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Xiaoqing Xu; Lifang Qiao; Nuo Cheng; Hongxia Liu; Wei Zhao – British Journal of Educational Technology, 2025
The rapid development of generative artificial intelligence (GenAI) has brought opportunities and new challenges to higher education. Students need a high level of self-regulated learning to adapt to this change. However, it is difficult for students to persist in self-regulation without guidance. Metacognitive support has a significant advantage…
Descriptors: Independent Study, Learning Experience, Artificial Intelligence, Technology Uses in Education
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Giulia Cosentino; Jacqueline Anton; Kshitij Sharma; Mirko Gelsomini; Michail Giannakos; Dor Abrahamson – British Journal of Educational Technology, 2025
This study explores the role of generative AI (GenAI) in providing formative feedback in children's digital learning experiences, specifically in the context of mathematics education. Using multimodal data, the research compares AI-generated feedback with feedback from human instructors, focusing on its impact on children's learning outcomes.…
Descriptors: Artificial Intelligence, Technology Uses in Education, Feedback (Response), Mathematics Education
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Chia-Jung Li; Gwo-Jen Hwang; Ching-Yi Chang; Hui-Chi Su – British Journal of Educational Technology, 2025
In professional training, developing critical thinking is essential for professionals to analyse problem situations and respond effectively to emergencies. Conventional professional training typically employs multimedia materials combined with progressive prompting (PP) to support trainees in constructing knowledge and solving problems on their…
Descriptors: Artificial Intelligence, Technology Uses in Education, Prompting, Academic Achievement
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Michaela Arztmann; Jessica Lizeth Domínguez Alfaro; Lisette Hornstra; Jacqueline Wong; Johan Jeuring; Liesbeth Kester – British Journal of Educational Technology, 2025
A distinct feature of educational games using augmented reality (AR) is that the game is played through physically interacting with the environment, whereas physical interaction is typically rather limited in other digital games. Understanding and performing the interactive game mechanics can be cognitively demanding. Adding pre-training could…
Descriptors: Computer Simulation, Artificial Intelligence, Training, Cognitive Processes
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Anna Y. Q. Huang; Cheng-Yan Lin; Sheng-Yi Su; Stephen J. H. Yang – British Journal of Educational Technology, 2025
Programming education often imposes a high cognitive burden on novice programmers, requiring them to master syntax, logic, and problem-solving while simultaneously managing debugging tasks. Prior knowledge is a critical factor influencing programming learning performance. A lack of foundational knowledge limits students' self-regulated learning…
Descriptors: Artificial Intelligence, Technology Uses in Education, Coding, Programming
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Yun Dai; Ziyan Lin; Ang Liu; Wenlan Wang – British Journal of Educational Technology, 2024
While AI has become more prevalent in our society than ever, many young learners are found holding various naive, erroneous conceptions of AI due to the influence of their technology and media environments. To address this issue, this study seeks to propose a novel pedagogical solution to improve upper-elementary school students' scientific…
Descriptors: Artificial Intelligence, Technology Uses in Education, Elementary Education, Elementary School Students
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Chen, Chih-Ming – British Journal of Educational Technology, 2009
Developing personalised web-based learning systems has been an important research issue in e-learning because no fixed learning pathway will be appropriate for all learners. However, most current web-based learning platforms with personalised curriculum sequencing tend to emphasise the learner preferences and interests in relation to personalised…
Descriptors: Electronic Learning, Concept Mapping, Difficulty Level, Cognitive Processes