Recognizing Multidimensional Engagement of E-Learners Based on Multi-Channel Data in E-Learning Environment

Volume: 7, Pages: 149554 - 149567
Published: Jan 1, 2019
Abstract
Despite recent advances in MOOC, the current e-learning systems have advantages of alleviating barriers by time differences, and geographically spatial separation between teachers and students. However, there has been a 'lack of supervision' problem that e-learner's learning unit state(LUS) can't be supervised automatically. In this paper, we present a fusion framework considering three channel data sources: 1) videos/images from a camera, 2)...
Paper Details
Title
Recognizing Multidimensional Engagement of E-Learners Based on Multi-Channel Data in E-Learning Environment
Published Date
Jan 1, 2019
Volume
7
Pages
149554 - 149567
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