Designing and Evaluating an Educational Recommender System with Different Levels of User Control
Qurat Ul Ain, Mohamed Amine Chatti, William Kana Tsoplefack and, Rawaa Alatrash, Shoeb Joarder

TL;DR
This paper systematically designs and evaluates an educational recommender system with varying levels of user control, demonstrating that increased control enhances transparency, trust, and satisfaction among users.
Contribution
It introduces multiple levels of user control in ERS design and empirically evaluates their impact on user perceptions and recommendation goals.
Findings
User control positively affects perceived benefits of ERS.
Transparency strongly correlates with trust and satisfaction.
Trust has a strong correlation with user satisfaction.
Abstract
Educational recommender systems (ERSs) play a crucial role in personalizing learning experiences and enhancing educational outcomes by providing recommendations of personalized resources and activities to learners, tailored to their individual learning needs. However, their effectiveness is often diminished by insufficient user control and limited transparency. To address these challenges, in this paper, we present the systematic design and evaluation of an interactive ERS, in which we introduce different levels of user control. Concretely, we introduce user control around the input (i.e., user profile), process (i.e., recommendation algorithm), and output (i.e., recommendations) of the ERS. To evaluate our system, we conducted an online user study (N=30) to explore the impact of user control on users' perceptions of the ERS in terms of several important user-centric aspects. Moreover,…
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Taxonomy
TopicsRecommender Systems and Techniques · Intelligent Tutoring Systems and Adaptive Learning · Online Learning and Analytics
