An Analysis of Java Programming Behaviors, Affect, Perceptions, and Syntax Errors among Low-Achieving, Average, and High-Achieving Novice Programmers

• 主要作者: Rodrigo, Ma. Mercedes T.
• 格式: text
• 出版: Archīum Ateneo 2014
• 主題: Computer Sciences
• 在線閱讀: https://archium.ateneo.edu/discs-faculty-pubs/12; https://journals.sagepub.com/doi/abs/10.2190/EC.49.3.b
• 機構: Ateneo De Manila University

In this article we quantitatively and qualitatively analyze a sample of novice programmer compilation log data, exploring whether (or how) low-achieving, average, and high-achieving students vary in their grasp of these introductory concepts. High-achieving students self-reported having the easiest time learning the introductory programming topics. In a quantitative analysis, though, high-achieving and average students were: 1) more effective at debugging (on average, as quantified by Jadud's Error Quotient (EQ)) than low-achieving students; and 2) were least confused, as quantified using Lee's confusion metric. However, the differences in EQ and confusion between groups were not statistically significant. This implied that all groups struggled with programming to similar extents. This finding was further supported by was used to delineate two sets of variables. The results indicate that preference for autonomy in computer science learning positively predicts selfefficacy in learning computer science with the strongest coefficient. Computer science learner preference for teacher control is also a positive predictor. However, preference for participation in managing the computer class and preference for depending on the teacher did not play a significant role in the students' self-efficacy in learning computer science.