AI RESEARCH
Investigating the Effects of Different Levels of User Control in an Interactive Educational Recommender System
arXiv CS.AI
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ArXi:2605.01400v1 Announce Type: cross Educational recommender systems (ERSs) are becoming increasingly important in enhancing educational outcomes and personalizing learning experiences by providing recommendations of personalized resources and activities to learners, tailored to their individual learning needs. While user control is widely assumed to improve user experience, the effects of different levels of control in ERSs remain underexplored. To address this gap, we designed and evaluated an interactive ERS within the MOOC platform.