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Download full textRohani, Narjes; Gal, Kobi; Gallagher, Michael; Manataki, Areti – International Educational Data Mining Society, 2023
Massive Open Online Courses (MOOCs) make high-quality learning accessible to students from all over the world. On the other hand, they are known to exhibit low student performance and high dropout rates. Early prediction of student performance in MOOCs can help teachers intervene in time in order to improve learners' future performance. This is…
Descriptors: Prediction, Academic Achievement, Health Education, Data Science
Direct linkBui, Ngoc Van P. – ProQuest LLC, 2022
This research explores the use of eXplainable Artificial Intelligence (XAI) in Educational Data Mining (EDM) to improve the performance and explainability of artificial intelligence (AI) and machine learning (ML) models predicting at-risk students. Explainable predictions provide students and educators with more insight into at-risk indicators and…
Descriptors: Artificial Intelligence, At Risk Students, Prediction, Data Science
