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Majdi Beseiso – TechTrends: Linking Research and Practice to Improve Learning, 2025
Predicting students' success is crucial in educational settings to improve academic performance and prevent dropouts. This study aimed to improve student performance prediction by combining advanced machine learning (ML) approaches. Convolutional Neural Networks (CNNs) and attention mechanisms were used for extracting relevant features from…
Descriptors: Prediction, Success, Academic Achievement, Artificial Intelligence
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Nkomo, Larian M.; Nat, Muesser – TechTrends: Linking Research and Practice to Improve Learning, 2021
With various digital technologies increasingly integrated into higher education, understanding how students engage with such technologies has become vital. There are different ways to measure student engagement; however, self-reported measures such as questionnaires are predominantly used to understand student engagement. In contrast, this study…
Descriptors: Learner Engagement, Blended Learning, Educational Environment, Data Collection
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Cho, Eunsoon; Cho, Young Hoan; Grant, Michael M.; Song, Donggil; Huh, Yeol – TechTrends: Linking Research and Practice to Improve Learning, 2020
The Korean Society for Educational Technology (KSET) hosted its second panel discussion partnering with the Association for Educational Communications and Technology (AECT) at the 2019 AECT Convention in Las Vegas, Nevada. A total of four panelists, two from Korea and two from the U.S., participated in the discussion on the trends of educational…
Descriptors: Foreign Countries, Educational Technology, Technology Uses in Education, Telecommunications
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Aguilar, Stephen J. – TechTrends: Linking Research and Practice to Improve Learning, 2018
We are still designing educational experiences for the "average" student, and have room to improve. Learning analytics provides a way forward. This commentary describes how learning analytics-based applications are well positioned to meaningfully personalize the learning experience in diverse ways. In so doing, learning analytics has the…
Descriptors: Instructional Design, Social Justice, Educational Research, Data Collection
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Wang, Yinying – TechTrends: Linking Research and Practice to Improve Learning, 2016
Against the backdrop of the ever-increasing influx of big data, this article examines the opportunities and concerns over big data in education. Specifically, this article first introduces big data, followed by delineating the potential opportunities of using big data in education in two areas: learning analytics and educational policy. Then, the…
Descriptors: Educational Research, Data Collection, Data Analysis, Educational Policy
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Gaševic, Dragan; Dawson, Shane; Siemens, George – TechTrends: Linking Research and Practice to Improve Learning, 2015
The analysis of data collected from the interaction of users with educational and information technology has attracted much attention as a promising approach for advancing our understanding of the learning process. This promise motivated the emergence of the new research field, learning analytics, and its closely related discipline, educational…
Descriptors: Data Collection, Educational Research, Data Analysis, Information Technology
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Prasad, Deepak; Totaram, Rajneel; Usagawa, Tsuyoshi – TechTrends: Linking Research and Practice to Improve Learning, 2016
In the last few years, open textbook development has picked up dramatically due both to the expense of commercially published textbooks and the increasing availability of high-quality OER alternatives. While this offers a tremendous benefit in terms of lowering student textbook costs, the question remains, to what extent (if any) do open textbooks…
Descriptors: Textbooks, Open Source Technology, Electronic Publishing, Reader Text Relationship