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research-article

A recommender agent based on learning styles for better virtual collaborative learning experiences

Authors:

Maria-Iuliana Dascalu,

Constanta-Nicoleta Bodea,

Alin Moldoveanu,

Miltiadis Lytras,

Patricia Ordoñez de PablosAuthors Info & Claims

Computers in Human Behavior, Volume 45, Issue C

Pages 243 - 253

https://doi.org/10.1016/j.chb.2014.12.027

Published: 01 April 2015 Publication History

Abstract

We developed an educational collaborative filtering recommender agent.We propose a recommendation method for educational materials and tools.Our recommender agent has an integrated learning style finder.The agent produces two types of recommendations: suggestions and shortcuts.The recommender is integrated into a virtual collaborative learning environment. Almost unlimited access to educational information plethora came with a drawback: finding meaningful material is not a straightforward task anymore. Based on a survey related to how students find additional bibliographical resources for university courses, we concluded there is a strong need for recommended learning materials, for specialized online search and for personalized learning tools. As a result, we developed an educational collaborative filtering recommender agent, with an integrated learning style finder. The agent produces two types of recommendations: suggestions and shortcuts for learning materials and learning tools, helping the learner to better navigate through educational resources. Shortcuts are created taking into account only the user's profile, while suggestions are created using the choices made by the learners with similar learning styles. The learning style finder assigns to each user a profile model, taking into account an index of learning styles, as well as patterns discovered in the virtual behavior of the user. The current study presents the agent itself, as well as its integration to a virtual collaborative learning environment and its success and limitations, based on users' feedback.

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Cited By

Han X(2022)Recommendation Algorithm of Web-Based Learning Resources considering Timeliness and PopularityAdvances in Multimedia10.1155/2022/25848902022Online publication date: 1-Jan-2022
https://dl.acm.org/doi/10.1155/2022/2584890
Eryilmaz EThoms BAhmed ZLee K(2021)Effects of recommendations on message quality and community formation in online conversationsEducation and Information Technologies10.1007/s10639-020-10364-426:1(49-68)Online publication date: 1-Jan-2021
https://dl.acm.org/doi/10.1007/s10639-020-10364-4
Intayoad WKamyod CTemdee P(2020)Reinforcement Learning Based on Contextual Bandits for Personalized Online Learning Recommendation SystemsWireless Personal Communications: An International Journal10.1007/s11277-020-07199-0115:4(2917-2932)Online publication date: 1-Dec-2020
https://dl.acm.org/doi/10.1007/s11277-020-07199-0
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A recommender agent based on learning styles for better virtual collaborative learning experiences
1. Applied computing

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cover image Computers in Human Behavior

Computers in Human Behavior Volume 45, Issue C

April 2015

421 pages

ISSN:0747-5632

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Copyright © Elsevier Ltd.

Publisher

Elsevier Science Publishers B. V.

Netherlands

Publication History

Published: 01 April 2015

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Cited By

Han X(2022)Recommendation Algorithm of Web-Based Learning Resources considering Timeliness and PopularityAdvances in Multimedia10.1155/2022/25848902022Online publication date: 1-Jan-2022
https://dl.acm.org/doi/10.1155/2022/2584890
Eryilmaz EThoms BAhmed ZLee K(2021)Effects of recommendations on message quality and community formation in online conversationsEducation and Information Technologies10.1007/s10639-020-10364-426:1(49-68)Online publication date: 1-Jan-2021
https://dl.acm.org/doi/10.1007/s10639-020-10364-4
Intayoad WKamyod CTemdee P(2020)Reinforcement Learning Based on Contextual Bandits for Personalized Online Learning Recommendation SystemsWireless Personal Communications: An International Journal10.1007/s11277-020-07199-0115:4(2917-2932)Online publication date: 1-Dec-2020
https://dl.acm.org/doi/10.1007/s11277-020-07199-0
Hasanov ALaine TChung T(2019)A survey of adaptive context-aware learning environmentsJournal of Ambient Intelligence and Smart Environments10.3233/AIS-19053411:5(403-428)Online publication date: 1-Jan-2019
https://dl.acm.org/doi/10.3233/AIS-190534
(2018)A study on computing and e-learning in the perspective of distributed modelsInternational Journal of Grid and Utility Computing10.1504/IJGUC.2018.0939859:3(243-255)Online publication date: 1-Jan-2018
https://dl.acm.org/doi/10.1504/IJGUC.2018.093985
Sha JChen K(2017)Analysis of Technology Enhancing Knowledge Sharing in Learning CommunitiesProceedings of the 9th International Conference on Education Technology and Computers10.1145/3175536.3175552(22-26)Online publication date: 20-Dec-2017
https://dl.acm.org/doi/10.1145/3175536.3175552
Bertoncello VPossamai OBortolozzi FVosgerau D(2017)A Model for the Development of Learning Objects Using Educational DesignProceedings of the 2017 International Conference on Information System and Data Mining10.1145/3077584.3077611(111-118)Online publication date: 1-Apr-2017
https://dl.acm.org/doi/10.1145/3077584.3077611
Huptych MBohuslavek MHlosta MZdrahal ZWise AWinne PLynch GOchoa XMolenaar IDawson SHatala M(2017)Measures for recommendations based on past students' activityProceedings of the Seventh International Learning Analytics & Knowledge Conference10.1145/3027385.3027426(404-408)Online publication date: 13-Mar-2017
https://dl.acm.org/doi/10.1145/3027385.3027426
Dascalu MBodea CTesila BMoldoveanu AOrdoez de Pablos P(2017)How social and semantic technologies can sustain employability through knowledge development and positive behavioral changesComputers in Human Behavior10.1016/j.chb.2017.01.02670:C(507-517)Online publication date: 1-May-2017
https://dl.acm.org/doi/10.1016/j.chb.2017.01.026
(2016)A new approach for the recommendation of relevant learners in CSCL systemsInternational Journal of Technology Enhanced Learning10.5555/3059242.30592458:3-4(234-252)Online publication date: 1-Jan-2016
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