Multimedia learning analytics feedback in simulation-based training: A brief review
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Date
2024-06-10
Authors
Le, Lai Hoang
Nguyen, Hoang D.
Crane, Martin
Mai, Tai Tan
Journal Title
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Publisher
Association for Computing Machinery, Inc
Published Version
Abstract
Learning analytics has gained significant attention in recent years, particularly in the healthcare field. This area of research offers valuable insights to educators, students, and researchers to enhance the quality of education. One area of focus in learning analytics is how stakeholders provide feedback to each other during training in operating theatres. With the availability of diverse multimedia elements, such as text, images, and spoken language, as data, employing effective feedback methods can bring substantial benefits to teachers, students, and researchers. This study synthesizes various approaches that apply multimedia to provide feedback in teaching, comparing and exploring their potential application in simulation-based medical training. The feasibility of input data, the effectiveness of feedback on recipients, and the AI method of generating or synthesizing feedback using existing data efficiency are also discussed in line with ethical standards. Finally, a multimedia feedback framework is proposed, which utilizes diverse multimedia formats and can be effectively implemented in various real-world scenarios.
Description
© 2024, Owner/Author.
Keywords
SDG 4 - Quality Education , Learning analytics , Multimedia feedback , Simulation-based learning , [ComputerScience] , Computer Graphics and Computer-Aided Design , Human-Computer Interaction , Software
Citation
Le, L H, Nguyen, H D, Crane, M & Mai, T T 2024, Multimedia learning analytics feedback in simulation-based training: A brief review. in AIQAM 2024 - Proceedings of the 1st ACM Workshop on AI-powered Question Answering Systems for Multimedia, Phuket, Thailand, 10 June 2024. AIQAM 2024 - Proceedings of the 1st ACM Workshop on AI-powered Question Answering Systems for Multimedia, Association for Computing Machinery, Inc, pp. 25-30, 1st ACM Workshop on AI-powered Question Answering Systems for Multimedia, AIQAM 2024, Phuket, Thailand, 10/06/24. https://doi.org/10.1145/3643479.3662053
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