Data is sometimes seen as something cold and removed from the human element, but in reality, it is a window into that very humanity, and can form an essential foundation for keeping students on track.
The Experience API (xAPI for short) is far more than just an update to SCORM, the popular standard for tracking data from a learning management system. xAPI opens up a whole new world of possibilities for learning analytics. Examples of what real organizations are doing with it in real-life situations make it easier to grasp the scale of this advance and apply the learnings to your own situation.
As part of a Title III federal grant awarded to Bay Path University, the institution has planned to create a predictive model for traditional undergraduate persistence and another for financial aid warning flags. This is final installment in a series of posts that follow the steps in the CRISP-DM framework on our journey to produce the former.
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, und F. Schaub. Proceedings of the 9th International Conference on Learning Analytics & Knowledge, Seite 411--420. New York, NY, USA, ACM, (2019)