article

A hybrid recommender system integrated into LAMS for learning designers

Authors:

Soultana Karga,

Maya SatratzemiAuthors Info & Claims

Education and Information Technologies, Volume 23, Issue 3

Pages 1297 - 1329

https://doi.org/10.1007/s10639-017-9668-0

Published: 01 May 2018 Publication History

Abstract

In the constantly evolving field of e-learning, the Learning Design (LD) sector constitutes a critical success factor, as it has the potential to preserve and disseminate effective pedagogical approaches and enhance the quality of the educational process. Recognizing the LD process as demanding in terms of time and expertise this paper answers the research question of how to leverage Recommender Systems (RSs) and reuse pre-existing LD solutions in order to support teachers in the LD process. In particular, this paper presents the implementation and the first evaluation results of Mentor. Mentor is an RS that supports teachers in finding pre-existing LDs, which cater better for their needs and preferences, so as to re-design them. Mentor is integrated into LAMS, which is a well-known tool for designing, managing and delivering sequences of learning activities. The first user-centric evaluation experiment results are presented and confirm the underlying assumption that Mentor can facilitate teachers in the LD process. Further results concerning the user's general perception and the perceived usefulness of Mentor are discussed.

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Education and Information Technologies Volume 23, Issue 3

May 2018

409 pages

ISSN:1360-2357

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Pham APham C(2022)Students’ Perceptions towards Hybrid Learning during the Covid-19 PandemicProceedings of the 6th International Conference on Digital Technology in Education10.1145/3568739.3568744(25-30)Online publication date: 16-Sep-2022
https://dl.acm.org/doi/10.1145/3568739.3568744
Jeevamol JRenumol V(2021)An ontology-based hybrid e-learning content recommender system for alleviating the cold-start problemEducation and Information Technologies10.1007/s10639-021-10508-026:4(4993-5022)Online publication date: 1-Jul-2021
https://dl.acm.org/doi/10.1007/s10639-021-10508-0
Sebbaq Hel Faddouli NBennani S(2020)Recommender System to Support MOOCs TeachersProceedings of the 13th International Conference on Intelligent Systems: Theories and Applications10.1145/3419604.3419619(1-7)Online publication date: 23-Sep-2020
https://dl.acm.org/doi/10.1145/3419604.3419619
Karga SSatratzemi M(2019)Using explanations for recommender systems in learning design settings to enhance teachers’ acceptance and perceived experienceEducation and Information Technologies10.1007/s10639-019-09909-z24:5(2953-2974)Online publication date: 1-Sep-2019
https://dl.acm.org/doi/10.1007/s10639-019-09909-z
Karga SSatratzemi M(2019)Evaluating Teachers’ Perceptions of Learning Design Recommender SystemsTransforming Learning with Meaningful Technologies10.1007/978-3-030-29736-7_8(98-111)Online publication date: 16-Sep-2019
https://dl.acm.org/doi/10.1007/978-3-030-29736-7_8

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