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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.
Wilson et al. (Thu,) studied this question.