This study aims at providing explanations of students’ behaviors on LMS by incorporating dispositional dimensions (e.g., self-regulation and emotions) into conventional learning analytics models. Using a combination of demographic, trace, and self-reported data.
The Inspire plugin implements open source, transparent next-generation learning analytics using machine learning backends that go beyond simple descriptive analytics to provide predictions of learner success, and ultimately diagnosis and prescriptions (advisements) to learners and teachers. From Moodle HQ.
Should students be told what the data predict about their chances of success? Corporate leaders in predictive analytics business consider the issue posed by an Inside Higher Ed blogger.
Durch digitale Lernplattformen können vermehrt Daten über Lernende, Lerninhalte und die Lernsituation ausgewertet werden. Die algorithmische Analyse nennt sich Learning Analytics. Diese Analyse ermöglicht einen individuellen Lernprozess sowie eine Früherkennung von Lernschwächen. Learning Analytics bergen allerdings auch einige Nachteile.
W. Li, C. Brooks, and F. Schaub. Proceedings of the 9th International Conference on Learning Analytics & Knowledge, page 411--420. New York, NY, USA, ACM, (2019)