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Chang Cai; Shengxin Hong; Min Ma; Haiyue Feng; Sixuan Du; Minyang Chow; Winnie Li-Lian Teo; Siyuan Liu; Xiuyi Fan – Education and Information Technologies, 2025
Analyzing the teaching and learning environment (TLE) through student feedback is essential for identifying curricular gaps and improving teaching practices. However, traditional feedback analysis methods, particularly for qualitative data, are often time-consuming and prone to human bias. Large Language Models (LLMs) offer a promising solution by…
Descriptors: Educational Environment, Feedback (Response), Measures (Individuals), Natural Language Processing
Adam Lockwood; Ryan Farmer; Gagan Shergill; Nicholas Benson; Kacey Gilbert – Journal of Psychoeducational Assessment, 2025
This study examines the effectiveness of artificial intelligence (AI) in psychological report writing by comparing reports generated by human psychologists with those produced by OpenAI's Generative Pre-trained Transformer Version 4 (ChatGPT-4). A total of 249 licensed psychologists evaluated the reports based on overall quality, readability,…
Descriptors: Man Machine Systems, Artificial Intelligence, Psychological Evaluation, Reports
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
Xuefan Li; Tingsong Li; Minjuan Wang; Sining Tao; Xiaoxu Zhou; Xiaoqing Wei; Naiqing Guan – IEEE Transactions on Learning Technologies, 2025
With the rapid advancement of generative artificial intelligence (GAI), its application in educational settings has increasingly become a focal point, particularly in enhancing students' analytical capabilities. This study examines the effectiveness of the ChatGPT prompt framework in improving text analysis skills among students, specifically…
Descriptors: Artificial Intelligence, Technology Uses in Education, High School Students, Foreign Countries
Taegang Lee; Yoonhyoung Lee; Sungmook Choi – Language Learning & Technology, 2025
Empirical evidence remains sparse about how videos enhanced with first-language (L1) and second-language (L2) subtitles influence cognitive load in L2 learners. To address this point, 25 Korean undergraduate students were exposed to six short videos: baseline, L1-subtitled, and L2-subtitled videos at both high and low difficulty levels (determined…
Descriptors: Captions, Native Language, Second Language Learning, Language Processing

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