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International Conference on Computational Collective Intelligence

ICCCI 2018: Computational Collective Intelligence pp 260–269Cite as

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

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Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 11055))

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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Acknowledgements

The authors wish to thank Akio Sakai, Alejandra Vilaplana, Anna Bogdanova, Eiji Onchi, Emika Okumura, Felix Dollack, Gustavo Ruiz, Imme Arce, Marusia Flores, Nikos Fragkiadakis, Shane Williamson, Suomiya Bao, and our reviewers for their contributions. This paper was written with the support of the Rotary Yoneyama Scholarship Foundation.

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Authors and Affiliations

  1. The University of Tsukuba, Tsukuba, Japan

    Xanat Vargas Meza & Toshimasa Yamanaka

Authors
  1. Xanat Vargas Meza
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  2. Toshimasa Yamanaka
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Corresponding author

Correspondence to Xanat Vargas Meza .

Editor information

Editors and Affiliations

  1. Faculty of Information Technology, Ton Duc Thang University, Ho Chi Minh City, Vietnam

    Ngoc Thanh Nguyen

  2. Department of Computer Science and Creative Technologies, University of the West of England, Bristol, United Kingdom

    Elias Pimenidis

  3. Department of Computer Science and Creative Technologies, University of the West of England, Bristol, United Kingdom

    Zaheer Khan

  4. Faculty of Computer Science and Management, Wrocław University of Science and Technology, Wrocław, Poland

    Bogdan Trawiński

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Meza, X.V., Yamanaka, T. (2018). Proposal of a Recommendation System for Complex Topic Learning Based on a Sustainable Design Approach. In: Nguyen, N., Pimenidis, E., Khan, Z., Trawiński, B. (eds) Computational Collective Intelligence. ICCCI 2018. Lecture Notes in Computer Science(), vol 11055. Springer, Cham. https://doi.org/10.1007/978-3-319-98443-8_24

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  • DOI: https://doi.org/10.1007/978-3-319-98443-8_24

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-98442-1

  • Online ISBN: 978-3-319-98443-8

  • eBook Packages: Computer ScienceComputer Science (R0)

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