A Video Recommendation System for Complex Topic Learning Based on a Sustainable Design Approach

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 the 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 the adoption of complex thinking by taking on account a user’s objective and subjective contexts.