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Oscar Karnalim; Hapnes Toba; Meliana Christianti Johan – Education and Information Technologies, 2024
Artificial Intelligence (AI) can foster education but can also be misused to breach academic integrity. Large language models like ChatGPT are able to generate solutions for individual assessments that are expected to be completed independently. There are a number of automated detectors for AI assisted work. However, most of them are not dedicated…
Descriptors: Artificial Intelligence, Academic Achievement, Integrity, Introductory Courses
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Solano-Flores, Guillermo – Educational Measurement: Issues and Practice, 2021
This article proposes a Boolean approach to representing and analyzing interobserver agreement in dichotomous coding. Building on the notion that observations are samples of a universe of observations, it submits that coding can be viewed as a process in which observers sample pieces of evidence on constructs. It distinguishes between formal and…
Descriptors: Online Searching, Coding, Interrater Reliability, Evidence
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Shi, Yang; Mao, Ye; Barnes, Tiffany; Chi, Min; Price, Thomas W. – International Educational Data Mining Society, 2021
Automatically detecting bugs in student program code is critical to enable formative feedback to help students pinpoint errors and resolve them. Deep learning models especially code2vec and ASTNN have shown great success for "large-scale" code classification. It is not clear, however, whether they can be effectively used for bug…
Descriptors: Artificial Intelligence, Program Effectiveness, Coding, Computer Science Education
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Maertens, Rien; Van Petegem, Charlotte; Strijbol, Niko; Baeyens, Toon; Jacobs, Arne Carla; Dawyndt, Peter; Mesuere, Bart – Journal of Computer Assisted Learning, 2022
Background: Learning to code is increasingly embedded in secondary and higher education curricula, where solving programming exercises plays an important role in the learning process and in formative and summative assessment. Unfortunately, students admit that copying code from each other is a common practice and teachers indicate they rarely use…
Descriptors: Plagiarism, Benchmarking, Coding, Computer Science Education
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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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Tsabari, Stav; Segal, Avi; Gal, Kobi – International Educational Data Mining Society, 2023
Automatically identifying struggling students learning to program can assist teachers in providing timely and focused help. This work presents a new deep-learning language model for predicting "bug-fix-time", the expected duration between when a software bug occurs and the time it will be fixed by the student. Such information can guide…
Descriptors: College Students, Computer Science Education, Programming, Error Patterns