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Teija Paavilainen; Sonsoles López-Pernas; Sanna Väisänen; Sini Kontkanen; Laura Hirsto – Technology, Knowledge and Learning, 2025
In digitalized learning processes, learning analytics (LA) can help teachers make pedagogically sound decisions and support pupils' self-regulated learning (SRL). However, research on the role of the pedagogical dimensions of learning design (LD) in influencing the possibilities of LA remains scarce. Primary school presents a unique LA context…
Descriptors: Learning Analytics, Independent Study, Elementary Education, Instructional Design
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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
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Mohammed Jebbari; Bouchaib Cherradi; Soufiane Hamida; Abdelhadi Raihani – Education and Information Technologies, 2024
With the advancements in technology and the growing demand for online education, Virtual Learning Environments (VLEs) have experienced rapid development in recent years. This demand was especially evident during the COVID-19 pandemic. The incorporation of new technologies in VLEs provides new opportunities to better understand the behaviors of…
Descriptors: MOOCs, Algorithms, Computer Simulation, COVID-19
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Omer Ari; Kara Hageman; Andrea Lofgren – Research & Practice in Assessment, 2024
Quizzes using test-enhanced learning features of spaced, varied, and interleaved retrieval practice have been shown to support consolidation of knowledge gains in students. In this pilot study, we examined the test-enhanced learning potential of a novel quizzing method designed to Spiral Assessment to Reinforce Knowledge (SPARK; Hageman, 2020)…
Descriptors: Online Courses, Computer Assisted Testing, Taxonomy, Learning Processes
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Tran, Tuan M.; Hasegawa, Shinobu – International Association for Development of the Information Society, 2022
A learner model reflects learning patterns and characteristics of a learner. A learner model with learning history and its effectiveness plays a significant role in supporting a learner's understanding of their strengths and weaknesses of their way of learning in order to make proper adjustments for improvement. Nowadays, learners have been…
Descriptors: Markov Processes, Learning Processes, Models, Scores
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Tlili, Ahmed; Denden, Mouna; Essalmi, Fathi; Jemni, Mohamed; Chang, Maiga; Kinshuk; Chen, Nian-Shing – Interactive Learning Environments, 2023
The ability of automatically modeling learners' personalities is an important step in building adaptive learning environments. Several studies showed that knowing the personality of each learner can make the learning interaction with the provided learning contents and activities within learning systems more effective. However, the traditional…
Descriptors: Learning Analytics, Learning Management Systems, Intelligent Tutoring Systems, Bayesian Statistics
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Chu, Wei; Pavlik, Philip I., Jr. – International Educational Data Mining Society, 2023
In adaptive learning systems, various models are employed to obtain the optimal learning schedule and review for a specific learner. Models of learning are used to estimate the learner's current recall probability by incorporating features or predictors proposed by psychological theory or empirically relevant to learners' performance. Logistic…
Descriptors: Reaction Time, Accuracy, Models, Predictor Variables