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Jinsook Lee; Yann Hicke; Renzhe Yu; Christopher Brooks; René F. Kizilcec – British Journal of Educational Technology, 2024
Large language models (LLMs) are increasingly adopted in educational contexts to provide personalized support to students and teachers. The unprecedented capacity of LLM-based applications to understand and generate natural language can potentially improve instructional effectiveness and learning outcomes, but the integration of LLMs in education…
Descriptors: Artificial Intelligence, Technology Uses in Education, Equal Education, Algorithms
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Hyunkyung Chee; Solmoe Ahn; Jihyun Lee – British Journal of Educational Technology, 2025
This study aims to develop a comprehensive competency framework for artificial intelligence (AI) literacy, delineating essential competencies and sub-competencies. This framework and its potential variations, tailored to different learner groups (by educational level and discipline), can serve as a crucial reference for designing and implementing…
Descriptors: Competence, Digital Literacy, Artificial Intelligence, Technology Uses in Education
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Huixiao Le; Yuan Shen; Zijian Li; Mengyu Xia; Luzhen Tang; Xinyu Li; Jiyou Jia; Qiong Wang; Dragan Gaševic; Yizhou Fan – British Journal of Educational Technology, 2025
Understanding learners' preferences in educational settings is crucial for optimizing learning outcomes and experience. As artificial intelligence (AI) becomes increasingly integrated into educational contexts, it is crucial to understand learners' preferences between AI and human tutors to support their learning. While AI demonstrates growing…
Descriptors: Student Attitudes, Preferences, Electronic Learning, Artificial Intelligence