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Kun Wang – International Journal of Web-Based Learning and Teaching Technologies, 2025
This study investigates the development and implementation of a big data-driven English ecological classroom teaching model, aiming to reform university English instruction in alignment with contemporary technological advancements. The conventional teaching framework, often limited to textbooks and in-class activities, has been shown to…
Descriptors: English (Second Language), Second Language Learning, Second Language Instruction, Learner Engagement
Samaranayake, Sobitha; Gunawardena, Athula D. A.; Meyer, Robert R. – Athens Journal of Education, 2023
Many students in the Unites States enter college without having decided on a focus for their studies, and thus are faced with choosing from a large number of potential majors and associated very complex sets of degree requirements which can include many courses in other areas of study. Academic advisors use academic planning tools to help students…
Descriptors: College Students, Degree Requirements, Academic Degrees, Decision Support Systems
Varun Mandalapu – ProQuest LLC, 2021
Educational data mining focuses on exploring increasingly large-scale data from educational settings, such as Learning Management Systems (LMS), and developing computational methods to understand students' behaviors and learning settings better. There has been a multitude of research dedicated to studying the student learning process, leading to…
Descriptors: Models, Student Behavior, Learning Management Systems, Data Use
Hu, Xiangen, Ed.; Barnes, Tiffany, Ed.; Hershkovitz, Arnon, Ed.; Paquette, Luc, Ed. – International Educational Data Mining Society, 2017
The 10th International Conference on Educational Data Mining (EDM 2017) is held under the auspices of the International Educational Data Mining Society at the Optics Velley Kingdom Plaza Hotel, Wuhan, Hubei Province, in China. This years conference features two invited talks by: Dr. Jie Tang, Associate Professor with the Department of Computer…
Descriptors: Data Analysis, Data Collection, Graphs, Data Use

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