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Abdullahi Yusuf; Amiru Yusuf Muhammad – Journal of Educational Computing Research, 2024
The study investigates the potential of anxiety clusters in predicting programming performance in two distinct coding environments. Participants comprised 83 second-year programming students who were randomly assigned to either a block-based or a text-based group. Anxiety-induced behaviors were assessed using physiological measures (Apple Watch…
Descriptors: Novices, Programming, Anxiety, Coding
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Linjing Wu; Xuelin Xiang; Xueyan Yang; Xuan Jin; Liang Chen; Qingtang Liu – Educational Technology Research and Development, 2025
Problem-solving strategies are crucial in learning programming. Owing to their hidden nature, traditional methods such as interviews and questionnaires cannot reflect the details and differences of problem-solving strategies in programming. This study uses the Hidden Markov Model to detect and compare the problem-solving strategies of different…
Descriptors: Markov Processes, Problem Solving, Programming, Identification
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Lokkila, Erno; Christopoulos, Athanasios; Laakso, Mikko-Jussi – Informatics in Education, 2023
Prior programming knowledge of students has a major impact on introductory programming courses. Those with prior experience often seem to breeze through the course. Those without prior experience see others breeze through the course and disengage from the material or drop out. The purpose of this study is to demonstrate that novice student…
Descriptors: Prior Learning, Programming, Computer Science Education, Markov Processes
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Lavbic, Dejan; Matek, Tadej; Zrnec, Aljaž – Interactive Learning Environments, 2017
Today's software industry requires individuals who are proficient in as many programming languages as possible. Structured query language (SQL), as an adopted standard, is no exception, as it is the most widely used query language to retrieve and manipulate data. However, the process of learning SQL turns out to be challenging. The need for a…
Descriptors: Evaluation Methods, Information Systems, Intelligent Tutoring Systems, Computer Science Education
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Feng, Mingyu, Ed.; Käser, Tanja, Ed.; Talukdar, Partha, Ed. – International Educational Data Mining Society, 2023
The Indian Institute of Science is proud to host the fully in-person sixteenth iteration of the International Conference on Educational Data Mining (EDM) during July 11-14, 2023. EDM is the annual flagship conference of the International Educational Data Mining Society. The theme of this year's conference is "Educational data mining for…
Descriptors: Information Retrieval, Data Analysis, Computer Assisted Testing, Cheating
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Lynch, Collin F., Ed.; Merceron, Agathe, Ed.; Desmarais, Michel, Ed.; Nkambou, Roger, Ed. – International Educational Data Mining Society, 2019
The 12th iteration of the International Conference on Educational Data Mining (EDM 2019) is organized under the auspices of the International Educational Data Mining Society in Montreal, Canada. The theme of this year's conference is EDM in Open-Ended Domains. As EDM has matured it has increasingly been applied to open-ended and ill-defined tasks…
Descriptors: Data Collection, Data Analysis, Information Retrieval, Content Analysis