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Agus Santoso; Heri Retnawati; Kartianom; Ezi Apino; Ibnu Rafi; Munaya Nikma Rosyada – Open Education Studies, 2024
The world's move to a global economy has an impact on the high rate of student academic failure. Higher education, as the affected party, is considered crucial in reducing student academic failure. This study aims to construct a prediction (predictive model) that can forecast students' time to graduation in developing countries such as Indonesia,…
Descriptors: Time to Degree, Open Universities, Foreign Countries, Predictive Measurement
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Jialun Pan; Zhanzhan Zhao; Dongkun Han – IEEE Transactions on Learning Technologies, 2025
Properly predicting students' academic performance is crucial for elevating educational outcomes in various disciplines. Through precise performance prediction, schools can quickly pinpoint students facing challenges and provide customized educational materials suited to their specific learning needs. The reliance on teachers' experience to…
Descriptors: Prediction, Academic Achievement, At Risk Students, Artificial Intelligence
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John Pace; John Hansen; John Stewart – Physical Review Physics Education Research, 2024
Machine learning models were constructed to predict student performance in an introductory mechanics class at a large land-grant university in the United States using data from 2061 students. Students were classified as either being at risk of failing the course (earning a D or F) or not at risk (earning an A, B, or C). The models focused on…
Descriptors: Artificial Intelligence, Identification, At Risk Students, Physics