POSSIBILITIES OF QUANTITATIVE ANALYSIS OF HYPSOGRAPHY EDUCATION PROCESS IN COLLABORATIVE IMMERSIVE VIRTUAL REALITY
| Authors | |
|---|---|
| Year of publication | 2020 |
| Type | Article in Proceedings |
| Conference | 8th International Conference on Cartography & GIS: PROCEEDINGS VOL.1 |
| MU Faculty or unit | |
| Citation | |
| Web | https://iccgis2020.cartography-gis.com/8ICCGIS-Vol1/8ICCGIS_Proceedings_Vol1_2020.pdf |
| Keywords | immersive virtual reality; visual perception; eye tracking; education; interaction; measurement; behavior tracking |
| Description | In 2019, a transdisciplinary team at Masaryk University, Brno, CZ, developed a solution for collaborative education of hypsography in immersive virtual reality (collaborative immersive virtual environment, or CIVE). Its primary purpose was to help its users understand and apply the acquired knowledge of the principle of contour lines, which was achieved by solving map-based tasks together in pairs. Pilot use of the environment had been a subject of qualitative analysis, which allowed in depth insight into the users' experience, means of collaboration and communication, and cognitive processing. (Šašinka et al., 2019) After we examined thoroughly what the participants were going through, another research challenge has occurred: to identify and measure relevant objective variables on a quantitative level. Complex behaviour is difficult to crumble into well observable and well measurable variables that may be later analysed, especially in the setting pair (or group) collaboration in virtual space, where both interactions with other users and with the elements of the environment may be significant. The aim of this paper is to present a conception for quantitative analysis of the educational process in immersive virtual environment in the context of hypsographic task solving. That includes identification of relevant phenomena to focus on, definition of criteria according to which these phenomena will be assessed, and suggestion of means of statistical analysis of these data. Variables to be observed are for instance proximity between avatars (or users’ virtual personas), avatars’ locomotion, users’ oculomotor behaviour, speech production, and more. This conception may serve for further analysis of social interaction and provides basis for our current research of cross-cultural differences. |
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