Towards a Machine Learning flow-predicting model in a MOOC context
| العنوان: | Towards a Machine Learning flow-predicting model in a MOOC context |
|---|---|
| المؤلفون: | Sergio Ramírez Luelmo, Nour El Mawas, Rémi Bachelet, Jean Heutte |
| المساهمون: | Trigone-CIREL, Centre Interuniversitaire de Recherche en Education de Lille - ULR 4354 (CIREL), Université de Lille-Université de Lille, Centrale Lille |
| المصدر: | 14th International Conference on Computer Supported Education (CSEDU 2022) 14th International Conference on Computer Supported Education (CSEDU 2022), Apr 2022, Online Streaming, United Kingdom |
| بيانات النشر: | HAL CCSD, 2022. |
| سنة النشر: | 2022 |
| مصطلحات موضوعية: | Machine Learning, Flow, [SHS.EDU]Humanities and Social Sciences/Education, Autotelic experience, [SHS.PSY]Humanities and Social Sciences/Psychology, MOOC, Logistic Regression |
| الوصف: | International audience; Flow is a human psychological state positively correlated to self-efficacy, motivation, engagement, and academic achievement, all of which positively affect learning. However, automatic, real-time flow prediction is quite difficult, particularly in a Massively Online Open Course context, even more so because of its online, distant, asynchronous, and educational components. In such context, flow prediction allows for personalization of activities, content, and learning-paths. By pairing the results of the EduFlow2 and Flow-Q questionnaires (n = 1589, two years data collection) from the French MOOC “Gestion de Projet” (Project Management) to Machine Learning techniques (Logistic Regression), we create a Machine Learning model that successfully predicts flow (combined Accuracy & Precision ~ 0.8, AUC = 0.85) in an automatic, asynchronous fashion, in a MOOC context. The resulting Machine Learning model predicts the presence of flow (0.82) with a greater Precision than it predicts its absence (0.74). |
| اللغة: | English |
| URL الوصول: | https://explore.openaire.eu/search/publication?articleId=doi_dedup___::a1256402d69a6edf92e39ae92e051d98 https://halshs.archives-ouvertes.fr/halshs-03606527 |
| رقم الانضمام: | edsair.doi.dedup.....a1256402d69a6edf92e39ae92e051d98 |
| قاعدة البيانات: | OpenAIRE |
| الوصف غير متاح. |