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Multimedia learning analytics feedback in simulation-based training: A brief review

Le, Lai Hoang, Nguyen, Hoang D., Crane, Martin orcid logoORCID: 0000-0001-7598-3126 and Mai, Tai T. orcid logoORCID: 0000-0001-6657-0872 (2024) Multimedia learning analytics feedback in simulation-based training: A brief review. In: The 1st ACM Workshop on AI-Powered Q&A Systems for Multimedia (AIQAM ’24), 10-14 Jun 2024, Phuket, Thailand.

Abstract
Learning analytics has gained significant attention in recent years, particularly in the healthcare field. This area of re- search 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 re- cipients, 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.
Metadata
Item Type:Conference or Workshop Item (Paper)
Event Type:Workshop
Refereed:Yes
Uncontrolled Keywords:Computer-Assisted Instruction, Learning analytics, Simulation-based learning, Multimedia feedback
Subjects:Computer Science > Artificial intelligence
Social Sciences > Educational technology
DCU Faculties and Centres:DCU Faculties and Schools > Faculty of Engineering and Computing > School of Computing
Research Institutes and Centres > Scientific Computing and Complex Systems Modelling (Sci-Sym)
Research Institutes and Centres > ADAPT
Publisher:ACM
Funders:SFI Centre for Research Training in Artificial Intelligence under grant number 18/CRT/6223 (Lai Hoang Le)., SFI under Grant number 12/RC/2289-P2 at Insight, the SFI Research Centre for Data Analytics at UCC (Hoang D. Nguyen), SFI under Grant Agreement No. 13/RC/2106_P2 at the ADAPT SFI Research Centre at DCU, funded by SFI through the SFI Research Centres Programme (in part, Tai Tan Mai & Martin Crane)
ID Code:30005
Deposited On:28 May 2024 10:29 by Martin Crane . Last Modified 01 Jul 2024 04:30
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