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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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SEE Prediction: Construction of a L-based Energy Function., and . NC, page 841-847. ICSC Academic Press, International Computer Science Conventions, Canada / Switzerland, (1998)A Layered Approach towards Domain Authoring support., , and . IC-AI, page 615-621. CSREA Press, (2002)What’s new? Analysing language-specific Wikipedia entity contexts to support entity-centric news retrieval., , and . Transactions on Computational Collective Intelligence, TCCI XXVI, (June 2017)Energy function construction and implementation for stock exchange prediction NNs., and . KES (3), page 403-410. IEEE, (1998)Combining Heterogeneous User Generated Data to Sense Well-being., , , , , and . COLING, page 3007-3018. ACL, (2016)Immersion in e-Learning.. HT (Extended Proceedings), volume 1914 of CEUR Workshop Proceedings, CEUR-WS.org, (2017)Twitter Analysis to Predict the Satisfaction of Telecom Company Customers., and . HT (Extended Proceedings), volume 1628 of CEUR Workshop Proceedings, CEUR-WS.org, (2016)INTERACTION: A Generative XAI Framework for Natural Language Inference Explanations., , , , , , and . IJCNN, page 1-8. IEEE, (2022)On the Need for Fine-Grained Analysis of Gender Versus Commenting Behaviour in MOOCs., , , , , , and . ICIEI, page 73-77. ACM, (2018)The LAG Grammar for Authoring the Adaptive Web., and . ITCC (1), page 382-288. IEEE Computer Society, (2004)