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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
Shilpi Harnal; Gaurav Sharma; Anupriya; Anand Muni Mishra; Deepak Bagga; Nikhil Saini; Pankaj Kumar Goley; Kumar Anupam – Journal of Computer Assisted Learning, 2024
Background: An innovative and interactive real-world environment can be presented with augmented reality (AR) that comprises digital visual elements, audio, or other sensory information delivered via technology to enhance one's experience. AR has numerous potential applications in various everyday fields. The education sector is one such arena…
Descriptors: Bibliometrics, Computer Simulation, Artificial Intelligence, Educational Technology
Fountoukidou, Sofia; Matzat, Uwe; Ham, Jaap; Midden, Cees – Journal of Computer Assisted Learning, 2022
Background: Though pedagogical artificial agents are expected to play a crucial role in the years to come, earlier studies provide inconsistent results regarding their effect on learning. This might be because their potential for exhibiting subtle nonverbal behaviours we know from human teachers has been untapped. What is more, there is little…
Descriptors: Artificial Intelligence, Assistive Technology, Technology Uses in Education, Nonverbal Communication
Héctor J. Pijeira-Díaz; Shashank Subramanya; Janneke van de Pol; Anique de Bruin – Journal of Computer Assisted Learning, 2024
Background: When learning causal relations, completing causal diagrams enhances students' comprehension judgements to some extent. To potentially boost this effect, advances in natural language processing (NLP) enable real-time formative feedback based on the automated assessment of students' diagrams, which can involve the correctness of both the…
Descriptors: Learning Analytics, Automation, Student Evaluation, Causal Models
Zehang Xie; Xinzhu Wu; Yunxiang Xie – Journal of Computer Assisted Learning, 2024
Background: With the development of artificial intelligence (AI) technology, generative AI has been widely used in the field of education and represents a groundbreaking shift in overcoming the constraints of time and space within educational activities. However, previous literature has not paid enough attention to AI-involved teaching patterns,…
Descriptors: Longitudinal Studies, Undergraduate Students, Robotics, Technology Uses in Education
Fatimah H. Aldeeb; Omar M. Sallabi; Monther M. Elaish; Gwo-Jen Hwang – Journal of Computer Assisted Learning, 2024
Background: This paper examines the use of augmented reality (AR) as a concept-association tool in schools, with the aim of enhancing primary school students' learning outcomes and engagement. Conflicting findings exist in previous studies regarding the cognitive load of AR-enriched learning, with some reporting reduced load and others indicating…
Descriptors: Artificial Intelligence, Computer Software, Teaching Methods, Learning Processes