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Sonja Kleter; Uwe Matzat; Rianne Conijn – IEEE Transactions on Learning Technologies, 2024
Much of learning analytics research has focused on factors influencing model generalizability of predictive models for academic performance. The degree of model generalizability across courses may depend on aspects, such as the similarity of the course setup, course material, the student cohort, or the teacher. Which of these contextual factors…
Descriptors: Prediction, Models, Academic Achievement, Learning Analytics
Xiuyu Lin; Zehui Zhan; Xuebo Zhang; Jiayi Xiong – IEEE Transactions on Learning Technologies, 2024
The attribution of learning success or failure is crucial for students' learning and motivation. Effective attribution of their learning success or failure in the context of a small private online course (SPOC) could generate students' motivation toward learning success while an incorrect attribution would lead to a sense of helplessness. Based on…
Descriptors: Learning Analytics, Learning Processes, Learning Motivation, Attribution Theory
Ueno, Maomi; Miyazawa, Yoshimitsu – IEEE Transactions on Learning Technologies, 2018
Over the past few decades, many studies conducted in the field of learning science have described that scaffolding plays an important role in human learning. To scaffold a learner efficiently, a teacher should predict how much support a learner must have to complete tasks and then decide the optimal degree of assistance to support the learner's…
Descriptors: Scaffolding (Teaching Technique), Prediction, Probability, Comparative Analysis