Investigating Influence of Demographic Factors on Study Recommenders

Huptych, Michal; Hlosta, Martin; Zdrahal, Zdenek and Kocvara, Jakub (2018). Investigating Influence of Demographic Factors on Study Recommenders. In: Artificial Intelligence in Education (Rosé, Carolyn Penstein; Martínez-Maldonado, Roberto; Hoppe, H. Ulrich; Luckin, Rose; Mavrikis, Manolis; Porayska-Pomsta, Kaska; McLaren, Bruce and du Boulay, Benedict eds.), Lecture Notes in Artificial Intelligence, Springer, Cham, pp. 150–154.



Recommender systems in e-learning platforms, can utilise various data about learners in order to provide them with the next best material to study. We build on our previous work, which defines the recommendations in terms of two measures (i.e. relevance and effort) calculated from data of successful students in the previous runs of the courses. In this paper we investigate the impact of students’ socio-demographic factors and analyse how these factors improved the recommendation. It has been shown that education and age were found to have a significant impact on engagement with materials.

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