National Key Research and Development Program of China [2017YFB1401300, 2017YFB1401303]; National Natural Science Foundation of ChinaNational Natural Science Foundation of China (NSFC) [61505064]; Hong Kong Scholars Programs [XJ2016063]; National Natural Science Foundation of Hubei Province [2016CFB497]; Self-determined Research Funds of CCNU [CCNU18ZDPY10, CCNU16JYKX031]
机构署名：
本校为第一机构
院系归属：
国家数字化学习工程技术研究中心
摘要：
Online learning engagement detection is a fundamental problem in educational information technology. Efficient detection of students’ learning situations can provide information to teachers to help them identify students having trouble in real time. To improve the accuracy of learning engagement detection, we have collected two aspects of students’ behavior data: face data (using adaptive weighted Local Gray Code Patterns for facial expression recognition) and mouse interaction. In this article, we propose a novel learning engagement detectio...
