Learning Style identification and usage in academia: A systematic mapping | Zendy

Miguel Alvim de Almeida | Zendy; Jairo Francisco de Souza | Zendy; Eduardo Barreré | Zendy

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Learning Style identification and usage in academia: A systematic mapping

Author(s) -

Miguel Alvim de Almeida,

Jairo Francisco de Souza,

Eduardo Barreré

Publication year - 2019

Publication title -

anais do xxx simpósio brasileiro de informática na educação (sbie 2019)

Language(s) - English

Resource type - Conference proceedings

DOI - 10.5753/cbie.sbie.2019.1341

Subject(s) - identification (biology) , adaptation (eye) , computer science , style (visual arts) , point (geometry) , learning styles , work (physics) , artificial intelligence , machine learning , human–computer interaction , data science , engineering , mathematics education , psychology , mechanical engineering , history , botany , geometry , mathematics , archaeology , neuroscience , biology

The different learning style models and applications might be an obstacle for those who are seeking to start to work in this field. Also, one might not be able to find some key papers that many regards as good starting points. This paper presents a systematic mapping, done with 102 papers, in regards to learning style identification and usage, and seeks to create a starting point for those who are starting to work on these research fields. The results show the predominance of a few learning style models and learning object metadata models. Also, there is a high amount of works focusing on personal solutions with non-automatic detection and adaptation models.

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