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2018 | OriginalPaper | Buchkapitel

Proposal of a Recommendation System for Complex Topic Learning Based on a Sustainable Design Approach

verfasst von : Xanat Vargas Meza, Toshimasa Yamanaka

Erschienen in: Computational Collective Intelligence

Verlag: Springer International Publishing

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Abstract

There are several issues compromising the educational role of social networks, particularly in the case of video based online content. Among them, individual (cognitive and emotional), social (privacy and ethics) and structural (algorithmic bias) challenges can be found. To cope with such issues, we propose a recommendation system for online video content, applying principles of sustainable design. Precision and recall in English were slightly lower for the system in comparison to YouTube, but the variety of recommended items increased; while in Spanish, precision and recall were higher. Expected results include fostering learning and adoption of complex thinking by taking on account a user’s objective and subjective context.

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Titel: Proposal of a Recommendation System for Complex Topic Learning Based on a Sustainable Design Approach
verfasst von: Xanat Vargas Meza
Toshimasa Yamanaka
Verlag: Springer International Publishing
Buch: Computational Collective Intelligence
Print ISBN: 978-3-319-98442-1

Electronic ISBN: 978-3-319-98443-8

Copyright-Jahr: 2018
DOI: https://doi.org/10.1007/978-3-319-98443-8_24

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