Which Recommender System Can Best Fit Social Learning Platforms?

Soude Fazeli, Babak Loni, Hendrik Drachsler, Peter Sloep

    Research output: Chapter in Book/Report/Conference proceedingConference article in proceedingAcademicpeer-review

    Abstract

    This study aims to develop a recommender system for social learning platforms that combine traditional learning management systems with commercial social networks like Facebook. We therefore take into account social interactions of users to make recommendations on learning resources. We propose to make use of graph-walking methods for improving performance of the well-known baseline algorithms. We evaluate the proposed graph-based approach in terms of their F1 score, which is an effective combination of precision and recall as two fundamental metrics used in recommender systems area. The results show that the graph-based approach can help to improve performance of the baseline recommenders; particularly for rather sparse educational datasets used in this study.
    Original languageEnglish
    Title of host publicationOpen Learning and Teaching in Educational Communities
    Subtitle of host publication9th European Conference on Technology Enhanced Learning, EC-TEL 2014, Graz, Austria, September 16-19, 2014, Proceedings
    EditorsChristoph Rensing, Sara de Freitas, Tobias Ley, Pedro J. Muñoz-Merino
    Place of PublicationCham, Switzerland
    PublisherSpringer
    Pages84-97
    Number of pages14
    ISBN (Electronic)978-3-319-11200-8
    ISBN (Print)978-3-319-11199-5
    DOIs
    Publication statusPublished - 2014
    Event9th European Conference on Technology Enhanced Learning: Open Learning and Teaching in Educational Communities - Graz, Austria
    Duration: 16 Sep 201419 Sep 2014
    Conference number: 9
    http://ectel2014.httc.de/index.php?id=681

    Publication series

    SeriesLecture Notes in Computer Science (LNCS)
    Volume8719
    ISSN0302-9743

    Conference

    Conference9th European Conference on Technology Enhanced Learning
    Abbreviated titleEC-TEL 2014
    Country/TerritoryAustria
    CityGraz
    Period16/09/1419/09/14
    Internet address

    Keywords

    • recommender system
    • social
    • learning
    • collaborative filtering
    • teacher
    • graph
    • similarity
    • performance
    • social learning platform
    • sparsity

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