Computer Science > Computers and Society
[Submitted on 15 Nov 2024 (v1), last revised 18 Nov 2024 (this version, v2)]
Title:Virtual Reality in Teacher Education: Insights from Pre-Service Teachers in Resource-limited Regions
View PDF HTML (experimental)Abstract:This study explores the perceptions, challenges, and opportunities associated with using Virtual Reality (VR) as a tool in teacher education among pre-service teachers in a resource-limited setting. Utilizing a qualitative case study design, the study draws on the experiences and reflections of 36 Ghanaian pre-service teachers who engaged with VR in a facilitated lesson for the first time. Findings reveal that initial exposure to VR generated a positive perception, with participants highlighting VR's potential as an engaging and interactive tool that can support experiential learning. Notably, many participants saw the VR-facilitated lesson as a promising alternative to synchronous online learning, particularly for its ability to simulate in-person presentations. They believe VR's immersive capabilities could enhance both teacher preparation and learner engagement in ways that traditional teaching often does not, especially noting that VR has the potential of addressing expensive educational field trips. Despite these promising perceptions, participants identified key challenges, including limited infrastructure, unreliable internet connectivity, and insufficient access to VR equipment as perceived challenges that might hinder the integration of VR in a resource-limited region like Ghana. These findings offer significant implications for educational policymakers and institutions aiming to leverage VR to enhance teacher training and professional development in similar contexts to consider addressing the perceived challenges for successful VR integration in education. We recommend further empirical research be conducted involving pre-service teachers use of VR in their classrooms.
Submission history
From: Matthew Nyaaba [view email][v1] Fri, 15 Nov 2024 14:39:07 UTC (1,063 KB)
[v2] Mon, 18 Nov 2024 05:14:37 UTC (1,064 KB)
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