Panorama of Recommender Systems to Support Learning

Hendrik Drachsler, Katrien Verbert, Olga C. Santos, Nikos Manouselis

    Research output: Chapter in Book/Report/Conference proceedingChapterAcademicpeer-review

    Abstract

    This chapter presents an analysis of recommender systems in TechnologyEnhanced Learning along their 15 years existence (2000-2014). All recommender systems considered for the review aim to support educational stakeholders by personalising the learning process. In this meta-review 82 recommender systems from 35 different countries have been investigated and categorised according to a given classification framework. The reviewed systems have been classified into 7 clusters according to their characteristics and analysed for their contribution to the evolution of the RecSysTEL research field. Current challenges have been identified to lead the work of the forthcoming years.
    Original languageEnglish
    Title of host publicationRecommender Systems Handbook
    EditorsFrancesco Ricci, Lior Rokach, Bracha Shapira
    Place of PublicationBoston, MA
    PublisherSpringer
    Pages421-451
    Number of pages31
    Edition2
    ISBN (Electronic)978-1-4899-7637-6
    ISBN (Print)978-1--4899-7636-9
    DOIs
    Publication statusPublished - 14 Dec 2015

    Keywords

    • recommender systems
    • learning
    • Technology enhanced learning
    • Classification framework
    • State-of-the-art
    • review
    • Educational datasets
    • Learning Analytics
    • Educational data mining
    • Trend analysis
    • Personalisation
    • Future challenges

    Fingerprint

    Dive into the research topics of 'Panorama of Recommender Systems to Support Learning'. Together they form a unique fingerprint.

    Cite this