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Leveraging Large Language Models to Generate Course-Specific Semantically Annotated Learning Objects
Dominic 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
Robert O. Davis; Yong-Jik Lee; Joseph Vincent; Lili Wan – Journal of Computer Assisted Learning, 2024
Background: Gestures are an integral component in human-to-human communication when the speaker is visually present to the listener. In the past several years, research has examined how computer-generated pedagogical agents can be designed to perform the four main gesture types and what this means for agent persona and learning outcomes. The…
Descriptors: Nonverbal Communication, Interpersonal Communication, Multimedia Instruction, Imagery
Robert F. Siegle; Scotty D. Craig – Journal of Computer Assisted Learning, 2024
Background: The voices virtual on-screen characters use has been shown to impact learning and perception outcomes. Recent replication research on these voices showed that synthetic voices were not a detriment if produced by a high-quality engine with clear articulation. The current manuscript examines previous accent research that utilized now…
Descriptors: Acoustics, Artificial Intelligence, Electronic Learning, Quality Assurance
Rashmi Khazanchi; Daniele Di Mitri; Hendrik Drachsler – Journal of Computer Assisted Learning, 2025
Background: Despite educational advances, poor mathematics achievement persists among K-12 students, particularly in rural areas with limited resources and skilled teachers. Artificial Intelligence (AI) based systems have increasingly been adopted to support the diverse learning needs of students and have been shown to enhance mathematics…
Descriptors: Mathematics Achievement, Rural Areas, Artificial Intelligence, Individualized Instruction
Kun Huang; Ching-Huei Chen – Journal of Computer Assisted Learning, 2025
Background: Digital game-based learning (DGBL) has shown promise in enhancing learning and motivation, with appropriate scaffolding playing a crucial role in facilitating student inquiries and knowledge acquisition through science games. While scaffolding is generally effective in promoting learning in DGBL, there is variability among different…
Descriptors: Video Technology, Educational Technology, Artificial Intelligence, Computer Mediated Communication
Peer reviewedScaife, M. – Journal of Computer Assisted Learning, 1989
Discusses information technology and its effects on developmental psychology and children's education. Topics discussed include a theory of child-computer interaction (CCI); programing; communication and computers, including electronic mail; cognitive science; artificial intelligence; modeling the user-system interaction; and the future of…
Descriptors: Artificial Intelligence, Child Development, Cognitive Processes, Computer Assisted Instruction

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