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Shuanghong Shen; Qi Liu; Zhenya Huang; Yonghe Zheng; Minghao Yin; Minjuan Wang; Enhong Chen – IEEE Transactions on Learning Technologies, 2024
Modern online education has the capacity to provide intelligent educational services by automatically analyzing substantial amounts of student behavioral data. Knowledge tracing (KT) is one of the fundamental tasks for student behavioral data analysis, aiming to monitor students' evolving knowledge state during their problem-solving process. In…
Descriptors: Student Behavior, Electronic Learning, Data Analysis, Models
Chen, Weiyu; Brinton, Christopher G.; Cao, Da; Mason-Singh, Amanda; Lu, Charlton; Chiang, Mung – IEEE Transactions on Learning Technologies, 2019
We study learning outcome prediction for online courses. Whereas prior work has focused on semester-long courses with frequent student assessments, we focus on short-courses that have single outcomes assigned by instructors at the end. The lack of performance data and generally small enrollments makes the behavior of learners, captured as they…
Descriptors: Online Courses, Outcomes of Education, Prediction, Course Content
Demmans Epp, Carrie; Bull, Susan – IEEE Transactions on Learning Technologies, 2015
Adding uncertainty information to visualizations is becoming increasingly common across domains since its addition helps ensure that informed decisions are made. This work has shown the difficulty that is inherent to representing uncertainty. Moreover, the representation of uncertainty has yet to be thoroughly explored in educational domains even…
Descriptors: Visual Aids, Data Analysis, Ambiguity (Context), Design