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[Vol.24 No.2] Sungtae LIM, Eunhee KIM, Hoseung BYUN (2023) Learning Analytics Framework on Metaverse
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  • 2023-10-31 01:35:37

The recent development of metaverse-related technology has led to efforts to overcome the limitations of time and space in education by creating a virtual educational environment. To make use of this platform efficiently, applying learning analytics has been proposed as an optimal instructional and learning decision support approach to address these issues by identifying specific rules and patterns generated from learning data, and providing a systematic framework as a guideline to instructors. To achieve this, we employed an inductive, bottom-up approach for framework modeling. During the modeling process, based on the activity system model, we specifically derived the fundamental components of the learning analytics framework centered on learning activities and their contexts. We developed a prototype of the framework through deduplication, categorization, and proceduralization from the components, and refined the learning analytics framework into a 7-stage framework suitable for application in the metaverse through 3 steps of Delphi surveys. Lastly, through a framework model evaluation consisting of seven items, we validated the metaverse learning analytics framework, ensuring its validity.

 

Keywords : Metaverse, Virtual world, Learning analytics, Learning analytics framework 

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내용

이전글 [Vol.24 No.2] Songhee KIM, Jaejin LEE (2023) Examining High School Students’ BYOD Use under Office of Education-led Policy: Insights from the Technology Acceptance Model
다음글 [Vol.24 No.2] Inah KO, Yeon KIM (2023) The Impact of How Often Students Use Mobile Devices on Their Perceptions of the Usefulness and Convenience of the Devices
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