Evaluating Teachers’ Perceptions of Learning Design Recommender Systems

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Abstract

Nowadays, researchers in the field of Learning Design are investigating ways to assist teachers in realizing their role as Learning Designers in the context of online and blended learning. This is a major quest for the field researchers due to the fact that it can affect the broader adoption of the Learning Design practices by teachers, with resulting improvements on the quality of teaching and learning outcomes. In this context, this paper investigates teacher-perceived experience and acceptance of a Recommender System (RS) that supports teachers in the designing process, by providing them with Learning Design recommendations. To this end, we conducted a user-centric evaluation experiment, which involved 50 teachers and was based on the ResQue model. According to the results, an RS which proposes existing Learning Designs is a highly accepted technology by teachers. Additionally, teachers believe that the use of the proposed RS can make the designing process easier and faster while it would also favor the sharing of good teaching practices and provide teachers with a valuable source of inspiration. The implications of this study suggest that developers in the Learning Design field should incorporate RSs into existing Learning Design environments in order to facilitate the designing process.

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Karga, S., & Satratzemi, M. (2019). Evaluating Teachers’ Perceptions of Learning Design Recommender Systems. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 11722 LNCS, pp. 98–111). Springer Verlag. https://doi.org/10.1007/978-3-030-29736-7_8

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