Cognitive Load Estimation Using a Hybrid Cluster-Based Unsupervised Machine Learning Technique
Author:
Affiliation:
1. Sozo Laboratory, Kyushu Institute of Technology, Fukuoka, Japan
2. College of Medicine, QU Health, Qatar University, Doha, Qatar
3. Department of Electrical Engineering, Qatar University, Doha, Qatar
Funder
Vice President (VP) Grant of the Health Cluster of Qatar University, and Open Access funding provided by the Qatar National Library
Publisher
Institute of Electrical and Electronics Engineers (IEEE)
Link
http://xplorestaging.ieee.org/ielx8/6287639/10380310/10643748.pdf?arnumber=10643748
Reference82 articles.
1. Cognitive Load Theory: Instructional Implications of the Interaction between Information Structures and Cognitive Architecture
2. Element Interactivity and Intrinsic, Extraneous, and Germane Cognitive Load
3. Cognitive Load Theory and Instructional Design: Recent Developments
4. Cognitive Load Measurement as a Means to Advance Cognitive Load Theory
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