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Sam O'Neill; David Mulgrew; Ovidiu Bagdasar – Open Education Studies, 2025
Large language models (LLMs) hold great promise for enhancing teaching and learning in higher education, yet educators and administrators still lack practical examples to guide their adoption. This article presents insights and use cases from the integration of LLMs into a first-year undergraduate computer science cohort. By employing LLMs as…
Descriptors: Artificial Intelligence, Natural Language Processing, Higher Education, College Faculty
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Ke Li; Lulu Lun; Pingping Hu – Education and Information Technologies, 2025
Amid the ongoing discussion about the potential of LLMs (Large Language Models) to facilitate language learning, there has been a broad spectrum of views in academia. However, little is known about the different viewpoints of students and what contributes to these differences. In light of this, this study adopts Q-methodology, a mixed-methods…
Descriptors: Student Attitudes, Language Attitudes, Affordances, Artificial Intelligence
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Sam Goundar, Editor – IntechOpen, 2025
"Massive Open Online Courses -- Learning Frontiers and Novel Innovations" explores the potential of MOOCs in revolutionizing global education. This book looks into the advancements, challenges, and innovative practices that define the evolving world of online learning. Chapters in the book address critical themes such as learner…
Descriptors: MOOCs, Educational Trends, Educational Innovation, Global Approach
Xiaoming Zhai, Editor; Joseph Krajcik, Editor – Oxford University Press, 2025
In the age of rapid technological advancements, the integration of Artificial Intelligence (AI), machine learning (ML), and large language models (LLMs) in Science, Technology, Engineering, and Mathematics (STEM) education has emerged as a transformative force, reshaping pedagogical approaches and assessment methodologies. "Uses of AI in STEM…
Descriptors: Artificial Intelligence, STEM Education, Technology Uses in Education, Educational Technology