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Direct linkLee, Chia-An; Huang, Nen-Fu; Tzeng, Jian-Wei; Tsai, Pin-Han – IEEE Transactions on Learning Technologies, 2023
Massive open online courses offer a valuable platform for efficient and flexible learning. They can improve teaching and learning effectiveness by enabling the evaluation of learning behaviors and the collection of feedback from students. The knowledge map approach constitutes a suitable tool for evaluating and presenting students' learning…
Descriptors: Artificial Intelligence, MOOCs, Concept Mapping, Student Evaluation
Xing, Wanli; Du, Dongping; Bakhshi, Ali; Chiu, Kuo-Chun; Du, Hanxiang – IEEE Transactions on Learning Technologies, 2021
Predictive modeling in online education is a popular topic in learning analytics research and practice. This study proposes a novel predictive modeling method to improve model transferability over time within the same course and across different courses. The research gaps addressed are limited evidence showing whether a predictive model built on…
Descriptors: Electronic Learning, Bayesian Statistics, Prediction, Models
Tempelaar, Dirk T.; Rienties, Bart; Nguyen, Quan – IEEE Transactions on Learning Technologies, 2017
Studies in the field of learning analytics (LA) have shown students' demographics and learning management system (LMS) data to be effective identifiers of "at risk" performance. However, insights generated by these predictive models may not be suitable for pedagogically informed interventions due to the inability to explain why students…
Descriptors: Student Behavior, Integrated Learning Systems, Personality, Educational Research
