Investigating Influence of Demographic Factors on Study Recommenders

  • Michal Huptych
  • Martin HlostaEmail author
  • Zdenek Zdrahal
  • Jakub Kocvara
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 10948)


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.


Personalised learning Educational recommender systems 


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Copyright information

© Springer International Publishing AG, part of Springer Nature 2018

Authors and Affiliations

  • Michal Huptych
    • 1
    • 2
  • Martin Hlosta
    • 1
    Email author
  • Zdenek Zdrahal
    • 1
    • 2
  • Jakub Kocvara
    • 1
  1. 1.Knowledge Media InstituteThe Open UniversityMilton KeynesUK
  2. 2.CIIRCCzech Technical University in PraguePragueCzech Republic

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