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Kajal Mahawar; Punam Rattan – Education and Information Technologies, 2025
Higher education institutions have consistently strived to provide students with top-notch education. To achieve better outcomes, machine learning (ML) algorithms greatly simplify the prediction process. ML can be utilized by academicians to obtain insight into student data and mine data for forecasting the performance. In this paper, the authors…
Descriptors: Electronic Learning, Artificial Intelligence, Academic Achievement, Prediction
Khaleel Asyraaf Mat Sanusi; Deniz Iren; Nardie Fanchamps; Mai Geisen; Roland Klemke – Educational Technology Research and Development, 2025
Psychomotor skill training has traditionally relied on the physical presence of both teacher and learner for effective demonstrations and feedback, posing challenges for remote and self-directed learning. Technological advancements have given rise to immersive learning environments (ILEs), offering novel solutions for interactive and multimodal…
Descriptors: Psychomotor Skills, Skill Development, Computer Simulation, Electronic Learning
Kalender Arikan – Journal of Baltic Science Education, 2025
Learning style (LS), either visual or verbal, has become debatable in the f ield of education vis-à-vis its relation to student success. However, it remains a valuable research theme for improving learning activities in the teaching of highly visual science fields, including biology, physics, and chemistry. Previous studies have primarily focused…
Descriptors: Cognitive Style, Biology, Retention (Psychology), Science Education
Jing Chen; Yi Jiang – SAGE Open, 2025
Anticipatory "it" pattern, which encodes interpersonal stance, plays a crucial role in academic writing. While previous studies have been explored the overuse and the underuse of this pattern among English as a Foreign Language (EFL) learners and published writers, there has been limited exploration of how EFL learners use the…
Descriptors: Foreign Countries, Masters Programs, Graduate Students, English (Second Language)
Brendan Bartanen; Andrew Kwok; Andrew Avitabile; Brian Heseung Kim – Grantee Submission, 2025
Heightened concerns about the health of the teaching profession highlight the importance of studying the early teacher pipeline. This exploratory, descriptive article examines preservice teachers' expressed motivation for pursuing a teaching career. Using data from a large teacher education program in Texas, we use a natural language processing…
Descriptors: Career Choice, Teaching (Occupation), Teacher Education Programs, Preservice Teachers