Learning to Program From Interactive Example Code (With and Without Intentional Bugs)

Abstract

Computing education for learning to program has made great strides in the current century. Exciting educational technologies are now available and active learning pedagogies are increasingly used. Interest is strong, but the longstanding problem remains: learning to program as an analytical endeavor is quite frustrating for many. The purpose of this study is to discover ways to mitigate this frustration. It researches ways to help students comprehend code by guiding them to take it apart (through reading, tracing, completing, and debugging) as they learn to write code on their own. This study contributes to the understanding of learning from errors. It also builds upon and further develops the emergent pedagogy of de-constructionism. The de-constructionist approach involves taking things apart, practice, and learning from errors. This study applies a de-constructionist approach in an experiment with ~80 undergraduates learning Python in an introductory programming class. During weekly lab periods, students engaged with web-based interactive practice problems that emphasize reading, tracing, completing, and in some cases, debugging code. Students also wrote code for lab and homework assignments. Approximately half of the students were given some that involved learning from bugs that were intentionally placed in the provided code, while the others were not. Learning gains were assessed using pre/post tests and exams. Surveys were used to measure attitudes. Learning gains and attitudes were compared according to condition (Bugs, NoBugs), prior experience, gender, minority status, and class size. This study demonstrates that bugs can be intentionally incorporated into practice problems that students like to solve, without detrimental effects on learning or attitudes about computing. It also contributes to the literature on code comprehension.