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Xing, Wanli; Pei, Bo; Li, Shan; Chen, Guanhua; Xie, Charles – Interactive Learning Environments, 2023
Engineering design plays an important role in education. However, due to its open nature and complexity, providing timely support to students has been challenging using the traditional assessment methods. This study takes an initial step to employ learning analytics to build performance prediction models to help struggling students. It allows…
Descriptors: Learning Analytics, Engineering Education, Prediction, Design
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Premlatha, K. R.; Dharani, B.; Geetha, T. V. – Interactive Learning Environments, 2016
E-learning allows learners individually to learn "anywhere, anytime" and offers immediate access to specific information. However, learners have different behaviors, learning styles, attitudes, and aptitudes, which affect their learning process, and therefore learning environments need to adapt according to these differences, so as to…
Descriptors: Electronic Learning, Profiles, Automation, Classification
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Huang, Yueh-Min; Huang, Yong-Ming; Liu, Chien-Hung; Tsai, Chin-Chung – Interactive Learning Environments, 2013
Web-based self-learning (WBSL) has received a lot of attention in recent years due to the vast amount of varied materials available in the Web 2.0 environment. However, this large amount of material also has resulted in a serious problem of cognitive overload that degrades the efficacy of learning. In this study, an information graphics method is…
Descriptors: Web 2.0 Technologies, Cognitive Processes, Difficulty Level, College Students