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Gitinabard, Niki; Xu, Yiqiao; Heckman, Sarah; Barnes, Tiffany; Lynch, Collin F. – IEEE Transactions on Learning Technologies, 2019
Blended courses that mix in-person instruction with online platforms are increasingly common in secondary education. These platforms record a rich amount of data on students' study habits and social interactions. Prior research has shown that these metrics are correlated with students performance in face-to-face classes. However, predictive models…
Descriptors: Blended Learning, Educational Technology, Technology Uses in Education, Prediction
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Pardo, Abelardo; Han, Feifei; Ellis, Robert A. – IEEE Transactions on Learning Technologies, 2017
Self-regulated learning theories are used to understand the reasons for different levels of university student academic performance. Similarly, learning analytics research proposes the combination of detailed data traces derived from technology-mediated tasks with a variety of algorithms to predict student academic performance. The former approach…
Descriptors: Student Centered Learning, Learning Theories, College Students, Academic Achievement
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Al-Hmouz, A.; Shen, Jun; Al-Hmouz, R.; Yan, Jun – IEEE Transactions on Learning Technologies, 2012
With recent advances in mobile learning (m-learning), it is becoming possible for learning activities to occur everywhere. The learner model presented in our earlier work was partitioned into smaller elements in the form of learner profiles, which collectively represent the entire learning process. This paper presents an Adaptive Neuro-Fuzzy…
Descriptors: Electronic Learning, Blended Learning, Educational Technology, Media Adaptation