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Virtual Reality, Eye Tracking and Machine Learning: Analysis of Learning Outcomes in Off-the-Shelve VR-Software

dc.contributor.authorTümler, Johannes
dc.contributor.authorErazo Sanchez, Juan Enrique
dc.contributor.authorHänig, Christian
dc.contributor.editorRöpke, René
dc.contributor.editorSchroeder, Ulrik
dc.date.accessioned2023-08-30T09:09:36Z
dc.date.available2023-08-30T09:09:36Z
dc.date.issued2023
dc.description.abstractThe 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.doi10.18420/delfi2023-32
dc.identifier.isbn978-3-88579-732-6
dc.identifier.pissn1617-5468
dc.identifier.urihttps://dl.gi.de/handle/20.500.12116/42192
dc.language.isoen
dc.publisherGesellschaft für Informatik e.V.
dc.relation.ispartof21. Fachtagung Bildungstechnologien (DELFI)
dc.relation.ispartofseriesLecture Notes in Informatics (LNI) - Proceedings, Volume P-322
dc.subjectVirtual Reality
dc.subjectEducation
dc.subjectEye Tracking
dc.subjectMachine Learning
dc.subjectImage Classification
dc.titleVirtual Reality, Eye Tracking and Machine Learning: Analysis of Learning Outcomes in Off-the-Shelve VR-Softwareen
dc.typeText/Conference Paper
gi.citation.endPage204
gi.citation.publisherPlaceBonn
gi.citation.startPage199
gi.conference.date11.-13. September 2023
gi.conference.locationAachen
gi.conference.reviewfull
gi.conference.sessiontitleConversational Systems und Virtual Reality

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