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Leveraging Large Language Models to Generate Course-Specific Semantically Annotated Learning Objects
Peer reviewed
Direct linkDominic Lohr; Marc Berges; Abhishek Chugh; Michael Kohlhase; Dennis Müller – Journal of Computer Assisted Learning, 2025
Background: Over the past few decades, the process and methodology of automatic question generation (AQG) have undergone significant transformations. Recent progress in generative natural language models has opened up new potential in the generation of educational content. Objectives: This paper explores the potential of large language models…
Descriptors: Resource Units, Semantics, Automation, Questioning Techniques
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
