A decade later: Students’ privacy perceptions of learning analytics

• In Event: Future-Oriented Dialogues on AI in Education

Abstract

This study examines students’ perceptions and willingness to share data within learning analytics (LA) systems. A within-subject online design was employed with N = 369 participants who viewed video vignettes of three LA systems: descriptive, predictive, and prescriptive. Findings reveal that descriptive and prescriptive systems are perceived more favorably than the predictive system; however, overall willingness to share personal data remains low, especially for intrusive measures such as emotion detection and gaze tracking. Additionally, higher perceived control is correlated with increased acceptance of LA tools. These insights inform strategies for designing privacy-sensitive LA systems that balance functionality with student trust and engagement.

Authors

• Clara Schumacher, University of Potsdam

• Dirk Ifenthaler, University of Mannheim