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Fatima Abu Deeb; Timothy Hickey – Computer Science Education, 2024
Background and Context: Auto-graders are praised by novice students learning to program, as they provide them with automatic feedback about their problem-solving process. However, some students often make random changes when they have errors in their code, without engaging in deliberate thinking about the cause of the error. Objective: To…
Descriptors: Reflection, Automation, Grading, Novices
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Meghan M. Parkinson; Seppe Hermans; David Gijbels; Daniel L. Dinsmore – Computer Science Education, 2024
Background and Context: More data are needed about how young learners identify and fix errors while programming in pairs. Objective: The study will identify discernible patterns in the intersection between debugging processes and the type of regulation used during debugging while children engage in coding to drive further theory and model…
Descriptors: Computer Science Education, Troubleshooting, Cooperative Learning, Coding
Samim Mirhosseini – ProQuest LLC, 2023
Computer science instructors typically have many responsibilities, such as creating material, delivering lectures, clarifying student questions, and grading student deliverables, while the demand for computer science education has been increasing. Handling all of these responsibilities is challenging in itself. However, it is made worse when…
Descriptors: Computer Science Education, Teacher Responsibility, Faculty Workload, Instructional Materials
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Zeng, Mini; Zhu, Feng – Journal of Cybersecurity Education, Research and Practice, 2021
Software vulnerabilities have become a severe cybersecurity issue. There are numerous resources of industry best practices available, but it is still challenging to effectively teach secure coding practices. The resources are not designed for classroom usage because the amount of information is overwhelming for students. There are efforts in…
Descriptors: Computer Software, Coding, Computer Security, Computer Science Education
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Dahn, Maggie; DeLiema, David; Enyedy, Noel – Teachers College Record, 2020
Background/Context: Computer science has been making its way into K-12 education for some time now. As computer science education has moved into learning spaces, research has focused on teaching computer science skills and principles but has not sufficiently explored the emotional aspects of students' experiences. This topic warrants further study…
Descriptors: Computer Science Education, Coding, Programming, Student Experience
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Mangaroska, Katerina; Sharma, Kshitij; Gaševic, Dragan; Giannakos, Michail – Journal of Computer Assisted Learning, 2022
Background: Problem-solving is a multidimensional and dynamic process that requires and interlinks cognitive, metacognitive, and affective dimensions of learning. However, current approaches practiced in computing education research (CER) are not sufficient to capture information beyond the basic programming process data (i.e., IDE-log data).…
Descriptors: Cognitive Processes, Psychological Patterns, Problem Solving, Programming
Hachisu, Yoshinari; Yoshida, Atsushi – International Association for Development of the Information Society, 2014
For supporting the education of debugging skills, we propose a system for generating error correction questions of programs and checking the correctness. The system generates HTML files for answering questions and CGI programs for checking answers. Learners read and answer questions on Web browsers. For management of error injection, we have…
Descriptors: Error Correction, Programming, Computer Science Education, Questioning Techniques