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Jia Zhu; Xiaodong Ma; Changqin Huang – IEEE Transactions on Learning Technologies, 2024
Knowledge tracing (KT) for evaluating students' knowledge is an essential task in personalized education. More and more researchers have devoted themselves to solving KT tasks, e.g., deep knowledge tracing (DKT), which can capture more sophisticated representations of student knowledge. Nonetheless, these techniques ignore the reconstruction of…
Descriptors: Teaching Methods, Knowledge Level, Algorithms, Attribution Theory
Yuang Wei; Bo Jiang – IEEE Transactions on Learning Technologies, 2024
Understanding student cognitive states is essential for assessing human learning. The deep neural networks (DNN)-inspired cognitive state prediction method improved prediction performance significantly; however, the lack of explainability with DNNs and the unitary scoring approach fail to reveal the factors influencing human learning. Identifying…
Descriptors: Cognitive Mapping, Models, Prediction, Short Term Memory
Hua Ma; Wen Zhao; Yuqi Tang; Peiji Huang; Haibin Zhu; Wensheng Tang; Keqin Li – IEEE Transactions on Learning Technologies, 2024
To prevent students from learning risks and improve teachers' teaching quality, it is of great significance to provide accurate early warning of learning performance to students by analyzing their interactions through an e-learning system. In existing research, the correlations between learning risks and students' changing cognitive abilities or…
Descriptors: College Students, Learning Analytics, Learning Management Systems, Academic Achievement
Wan, Han; Zhong, Zihao; Tang, Lina; Gao, Xiaopeng – IEEE Transactions on Learning Technologies, 2023
Small private online courses (SPOCs) have influenced teaching and learning in China's higher education. Learning management systems (LMSs) are important components in SPOCs. They can collect various data related to student behavior and support pedagogical interventions. This research used feature engineering and nearest neighbor smoothing models…
Descriptors: Online Courses, Learning Management Systems, Higher Education, Student Behavior
Whitehill, Jacob; Movellan, Javier – IEEE Transactions on Learning Technologies, 2018
We propose a method of generating teaching policies for use in intelligent tutoring systems (ITS) for concept learning tasks [1], e.g., teaching students the meanings of words by showing images that exemplify their meanings à la Rosetta Stone [2] and Duo Lingo [3]. The approach is grounded in control theory and capitalizes on recent work by [4],…
Descriptors: Intelligent Tutoring Systems, Second Language Learning, Educational Policy, Comparative Analysis
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