, Volume 45, Issue 1, pp 133–155 | Cite as

Social constructivist approach of motivation: social media messages recommendation system

  • Sébastien LouvignéEmail author
  • Masaki Uto
  • Yoshihiro Kato
  • Takatoshi Ishii
Original Paper


Contemporary learning theories and their implementations associated with information and communication technologies increasingly integrate social constructivist approaches in order to assist and facilitate the construction of knowledge. Social constructivism also highlights the important role of culture, learning attitude and behavior in the cognitive process. Modern e-learning systems need to include these psychological aspects in addition to knowledge construction in order to connect with long-standing pedagogical issues such as the decrease and lack of motivation for education. Current Social Networking Services (SNS) provide a platform where peers can express their passion, emotion, and motivation toward learning. Therefore, this research utilizes this platform to recommend motivational contents from peers for learning motivation enhancement (i.e., learners’ perception of their goal and purpose for learning). The proposed system consists of an SNS platform for learners to (1) express and evaluate their own goals for learning, (2) observe motivational messages from peers recommended from an LDA-based (latent Dirichlet allocation) model, and (3) evaluate their perceptions on motivational and psychological attributes. The LDA-based model recommends messages expressing diverse purposes for a shared goal by maximizing the topic divergence of Twitter messages. Learners’ self-evaluations show the positive and significant impact of observing diverse learning purposes from peers on intrinsic motivational attributes such as goal specificity, attainability, and on the confidence to achieve the desired outcome.


Social constructivism Learning motivation Recommendation system Latent Dirichlet allocation 



The authors thank the English Department of the University of Electro- Communications in Tokyo and professors SHI Jie, Shin’ichi Hashimoto, YU Yan and Paul McKenna who participated in the experiment and instructed their students to use the recommendation system presented in this paper.


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Copyright information

© The Behaviormetric Society 2017

Authors and Affiliations

  1. 1.Decimale SolutionGrenobleFrance
  2. 2.Graduate School of Information SystemsUniversity of Electro-CommunicationsChofuJapan
  3. 3.Benesse Educational Research and Development InstituteTama-shiJapan
  4. 4.Department of System DesignTokyo University of ScienceTokyoJapan

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