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Linh Huynh; Danielle S. McNamara – Grantee Submission, 2025
We conducted two experiments to assess the alignment between Generative AI (GenAI) text personalization and hypothetical readers' profiles. In Experiment 1, four LLMs (i.e., Claude 3.5 Sonnet; Llama; Gemini Pro 1.5; ChatGPT 4) were prompted to tailor 10 science texts (i.e., biology, chemistry, physics) to accommodate four different profiles…
Descriptors: Natural Language Processing, Profiles, Individual Differences, Semantics
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Ellana Black; Kristen Betts – Impacting Education: Journal on Transforming Professional Practice, 2025
This convergent mixed methods research study investigated how a small, non-representative sample of Educational Doctorate (EdD) faculty perceive and use generative AI and how they have leveraged the technology to support EdD students. A cross-sectional survey was used to gather data from 27 EdD faculty members to assess their generative AI…
Descriptors: Doctoral Programs, Education Majors, College Faculty, Artificial Intelligence
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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