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Predicting MOOCs Dropout Using Only Two Easily Obtainable Features from the First Week's Activities.

, , , , , , and . ITS, volume 11528 of Lecture Notes in Computer Science, page 163-173. Springer, (2019)

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Towards Designing Profitable Courses: Predicting Student Purchasing Behaviour in MOOCs., , , and . Int. J. Artif. Intell. Educ., 31 (2): 215-233 (2021)Earliest Predictor of Dropout in MOOCs: A Longitudinal Study of FutureLearn courses., , , , , and . ISD, Lund University / Association for Information Systems, (2018)Predicting MOOCs Dropout Using Only Two Easily Obtainable Features from the First Week's Activities., , , , , , and . ITS, volume 11528 of Lecture Notes in Computer Science, page 163-173. Springer, (2019)On the Need for Fine-Grained Analysis of Gender Versus Commenting Behaviour in MOOCs., , , , , , and . ICIEI, page 73-77. ACM, (2018)How is Learning Fluctuating? FutureLearn MOOCs Fine-Grained Temporal Analysis and Feedback to Teachers., , , , , and . ISD, Lund University / Association for Information Systems, (2018)Can learner characteristics predict their behaviour on MOOCs?, , , , , , and . ICETC, page 119-128. ACM, (2018)Context Unlocks Emotions: Text-based Emotion Classification Dataset Auditing with Large Language Models., , , , , , and . ACII, page 1-8. IEEE, (2023)MOOCRev: A Large-Scale Data Repository for Course Reviews., , , , , , , and . AIED Companion (2), volume 2151 of Communications in Computer and Information Science, page 124-131. Springer, (2024)Early Dropout Prediction for Programming Courses Supported by Online Judges., , , , , , , and . AIED (2), volume 11626 of Lecture Notes in Computer Science, page 67-72. Springer, (2019)Adopting Automatic Machine Learning for Temporal Prediction of Paid Certification in MOOCs., , and . AIED (1), volume 13355 of Lecture Notes in Computer Science, page 717-723. Springer, (2022)