Fine-grained affect detection in learners’ generated content using machine learning

Learners’ adaptation to academic trajectory is shaped by several influencing factors that ought to be considered while attempting to design an intervention towards improving academic performance. Emotion is one factor that influences students’ academic orientation and performance. Tracking emotions...

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Bibliographic Details
Published in:Education and information technologies 2019-11, Vol.24 (6), p.3767-3783
Main Authors: Kolog, Emmanuel Awuni, Devine, Samuel Nii Odoi, Ansong-Gyimah, Kwame, Agjei, Richard Osei
Format: Article
Language:English
Subjects:
Academic achievement
Algorithms
Artificial Intelligence
Autobiographies
Classification
Comparative Analysis
Computational linguistics
Computer Appl. in Social and Behavioral Sciences
Computer Science
Computers and Education
Counseling
Data mining
Education
Educational Technology
Emotions
Identification
Information Systems Applications (incl.Internet)
Language processing
Learning strategies
Machine learning
Natural language interfaces
Psychological Patterns
Psychologists
Students
User Interfaces and Human Computer Interaction
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