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Urgency Analysis of Learners' Comments: An Automated Intervention Priority Model for MOOC.

, , , and . ITS, volume 12677 of Lecture Notes in Computer Science, page 148-160. Springer, (2021)

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Automatic Subject-based Contextualisation of Programming Assignment Lists., , , , , and . EDM, International Educational Data Mining Society, (2020)A Recommendation System for Nurturing Students' Sense of Belonging., , , , , and . AIED (Posters/Late Breaking Results/...), volume 1831 of Communications in Computer and Information Science, page 130-135. Springer, (2023)MOOC Next Week Dropout Prediction: Weekly Assessing Time and Learning Patterns., , , , and . ITS, volume 12677 of Lecture Notes in Computer Science, page 119-130. Springer, (2021)Urgency Analysis of Learners' Comments: An Automated Intervention Priority Model for MOOC., , , and . ITS, volume 12677 of Lecture Notes in Computer Science, page 148-160. Springer, (2021)Towards a Human-AI Hybrid System for Categorising Programming Problems., , , , , , and . SIGCSE, page 94-100. ACM, (2021)Education in the age of Generative AI: Context and Recent Developments., , , , , and . CoRR, (2023)Serendipitous Gains of Explaining a Classifier - Artificial versus Human Performance and Annotator Support in an Urgent Instructor-Intervention Model for MOOCs., , , and . HUMAN@HT, page 3:1-3:7. ACM, (2023)Extracting the Language of the Need for Urgent Intervention in MOOCs by Analysing Text Posts., , , and . ICWL, volume 13869 of Lecture Notes in Computer Science, page 161-173. Springer, (2022)The engage taxonomy: SDT-based measurable engagement indicators for MOOCs and their evaluation., , , , , , and . User Model. User Adapt. Interact., 34 (2): 323-374 (April 2024)Explaining Individual and Collective Programming Students' Behavior by Interpreting a Black-Box Predictive Model., , , , , , , , and . IEEE Access, (2021)