Mood Recognition during Online Self-Assessment Tests

Individual emotions play a crucial role during any learning interaction. Identifying a student's emotional state and providing personalized feedback, based on integrated pedagogical models, has been considered to be one of the main limits of traditional tools of e-learning. This paper presents...

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Bibliographic Details
Published in:IEEE transactions on learning technologies 2009-01, Vol.2 (1), p.50-61
Main Authors: Moridis, C.N., Economides, A.A.
Format: Article
Language:English
Subjects:
Computer Uses in Education
Data mining
Decision support systems
Distance education
Education
Emotions
Human-centered computing
Learning
Mathematical models
Moods
On-line systems
Online
Personalization
Probability density function
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Summary:Individual emotions play a crucial role during any learning interaction. Identifying a student's emotional state and providing personalized feedback, based on integrated pedagogical models, has been considered to be one of the main limits of traditional tools of e-learning. This paper presents an empirical study that illustrates how learner mood may be predicted during online self-assessment tests. Here a previous method of determining student mood has been refined based on the assumption that the influence on learner mood of questions already answered declines in relation to their distance from the current question. Moreover, this paper sets out to indicate that ldquoexponential logicrdquo may help produce more efficient models, if integrated adequately with affective modelling. The results show that these assumptions may prove useful to future research.
ISSN:1939-1382
1939-1382
2372-0050
DOI:10.1109/TLT.2009.12