education Sciences, 9(2), 69.
  • DeLyser, L. A. (2018, July). A community model of csforall: Analysis of community commitments for cs education. In Proceedings of the 23rd Annual ACM Conference on Innovation and Technology in Computer Science Education, Larnaca Cyprus, (pp. 99–104).
  • Diekman, A. B., Steinberg, M., Brown, E. R., Belanger, A. L., & Clark, E. K. (2017). A goal congruity model of role entry, engagement, and exit: Understanding communal goal processes in STEM gender gaps. Personality and Social Psychology Review, 21(2), 142–175. https://doi.org/10.1177/1088868316642141
  • Dweck, C. S. (2007). Is math a gift? Beliefs that put females at risk. In S. J. Ceci & W. M. Williams (Eds.), Why aren’t more women in science?: Top researchers debate the evidence (pp. 47–55). American Psychological Association. https://doi.org/10.1037/11546-004
  • Eccles, J. S., & Wigfield, A. (2020). From expectancy-value theory to situated expectancy-value theory: A developmental, social cognitive, and sociocultural perspective on motivation. Contemporary Educational Psychology, 61, 101859. https://doi.org/10.1016/j.cedpsych.2020.101859
  • Eglash, R., Gilbert, J. E., & Foster, E. (2013). Toward culturally responsive computing education. Communications of the ACM, 56(7), 33–36. https://doi.org/10.1145/2483852.2483864
  • Gallup-Amazon. (2021). Developing careers of the Future: A study of student access to, and interest in, computer science, https://www.gallup.com/analytics/354740/study-of-student-interest-in-computer-science.aspx
  • Gartzia, L., Morgenroth, T., Ryan, M. K., & Peters, K. (2021). Testing the motivational effects of attainable role models: Field and experimental evidence. Journal of Theoretical Social Psychology, 5(4), 591–602. https://doi.org/10.1002/jts5.121
  • Hazari, Z., Sonnert, G., Sadler, P. M., & Shanahan, M. C. (2010). Connecting high school physics experiences, outcome expectations, physics identity, and physics career choice: A gender study. Journal of Research in Science Teaching, 47(8), 978–1003. https://doi.org/10.1002/tea.20363
  • Ho, D. E., Imai, K., King, G., & Stuart, E. A. (2007). Matching as nonparametric preprocessing for reducing model dependence in parametric causal inference. Political Analysis, 15(3), 199–236. https://doi.org/10.1093/pan/mpl013
  • Imai, K., Keele, L., & Tingley, D. (2010b). A general approach to causal mediation analysis. Psychological Methods, 15(4), 309–334. https://doi.org/10.1037/a0020761
  • Imai, K., Keele, L., Tingley, D., & Yamamoto, T. (2010a). Causal mediation analysis using R. In H. D. Vinod (Ed.), Advances in social science research using R (pp. 129–154). Springer.
  • Ito, M., Baumer, S., Bittanti, M., Cody, R., Stephenson, B. H., Horst, H. A., & Perkel, D. (2009). Hanging out, messing around, and geeking out: Kids living and learning with new media. MIT Press.
  • Ivie, R., Czujko, R., & Stowe, K. (2002). Women physicists speak: The 2001 international study of women in physics. AIP Conference Proceedings, Paris (France), 628( 1), 49–70. AIP.
  • Ivie, R., & Guo, S. (2006). Women physicists speak again. American Institute of Physics. Retrieved from http://www.aip.org/statistics/trend/report/iupap05.pdf
  • Jo, B., Stuart, E. A., MacKinnon, D. P., & Vinokur, A. D. (2011). The use of propensity scores in mediation analysis. Multivariate Behavioral Research, 46(3), 425–452. https://doi.org/10.1080/00273171.2011.576624
  • Kahle, J. B., & Lakes, M. K. (1983). The myth of equality in science classrooms. Journal of Research in Science Teaching, 20(2), 131–140. https://doi.org/10.1002/tea.3660200205
  • Kearney, M. S., & Levine, P. B. (2020). Role models, mentors, and media Influences. The Future of Children, 30(1), 83–106. https://doi.org/10.1353/foc.2020.0006
  • Kölling, M. (1999). The problem of teaching object-oriented programming. Journal of Object Oriented Programming, 11(8), 8–15.
  • Liggett, J. B. (2014). Geek as a constructed identity and a crucial component of STEM persistence. [ Master of Science thesis]. University of North Texas.
