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Debugging is a cornerstone of programming and has been shown to be especially problematic for beginners. While there has been some work trying to understand the difficulties that beginners face with debugging, investigating common mistakes or specific error types they struggle with, there is little work that focuses on in-depth analysis of how novice programmers approach debugging, and how it changes over time. In this paper, we present MAADS (MixedMethods Approach for the Analysis of Debugging Sequences), a scalable and generalizable approach that combines quantitative and qualitative methods by using a state/action representation and visualization to gain knowledge about the debugging process through a step by step analysis. To demonstrate the utility of MAADS, we analyzed the debugging processes of middle school students who developed code within May’s Journey, a game designed to teach basic programming principles. The approach showed great utility in identifying differences in students’ debugging techniques and learning paths.
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Teaching Explicit Programming Strategies to Adolescents
One way to teach programming problem solving is to teach explicit, step-by-step strategies. While prior work has shown these to be effective in controlled settings, there has been little work investigating their efficacy in classrooms. We conducted a 5-week case study with 17 students aged 15-18, investigating students' sentiments toward two strategies for debugging and code reuse, students' use of scaffolding to execute these strategies, and associations between students' strategy use and their success at independently writing programs in class. We found that while students reported the strategies to be valuable, many had trouble regulating their choice of strategies, defaulting to ineffective trial and error, even when they knew systematic strategies would be more effective. Students that embraced the debugging strategy completed more features in a game development project, but this association was mediated by other factors, such as reliance on help, strategy self-efficacy, and mastery of the programming language used in the class. These results suggest that teaching of strategies may require more explicit instruction on strategy selection and self-regulation.
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- PAR ID:
- 10119844
- Date Published:
- Journal Name:
- Symposium on Computer Science Education
- Page Range / eLocation ID:
- 469 to 475
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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- Free Publicly Accessible Full Text
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Accepted Manuscript1.0
- Conference Paper:
- https://doi.org/10.1145/3287324.3287371
