Brenda Cantwell Wilson
ABSTRACT
This study was conducted to determine factors that promote success in an introductory college computer science course. The model included twelve possible predictive factors including math background, attribution for success/failure (luck, effort, difficulty of task, and ability), domain specific self-efficacy, encouragement, comfort level in the course, work style preference, previous programming experience, previous non-programming computer experience, and gender. Subjects included 105 students enrolled in a CS1 introductory computer science course at a midwestern university. The study revealed three predictive factors in the following order of importance: comfort level, math, and attribution to luck for success/failure. Comfort level and math background were found to have a positive influence on success, whereas attribution to luck had a negative influence. The study also revealed by considering the different types of previous computer experiences (including formal programming class, self-initiated programming, internet use, game playing, and productivity software use) that both a formal class in programming and game playing were predictive of success. Formal training had a positive influence and games a negative influence on class grade.
- 1.Bandura, A. Self-efficacy: Toward a unifying theory of behavioral change. Psychological Review, 84(2), (1977), 191-215.Google Scholar
Cross Ref
- 2.Bunderson, E.D., & Christensen, M.E. An analysis of retention problems for female students in university computer science programs. Journal of Research on Computing in Education 28(1), (1995), 1-15.Google ScholarCross Ref
- 3.Clarke, V.A., & Chambers, S.M. Gender-based factors in computing enrollments and achievement: Evidence from a study of tertiary students. Journal of Educational Computing Research, 5(4), (1989), 409- 429.Google ScholarCross Ref
- 4.Cottrell, J. I'm a stranger here myself: A consideration of women in computing. Proceedings of the 1992 ACM SIG UCCS User Services Conference, (1992), 71 - 76. Google ScholarDigital Library
- 5.Deboer, G.E. Factors related to the decision of men and women to continue taking science courses in college. Journal of Research in Science Teaching, 21(3), (1984), 325-329.Google ScholarCross Ref
- 6.Dweck, C.S., & Leggett, E.L. A social-cognitive approach to motivation and personality. Psychological Review (95), (1988), 256-273.Google ScholarCross Ref
- 7.Kersteen, Z.A., Linn, M.C., Clancey, M., & Hardyck, C. Previous experience and the learning of computer programming: The computer helps those who help themselves. Journal of Educational Computing Research 4(3), (1988).Google ScholarCross Ref
- 8.Maeher, M.L. On doing well in science: Why Johnny no longer excels; why Sarah never did. In S.G. Paris, G.M. Olsen, & H.W. Stevenson (Eds.), Learning and Motivation in the Classroom (Chapter 8), (1988).Google Scholar
- 9.Miura, I.T. The relationship of computer self-efficacy expectations to computer interest and course enrollment in college. Sex Roles, 16(5), (1987), 303- 311.Google ScholarCross Ref
- 10.Ramalingam, V., & Wiedenbeck, S. Development and validation of scores on a computer programming selfefficacy scale and group analyses of novice programmer self-efficacy. Journal of Educational Computing Research, 19(4), ( 1998 ), 367-381.Google Scholar
- 11.Taylor, H., & Mounfield, L. An analysis of success factors in college computer science: High school methodology is a key element. Journal of Research on Computing in Education, 24(2), (1991), 240-245.Google ScholarCross Ref
- 12.Taylor, H., & Mounfield, L. Exploration of the relationship between prior computing experience and gender on success in college computer science. Journal of Educational Computing Research 11(4), (1994), 291-306.Google ScholarCross Ref
Index Terms
- Contributing to success in an introductory computer science course: a study of twelve factors
Recommendations
Contributing to success in an introductory computer science course: a study of twelve factors
This study was conducted to determine factors that promote success in an introductory college computer science course. The model included twelve possible predictive factors including math background, attribution for success/failure (luck, effort, ...
Student attitudes toward statistics before and after a computer-integrated introductory statistics course
A validated questionnaire measuring the attitude of engineering students toward statistics was administered to 46 male and 17 female undergraduate engineers during the first and last week of class. The objective was to test the hypothesis that a newly ...
Comments