Students' Expectations of Learning Analytics Features

• In Event: 30.057 - Learning Analytics and Data Mining to Improve Student Learning and Teacher Professional Development

Abstract

In higher education settings more and more learning takes place in online learning environments. To support and understand students’ (self-regulated) learning processes better, learning analytics provides a promising approach. The purpose of this exploratory qualitative study was to investigate students’ expectations towards features of learning analytics systems. A total of 20 university students participated in the present study. They were given an introduction on learning analytics systems before being interviewed about their expectations of learning analytics features. Findings show that students expect learning analytics features, which support their planning and organizing of learning processes, facilitate self-assessment, give suitable learning recommendations and show analyses of their learning activities.

Authors

• Clara Schumacher, University of Mannheim

• Dirk Ifenthaler, University of Mannheim