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Heidi Taveter; Marina Lepp – Informatics in Education, 2025
Learning programming has become increasingly popular, with learners from diverse backgrounds and experiences requiring different support. Programming-process analysis helps to identify solver types and needs for assistance. The study examined students' behavior patterns in programming among beginners and non-beginners to identify solver types,…
Descriptors: Behavior Patterns, Novices, Expertise, Programming
Xiner Liu; Andres Felipe Zambrano; Ryan S. Baker; Amanda Barany; Jaclyn Ocumpaugh; Jiayi Zhang; Maciej Pankiewicz; Nidhi Nasiar; Zhanlan Wei – Journal of Learning Analytics, 2025
This study explores the potential of the large language model GPT-4 as an automated tool for qualitative data analysis by educational researchers, exploring which techniques are most successful for different types of constructs. Specifically, we assess three different prompt engineering strategies -- Zero-shot, Few-shot, and Fewshot with…
Descriptors: Coding, Artificial Intelligence, Automation, Data Analysis
Hoffman, Heather J.; Elmi, Angelo F. – Journal of Statistics and Data Science Education, 2021
Teaching students statistical programming languages while simultaneously teaching them how to debug erroneous code is challenging. The traditional programming course focuses on error-free learning in class while students' experiences outside of class typically involve error-full learning. While error-free teaching consists of focused lectures…
Descriptors: Statistics Education, Programming Languages, Troubleshooting, Coding
Lepp, Marina; Palts, Tauno; Luik, Piret; Kaspar, Papli; Suviste, Reelika; Säde, Merilin; Hollo, Kaspar; Vaherpuu, Vello; Tõnisson, Eno – International Review of Research in Open and Distributed Learning, 2018
Learning programming has become more and more popular and organizing introductory massive open online courses (MOOCs) on programming can be one way to bring this education to the masses. While programming MOOCs usually use automated assessment to give feedback on the submitted code, the lack of understanding of certain aspects of the tasks and…
Descriptors: Troubleshooting, Introductory Courses, Programming, Computer Science Education
Fitzgerald, S.; McCauley, R.; Hanks, B.; Murphy, L.; Simon, B.; Zander, C. – IEEE Transactions on Education, 2010
Learning to debug is a difficult, yet essential, aspect of learning to program. Students in this multi-institutional study report that finding bugs is harder than fixing them. They use a wide variety of debugging strategies, some of them unexpected. Time spent on understanding the problem can be effective. Pattern matching, particularly at the…
Descriptors: Undergraduate Study, Computer Science Education, Introductory Courses, Programming
Fitzgerald, Sue; Lewandowski, Gary; McCauley, Renee; Murphy, Laurie; Simon, Beth; Thomas, Lynda; Zander, Carol – Computer Science Education, 2008
Debugging is often difficult and frustrating for novices. Yet because students typically debug outside the classroom and often in isolation, instructors rarely have the opportunity to closely observe students while they debug. This paper describes the details of an exploratory study of the debugging skills and behaviors of contemporary novice Java…
Descriptors: Troubleshooting, Teaching Methods, Computer Science Education, Programming
Bennedsen, Jens; Schulte, Carsten – ACM Transactions on Computing Education, 2010
This article reports on an experiment undertaken in order to evaluate the effect of a program visualization tool for helping students to better understand the dynamics of object-oriented programs. The concrete tool used was BlueJ's debugger and object inspector. The study was done as a control-group experiment in an introductory programming…
Descriptors: Programming, Introductory Courses, Control Groups, Experimental Groups