skip to main content
10.1145/2016911.2016915acmconferencesArticle/Chapter ViewAbstractPublication PagesicerConference Proceedingsconference-collections
research-article

Deciding to major in computer science: a grounded theory of students' self-assessment of ability

Published:08 August 2011Publication History

ABSTRACT

There is great interest in understanding and influencing students' attraction to computing-related majors. This qualitative study is based on interviews with 31 students enrolled in introductory programming courses at two public universities in the United States. This paper presents a model of five factors that influence student decisions to major in CS and elaborates on our grounded theory analysis of one of these factors: how students assess their CS-related ability. We describe how students measure their ability in terms of speed, grades, and previous experience and how students make interpretations and decisions based upon these measurements. We found that students' interpretations were influenced by experiences in their environments and beliefs about ability as being fixed or malleable.

References

  1. Astin, A. W. (1993). What matters in college? San Francisco, CA: Jossey-Bass.Google ScholarGoogle Scholar
  2. Bandura, A. (1977). Self-efficacy. Psychological Review, 84(2).Google ScholarGoogle Scholar
  3. Barker, L. J., Garvin-Doxas, K., & Jackson, M. H. (2002). Defensive climate in the computer science classroom. In Proc. SIGCSE. Google ScholarGoogle ScholarDigital LibraryDigital Library
  4. Barker, L. J., McDowell, C., & Kalahar, K. (2009). Exploring factors that influence computer science introductory course students to persist in the major. In Proc. SIGCSE. Google ScholarGoogle ScholarDigital LibraryDigital Library
  5. Beyer, S., Rynes, K., & Haller, S. (2004). Deterrents to women taking computer science courses. IEEE Technology and Society Magazine, 23(1).Google ScholarGoogle ScholarCross RefCross Ref
  6. Boyle, R., Carter, J., & Clark, M. (2002). What makes them succeed? Entry, progression and graduation in Computer Science. J. Further & Higher Education, 26(1).Google ScholarGoogle Scholar
  7. Carter, L. (2006). Why students with an apparent aptitude for computer science don't choose to major in computer science. In Proc. SIGCSE. Google ScholarGoogle ScholarDigital LibraryDigital Library
  8. Corbin, J. M., & Strauss, A. C. (2008). Basics of Qualitative Research. Thousand Oaks, CA: SAGE Publications.Google ScholarGoogle Scholar
  9. Cutts, Q., Cutts, E., Draper, S., O'Donnell, P., & Saffrey, P. (2010). Manipulating mindset to positively influence introductory programming performance. In Proc. SIGCSE. Google ScholarGoogle ScholarDigital LibraryDigital Library
  10. Dweck, C. S., & Leggett, E. L. (1988). A social-cognitive approach to motivation and personality. Psychological Review, 95(2).Google ScholarGoogle Scholar
  11. Eccles, J. S. (2007). Where are all the women? In S. J. Ceci & W. M. Williams (Eds.), Why aren't more women in science? Washington, DC: American Psychological Association.Google ScholarGoogle Scholar
  12. Gal-Ezer, J., Shahak, D., & Zur, E. (2009). Computer science issues in high school. In Proc. ITICSE. Google ScholarGoogle ScholarDigital LibraryDigital Library
  13. Goyette, K. A., & Mullen, A. L. (2006). Who studies the arts and sciences? J. Higher Education, 77(3).Google ScholarGoogle Scholar
  14. Kinnunen, P., & Malmi, L. (2006). Why students drop out CS1 course? In Proc. ICER. Google ScholarGoogle ScholarDigital LibraryDigital Library
  15. Lacey, A. T., & Wright, B. (2009). Employment outlook 2009-18. Monthly Labor Review, 132(11).Google ScholarGoogle Scholar
  16. Lent, R. W., Brown, S. D., & Hackett, G. (1995). Toward a unifying social cognitive theory of career and academic interest, choice, and performance. J. Vocational Behavior, 45(1).Google ScholarGoogle Scholar
  17. Lent, R. W., Lopez, Jr., A. M., Lopez, F. G., & Sheu, H. (2008). Social cognitive career theory and the prediction of interests and choice goals in the computing disciplines. J. Vocational Behavior, 73(1).Google ScholarGoogle Scholar
  18. Lewis, C. (2007). Attitudes and beliefs about computer science among students and faculty. SIGCSE Bulletin, 39(2). Google ScholarGoogle ScholarDigital LibraryDigital Library
  19. Margolis, J., & Fisher, A. (2003). Unlocking the Clubhouse. Cambridge, MA: MIT Press.Google ScholarGoogle Scholar
  20. Molden, D. C., & Dweck, C. S. (2006). Finding "meaning" in psychology. American Psychologist, 61(3).Google ScholarGoogle Scholar
  21. Murphy, L., & Thomas, L. (2008). Dangers of a fixed mindset. In Proc. ITICSE. Google ScholarGoogle ScholarDigital LibraryDigital Library
  22. Porter, S., & Umbach, P. (2006). College major choice. Research in Higher Education, 47.Google ScholarGoogle Scholar
  23. Robins, A. (2010). Learning edge momentum. Computer Science Education, 20(1).Google ScholarGoogle Scholar
  24. Simon, B., Hanks, B., Murphy, L., Fitzgerald, S., McCauley, R., Thomas, L., & Zander, C. (2008). Saying isn't necessarily believing. In Proc. ICER. Google ScholarGoogle ScholarDigital LibraryDigital Library
  25. Steele, C. M. (1997). A threat in the air. American Psychologist, 52(6), 613--629.Google ScholarGoogle ScholarCross RefCross Ref
  26. Strauss, A. C., & Corbin, J. M. (1990). Basics of Qualitative Research. Thousand Oaks, CA: SAGE Publications.Google ScholarGoogle Scholar
  27. Suddaby, R. (2006). From the editors: What grounded theory is not. Academy of Management J., 49(4).Google ScholarGoogle Scholar
  28. Wilson, B. C. (2002). A study of factors promoting success in computer science including gender differences. Computer Science Education, 12(1-2).Google ScholarGoogle Scholar
  29. Zweben, S. (2010). Undergraduate CS enrollment continues rising. Computing Research News, 22(3).Google ScholarGoogle Scholar

Index Terms

  1. Deciding to major in computer science: a grounded theory of students' self-assessment of ability
        Index terms have been assigned to the content through auto-classification.

        Recommendations

        Comments

        Login options

        Check if you have access through your login credentials or your institution to get full access on this article.

        Sign in
        • Published in

          cover image ACM Conferences
          ICER '11: Proceedings of the seventh international workshop on Computing education research
          August 2011
          156 pages
          ISBN:9781450308298
          DOI:10.1145/2016911
          • General Chair:
          • Kate Sanders,
          • Program Chairs:
          • Michael E. Caspersen,
          • Alison Clear,
          • Kate Sanders

          Copyright © 2011 ACM

          Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

          Publisher

          Association for Computing Machinery

          New York, NY, United States

          Publication History

          • Published: 8 August 2011

          Permissions

          Request permissions about this article.

          Request Permissions

          Check for updates

          Qualifiers

          • research-article

          Acceptance Rates

          Overall Acceptance Rate189of803submissions,24%

          Upcoming Conference

          ICER 2024
          ACM Conference on International Computing Education Research
          August 13 - 15, 2024
          Melbourne , VIC , Australia

        PDF Format

        View or Download as a PDF file.

        PDF

        eReader

        View online with eReader.

        eReader