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Title: Towards Collaborative Immersive Qualitative Analysis
Authors: Davidsen, Jacob
McIlvenny, Paul
Keywords: CSCL
Issue Date: 2022
Publisher: International Society of the Learning Sciences
Citation: Davidsen, J. & McIlvenny, P. (2022). Towards collaborative immersive qualitative analysis. In Weinberger, A. Chen, W., Hernández-Leo, D., & Chen, B. (Eds.), Proceedings of the 15th International Conference on Computer-Supported Collaborative Learning - CSCL 2022 (pp. 304-307). International Society of the Learning Sciences.
Abstract: In this paper, we explore how researchers in Immersive Virtual Reality (IVR) collaboratively analyse how copresent students interactively identify problems based on video data recorded with multiple 2D and 360° cameras. We are working with a double data set – the original recordings and a recording of the analysis performed in IVR. The focus is on how IVR can be used to analyse 360° video data by a distributed team of researchers. We outline a new methodological approach called Collaborative Immersive Qualitative Analysis (CIQA). In contrast to the branch of work in CSCL that focuses on machine analytics, we present a methodology and software that allows researchers to inhabit the captured scene with tools that encourage a more immersive take on interaction analysis. Until now, IVR has primarily been used as a tool for individual cognitive training, but we suggest that IVR can be used to support a collaborative, volumetric research infrastructure.
Description: Short Paper
Appears in Collections:ISLS Annual Meeting 2022

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