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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.

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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.

Item Type: Conference or Workshop Item
Copyright Holders: 2018 Springer International Publishing AG
ISBN: 3-319-93845-2, 978-3-319-93845-5
ISSN: 0302-9743
Keywords: personalised learning; educational recommender systems
Academic Unit/School: Faculty of Science, Technology, Engineering and Mathematics (STEM) > Knowledge Media Institute (KMi)
Faculty of Science, Technology, Engineering and Mathematics (STEM)
Item ID: 56293
Depositing User: Kay Dave
Date Deposited: 10 Sep 2018 09:38
Last Modified: 02 May 2019 06:12
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