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Seyed Parsa Neshaei; Paola Mejia-Domenzain; Richard Lee Davis; Tanja Käser – British Journal of Educational Technology, 2025
Reflective writing is known as a useful method in learning sciences to improve the metacognitive skills of students. However, students struggle to structure their reflections properly, limiting the possible learning gains. Previous works in educational technologies literature have explored the paradigms of learning from worked and modelling…
Descriptors: Artificial Intelligence, Technology Uses in Education, Reflection, Writing (Composition)
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Fengyao Sun; Peiyao Tian; Daner Sun; Yanhua Fan; Yuqin Yang – British Journal of Educational Technology, 2024
In the ever-evolving AI-driven education, integrating AI technologies into teaching practices has become increasingly imperative for aspiring STEM educators. Yet, there remains a dearth of studies exploring pre-service STEM teachers' readiness to incorporate AI into their teaching practices. This study examined the factors influencing teachers'…
Descriptors: Artificial Intelligence, Educational Technology, Technology Integration, Preservice Teachers
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Belle Dang; Luna Huynh; Faaiz Gul; Carolyn Rosé; Sanna Järvelä; Andy Nguyen – British Journal of Educational Technology, 2025
The rise of generative artificial intelligence (GAI), especially with multimodal large language models like GPT-4o, sparked transformative potential and challenges for learning and teaching. With potential as a cognitive offloading tool, GAI can enable learners to focus on higher-order thinking and creativity. Yet, this also raises questions about…
Descriptors: Man Machine Systems, Artificial Intelligence, Technology Uses in Education, Cooperative Learning
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Istenic, Andreja; Bratko, Ivan; Rosanda, Violeta – British Journal of Educational Technology, 2021
Teachers' readiness for technology integration depends also on their beliefs about the contribution of technology to teaching and learning, which influence their motivation for its adoption. Initial pre-service teacher education is critical in reducing the attitude-behaviour divide supporting technology acceptability, acceptance and use.…
Descriptors: Preservice Teachers, Technology Integration, Robotics, 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
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Oleksandra Poquet; Maarten de Laat – British Journal of Educational Technology, 2021
Due to the ongoing digitalisation of workplaces and educational settings, human activity underpinning learning and work is increasingly mediated by technology. The advancement of artificial intelligence (AI) and its integration into everyday technologies influences how people are exposed to information, interact, learn and make decisions. We argue…
Descriptors: Skill Development, Lifelong Learning, Artificial Intelligence, Technology Uses in Education
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Wang, Shanyong; Yu, Haotian; Hu, Xianfeng; Li, Jun – British Journal of Educational Technology, 2020
The advancement of technology, especially the development and application of artificial intelligence, has deeply affected the education sector and brought opportunities for pedagogical adaptation. Intelligent tutoring systems, a major application of artificial intelligence in education, have drawn extensive concerns. However, in reality, the…
Descriptors: College Faculty, Teacher Attitudes, Technology Integration, Intelligent Tutoring Systems