Virtual Reality, Eye Tracking and Machine Learning: Analysis of Learning Outcomes in Off-the-Shelve VR-Software
dc.contributor.author | Tümler, Johannes | |
dc.contributor.author | Erazo Sanchez, Juan Enrique | |
dc.contributor.author | Hänig, Christian | |
dc.contributor.editor | Röpke, René | |
dc.contributor.editor | Schroeder, Ulrik | |
dc.date.accessioned | 2023-08-30T09:09:36Z | |
dc.date.available | 2023-08-30T09:09:36Z | |
dc.date.issued | 2023 | |
dc.description.abstract | The combination of Virtual Reality (VR) and eye tracking allows to analyze how students use the presented VR content for learning. Here, we propose a novel approach to analyze eye tracking data in VR, even if no access to the VR software source code is given. This proof-of-concept leverages image classification methods to identify objects that captured the students' attention in VR. The method allows analysis of individual learning strategies and correlate those to individual learning outcomes. | en |
dc.identifier.doi | 10.18420/delfi2023-32 | |
dc.identifier.isbn | 978-3-88579-732-6 | |
dc.identifier.pissn | 1617-5468 | |
dc.identifier.uri | https://dl.gi.de/handle/20.500.12116/42192 | |
dc.language.iso | en | |
dc.publisher | Gesellschaft für Informatik e.V. | |
dc.relation.ispartof | 21. Fachtagung Bildungstechnologien (DELFI) | |
dc.relation.ispartofseries | Lecture Notes in Informatics (LNI) - Proceedings, Volume P-322 | |
dc.subject | Virtual Reality | |
dc.subject | Education | |
dc.subject | Eye Tracking | |
dc.subject | Machine Learning | |
dc.subject | Image Classification | |
dc.title | Virtual Reality, Eye Tracking and Machine Learning: Analysis of Learning Outcomes in Off-the-Shelve VR-Software | en |
dc.type | Text/Conference Paper | |
gi.citation.endPage | 204 | |
gi.citation.publisherPlace | Bonn | |
gi.citation.startPage | 199 | |
gi.conference.date | 11.-13. September 2023 | |
gi.conference.location | Aachen | |
gi.conference.review | full | |
gi.conference.sessiontitle | Conversational Systems und Virtual Reality |
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