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Showing 1 to 15 of 27 results Save | Export
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Long Zhang; Khe Foon Hew – Education and Information Technologies, 2025
Although self-regulated learning (SRL) plays an important role in supporting online learning performance, the lack of student self-regulation skills poses a persistent problem to many educators. Recommender systems have the potential to promote SRL by delivering personalized feedback and tailoring learning strategies to meet individual learners'…
Descriptors: Independent Study, Electronic Learning, Online Courses, Artificial Intelligence
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Wali Khan Monib; Atika Qazi; Malissa Maria Mahmud – Education and Information Technologies, 2025
ChatGPT has emerged as a transformative technology with its remarkable ability to generate human-like responses, propelling its widespread adoption. While prior research has investigated the general landscape of AI-driven tools such as ChatGPT, the current study focuses specifically on exploring learners' experiences and perceptions regarding the…
Descriptors: Student Attitudes, Student Experience, Artificial Intelligence, Natural Language Processing
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Ambroise Baillifard; Maxime Gabella; Pamela Banta Lavenex; Corinna S. Martarelli – Education and Information Technologies, 2025
Effective learning strategies based on principles like personalization, retrieval practice, and spaced repetition are often challenging to implement due to practical constraints. Here we explore the integration of AI tutors to complement learning programs in accordance with learning sciences. A semester-long study was conducted at UniDistance…
Descriptors: Intelligent Tutoring Systems, Artificial Intelligence, Instructional Effectiveness, Learning Strategies
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Dominic Lohr; Hieke Keuning; Natalie Kiesler – Journal of Computer Assisted Learning, 2025
Background: Feedback as one of the most influential factors for learning has been subject to a great body of research. It plays a key role in the development of educational technology systems and is traditionally rooted in deterministic feedback defined by experts and their experience. However, with the rise of generative AI and especially large…
Descriptors: College Students, Programming, Artificial Intelligence, Feedback (Response)
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Yuan Yao; Yiwen Sun; Siyu Zhu; Xinhua Zhu – European Journal of Education, 2025
Recent years have witnessed a growing application of generative artificial intelligence (GenAI) technology in writing instruction. Students should mobilise their metacognitive strategies during this endeavour to maximise the benefits of GenAI while avoiding the potential negative impacts. Within the context of tertiary education in Hong Kong, this…
Descriptors: Metacognition, Learning Strategies, Graduate Students, Technology Uses in Education
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Kok-Sing Tang; Grant Cooper – Science & Education, 2025
The introduction of generative artificial intelligence (GenAI) tools like ChatGPT has raised many challenging questions about the nature of teaching, learning, and assessment in every subject area, including science. Unlike other disciplines, natural science is unique because the ontological and epistemological understanding of nature is…
Descriptors: Science Education, Artificial Intelligence, Physical Environment, Realism
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Weijiao Huang; Khe Foon Hew – IEEE Transactions on Learning Technologies, 2025
In an online learning environment, both instruction and assessments take place virtually where students are primarily responsible for managing their own learning. This requires a high level of self-regulation from students. Many online students, however, lack self-regulation skills and are ill-prepared for autonomous learning, which can cause…
Descriptors: Independent Study, Interpersonal Relationship, Electronic Learning, Computer Software
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Msafiri Mgambi Msambwa; Zhang Wen; Kangwa Daniel – European Journal of Education, 2025
Artificial intelligence (AI) has extensively developed, impacting different sectors of society, including higher education, and has attracted the attention of various educational stakeholders, leading to a growing number of research on its integration into education. Hence, this systematic literature review examines the impact of integrating AI…
Descriptors: Influence of Technology, Technology Uses in Education, Artificial Intelligence, Cooperative Learning
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Gal Sasson Lazovsky; Tuval Raz; Yoed N. Kenett – Journal of Creative Behavior, 2025
As artificial intelligence and natural language processing methods rapidly develop, communication plays a pivotal role in every-day interactions. In this theoretical paper, we explore the overlap and commonalities between question-asking and prompt engineering. While seemingly distinct, these processes share a common foundation in essential skills…
Descriptors: Creativity, Questioning Techniques, Inquiry, Artificial Intelligence
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William T. Faranda – Marketing Education Review, 2025
Students' approaches to learning, including "deep," "surface," or "strategic" methods, significantly impact their academic success and skill development. This study investigates the transition in learning approach preferences among marketing majors, comparing junior-level students beginning their upper-division…
Descriptors: Business Education, Marketing, Capstone Experiences, Academic Achievement
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Conrad Borchers; Jeroen Ooge; Cindy Peng; Vincent Aleven – Grantee Submission, 2025
Personalized problem selection enhances student practice in tutoring systems. Prior research has focused on transparent problem selection that supports learner control but rarely engages learners in selecting practice materials. We explored how different levels of control (i.e., full AI control, shared control, and full learner control), combined…
Descriptors: Intelligent Tutoring Systems, Artificial Intelligence, Learner Controlled Instruction, Learning Analytics
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Carl Boel; Tijs Rotsaert; Martin Valcke; Tammy Schellens – Journal of Computer Assisted Learning, 2025
Background: As immersive virtual reality (IVR) is increasingly being used by teachers worldwide, it becomes pressing to investigate how this technology can foster learning processes. Several authors have pointed to this need, as results on the effectiveness of IVR for learning are still inconclusive. Objectives: To address this gap, we first…
Descriptors: Artificial Intelligence, Computer Simulation, Learning Strategies, Middle School Students
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Bin Meng; Fan Yang – International Journal of Web-Based Learning and Teaching Technologies, 2025
This paper proposes a computer-aided teaching model using knowledge graph construction and learning path recommendation. It first creates a multimodal knowledge graph to illustrate complex relationships among knowledge. Learning elements and sequences are then used to form time sequences stored as directed graphs, supporting flexible path…
Descriptors: Students, Teachers, Computer Assisted Instruction, Knowledge Representation
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Bin Liu; Yuanyuan Liao – Education and Information Technologies, 2025
The rapid advancement of generative AI technologies is increasingly accompanied by their broader application across various sectors, particularly within creative industries. In this study, IBM Watson BEAT software, based on generative AI technology, was tested as an educational tool in the process of teaching music composition theory to flute…
Descriptors: Artificial Intelligence, Technology Uses in Education, Technology Integration, Educational Technology
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Matthew Moreno; Keerat Grewal; Maria Cutumisu; Jason M. Harley – Educational Psychology Review, 2025
Medical simulations allow medical trainees to work within teams to develop their self-regulated learning (SRL) and socially shared regulated learning (SSRL) skills. These skills are imperative in optimizing performance and teamwork and could be reflected in physiological responses given by learners. This study examines how medical trainees'…
Descriptors: Artificial Intelligence, Technology Uses in Education, Prediction, Algorithms
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