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Guiqin Liang; Chunsong Jiang; Qiuzhe Ping; Xinyi Jiang – Interactive Learning Environments, 2024
With long-term impact of COVID-19 on education, online interactive live courses have been an effective method to keep learning and teaching from being interrupted, attracting more and more attention due to their synchronous and real-time interaction. However, there is no suitable method for predicting academic performance for students…
Descriptors: Academic Achievement, Prediction, Engineering Education, Online Courses
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Wan, Han; Liu, Kangxu; Yu, Qiaoye; Gao, Xiaopeng – IEEE Transactions on Learning Technologies, 2019
Most educational institutions adopted the hybrid teaching mode through learning management systems. The logging data/clickstream could describe learners' online behavior. Many researchers have used them to predict students' performance, which has led to a diverse set of findings, but how to use insights from captured data to enhance learning…
Descriptors: Educational Practices, Learner Engagement, Identification, Study Habits
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Abdous, M'hammed; He, Wu; Yen, Cherng-Jyh – Educational Technology & Society, 2012
As higher education diversifies its delivery modes, our ability to use the predictive and analytical power of educational data mining (EDM) to understand students' learning experiences is a critical step forward. The adoption of EDM by higher education as an analytical and decision making tool is offering new opportunities to exploit the untapped…
Descriptors: Electronic Learning, Online Courses, Video Technology, Synchronous Communication