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Milos Ilic; Goran Kekovic; Vladimir Mikic; Katerina Mangaroska; Lazar Kopanja; Boban Vesin – IEEE Transactions on Learning Technologies, 2024
In recent years, there has been an increasing trend of utilizing artificial intelligence (AI) methodologies over traditional statistical methods for predicting student performance in e-learning contexts. Notably, many researchers have adopted AI techniques without conducting a comprehensive investigation into the most appropriate and accurate…
Descriptors: Artificial Intelligence, Academic Achievement, Prediction, Programming
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Marwan, Samiha; Price, Thomas W. – IEEE Transactions on Learning Technologies, 2023
Novice programmers often struggle on assignments, and timely help, such as a hint on what to do next, can help students continue to progress and learn, rather than giving up. However, in large programming classrooms, it is hard for instructors to provide such real-time support for every student. Researchers have, therefore, put tremendous effort…
Descriptors: Data Use, Cues, Programming, Computer Science Education
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Malliarakis, Christos; Satratzemi, Maya; Xinogalos, Stelios – IEEE Transactions on Learning Technologies, 2017
Computer programming has for decades posed several difficulties for students of all educational levels. A number of teaching approaches have been proposed over the years but none seems to fulfil the needs of students nowadays. Students use computers mainly for playing games and the Internet and as quite a few researchers state this aspect of…
Descriptors: Computer Games, Computer Science Education, Programming, Instructional Effectiveness