  • Lockwood, P. (2006). Someone like me can be successful”: Do college students need same‐gender role models? Psychology of Women Quarterly, 30(1), 36–46. https://doi.org/10.1111/j.1471-6402.2006.00260.x
  • Mani, A., & Riley, E. (2019). Social networks, role models, peer effects, and aspirations, WIDER Working Paper, No. 2019/120, ISBN 978-92-9256-756-9, The United Nations University World Institute for Development Economics Research (UNU-WIDER), Helsinki. https://doi.org/10.35188/UNU-WIDER/2019/756-9
  • Margolis, J., Estrella, R., Goode, J., Holme, J. J., & Nao, K. (2017). Stuck in the shallow end: Education, race, and computing. The MIT Press.
  • Marken, S., Crabtree, S. (2021). Role models spark students’ interest in computer science. Retrieved from https://news.gallup.com/poll/355070/role-models-spark-students-interest-computer-science.aspx
  • McKenna, B. W., & Bergie, L. (2016). Creating the next generation of innovators. Publications & Research Paper 6. http://digitalcommons.imsa.edu/stratinnov_pr/6.
  • Miller, D. I., Eagly, A. H., & Linn, M. C. (2015). Women’s representation in science predicts national gender‐science stereotypes: Evidence from 66 nations. Journal of Educational Psychology, 107(3), 631–644. https://doi.org/10.1037/edu0000005
  • Morgenroth, T., Ryan, M. K., & Peters, K. (2015). The motivational theory of role modeling: How role models influence role aspirants’ goals. Review of General Psychology, 19(4), 465–483. https://doi.org/10.1037/gpr0000059
  • Ni, L., Tian, Y., McKlin, T., & Baskin, J. (2023). Who is teaching computer science? Understanding professional identity of American computer science teachers through a national survey. Computer Science Education.
  • Potvin, P., & Hasni, A. (2014). Interest, motivation and attitude towards science and technology at K‐12 levels: A systematic review of 12 years of educational research. Studies in Science Education, 50(1), 85–129. https://doi.org/10.1080/03057267.2014.881626
  • Ruggles, S., Flood, S., Goeken, R., Schouweiler, M., & Sobek, M. (2022). IPUMS USA: Version 12.0 2020 American community survey. IPUMS. https://doi.org/10.18128/D010.V12.0
  • Sax, L. J., Lehman, K. J., Jacobs, J. A., Kanny, M. A., Lim, G., Monje-Paulson, L., & Zimmerman, H. B. (2017). Anatomy of an enduring gender gap: The evolution of women’s participation in computer science. The Journal of Higher Education, 88(2), 258–293. https://doi.org/10.1080/00221546.2016.1257306
  • Stack Overflow. (2021) Stack Overflow developers survey 2021. [Online]. Available: https://insights.stackoverflow.com/survey/2021
  • Stehlik, M., Cawley, E., & Kosbie, D. (2020, February). Cmu cs academy: A browser-based, text-based introduction to programming through graphics and animations in python. In Proceedings of the 51st ACM Technical Symposium on Computer Science Education, USA, (pp. 1420–1420).
  • Stern, J., Reid, E., & Bancroft, K. (2015, February). Teaching introductory computer science for a diverse student body: Girls who code style. In Proceedings of the 46th ACM Technical Symposium on Computer Science Education, Kansas, Missouri, USA, (pp. 705–705).
  • Sto. Domingo, M. R., Sharp, S., Freeman, A., Freeman, Jr, T., Harmon, K., Wiggs, M., Sathy, V., Panter, A.T., Oseguera, L., Sun, S., & Williams, M.E. (2019). Replicating Meyerhoff for inclusive excellence in STEM. Science, 364(6438), 335–337.
  • 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), 1–13. https://doi.org/10.1016/j.jvb.2017.09.008
  • Twarek, B. (2018). A call to celebrate diversity in computer science. Retrived from https://advocate.csteachers.org/tag/role-models/
  • Tytler, R. (2014). Attitudes, identity, and aspirations toward science. In N. G. Lederman & S. K. Abell (Eds.), Handbook of research on science education volume II (pp. 82–102). Taylor & Francis.
  • Upadhyaya, B., McGill, M. M., & Decker, A. (2020, February). A longitudinal analysis of k-12 computing education research in the United States: Implications and recommendations for change. In Proceedings of the 51st ACM technical symposium on computer science education, USA, (pp. 605–611).
  • Wang, M. T., & Degol, J. (2013). Motivational pathways to STEM career choices: Using expectancy–value perspective to understand individual and gender differences in STEM fields. Developmental Review, 33(4), 304–340. https://doi.org/10.1016/j.dr.2013.08.001
  • Wigfield, A. (1994). Expectancy-value theory of achievement motivation: A developmental perspective. Educational Psychology Review, 6(1), 49–78. https://doi.org/10.1007/BF02209024