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Review of affective computing in education/learning: Trends and challenges
Author(s) -
Wu ChihHung,
Huang YuehMin,
Hwang JanPan
Publication year - 2016
Publication title -
british journal of educational technology
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.79
H-Index - 95
eISSN - 1467-8535
pISSN - 0007-1013
DOI - 10.1111/bjet.12324
Subject(s) - categorization , affect (linguistics) , affective computing , process (computing) , computer science , psychology , educational technology , mathematics education , artificial intelligence , communication , operating system
Affect can significantly influence education/learning. Thus, understanding a learner's affect throughout the learning process is crucial for understanding motivation. In conventional education/learning research, learner motivation can be known through postevent self‐reported questionnaires. With the advance of affective computing technology, researchers are able to objectively identify and measure a learner's affective status during the entire learning process in a real‐time manner, and then they are able to understand the interrelationship between emotion, motivation and learning performance. There are over 100 papers in the ScienceDirect database with the keywords “affective computing in education” or “affective computing in learning,” which reveals that this emerging technology has been applied to education/learning. This study intends to categorize and summarize those measurements so as to realize their applicability, feasibility and trends. Finally, some challenges and suggestions are then raised for helping educational researchers when applying affective computing technology.