Personalized Generative AI in VR for Enhanced Engagement: Eye-Tracking Insights into Cultural Heritage Learning through Neapolitan Pizza Making
Virtual Reality (VR) and Generative Artificial Intelligence (Gen-AI) are transforming personalized learning, particularly in intangible cultural heritage (ICH) education. However, designing immersive experiences that enhance engagement without overwhelming learners presents a challenge. This study e...
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| creator | Lau, Ka Hei Carrie Sen, Sema Stark, Philipp Bozkir, Efe Kasneci, Enkelejda |
| description | Virtual Reality (VR) and Generative Artificial Intelligence (Gen-AI) are
transforming personalized learning, particularly in intangible cultural
heritage (ICH) education. However, designing immersive experiences that enhance
engagement without overwhelming learners presents a challenge. This study
examines the impact of personalized AI narration on user engagement and
attention in a VR environment through eye-tracking metrics. In a controlled
experiment with 54 participants, we explored three levels of personalization
(high, moderate, none) in a Neapolitan pizza-making task, measuring attention
and cognitive load through fixation duration, saccade duration, and pupil
diameter. Results indicate that high personalization increased engagement by
64.1% over no personalization (p < 0.001). Furthermore, regression analysis
reveals specific eye-tracking metrics significantly predict gameplay duration,
underscoring eye-tracking's potential to capture real-time engagement. These
findings support the use of eye-tracking to inform the development of adaptive
VR learning experiences. Future work may integrate subjective assessments to
better understand users' underlying motivations. |
| doi_str_mv | 10.48550/arxiv.2411.18438 |
| format | Article |
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transforming personalized learning, particularly in intangible cultural
heritage (ICH) education. However, designing immersive experiences that enhance
engagement without overwhelming learners presents a challenge. This study
examines the impact of personalized AI narration on user engagement and
attention in a VR environment through eye-tracking metrics. In a controlled
experiment with 54 participants, we explored three levels of personalization
(high, moderate, none) in a Neapolitan pizza-making task, measuring attention
and cognitive load through fixation duration, saccade duration, and pupil
diameter. Results indicate that high personalization increased engagement by
64.1% over no personalization (p < 0.001). Furthermore, regression analysis
reveals specific eye-tracking metrics significantly predict gameplay duration,
underscoring eye-tracking's potential to capture real-time engagement. These
findings support the use of eye-tracking to inform the development of adaptive
VR learning experiences. Future work may integrate subjective assessments to
better understand users' underlying motivations.</description><identifier>DOI: 10.48550/arxiv.2411.18438</identifier><language>eng</language><subject>Computer Science - Human-Computer Interaction</subject><creationdate>2024-11</creationdate><rights>http://arxiv.org/licenses/nonexclusive-distrib/1.0</rights><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><link.rule.ids>228,230,776,881</link.rule.ids><linktorsrc>$$Uhttps://arxiv.org/abs/2411.18438$$EView_record_in_Cornell_University$$FView_record_in_$$GCornell_University$$Hfree_for_read</linktorsrc><backlink>$$Uhttps://doi.org/10.48550/arXiv.2411.18438$$DView paper in arXiv$$Hfree_for_read</backlink></links><search><creatorcontrib>Lau, Ka Hei Carrie</creatorcontrib><creatorcontrib>Sen, Sema</creatorcontrib><creatorcontrib>Stark, Philipp</creatorcontrib><creatorcontrib>Bozkir, Efe</creatorcontrib><creatorcontrib>Kasneci, Enkelejda</creatorcontrib><title>Personalized Generative AI in VR for Enhanced Engagement: Eye-Tracking Insights into Cultural Heritage Learning through Neapolitan Pizza Making</title><description>Virtual Reality (VR) and Generative Artificial Intelligence (Gen-AI) are
transforming personalized learning, particularly in intangible cultural
heritage (ICH) education. However, designing immersive experiences that enhance
engagement without overwhelming learners presents a challenge. This study
examines the impact of personalized AI narration on user engagement and
attention in a VR environment through eye-tracking metrics. In a controlled
experiment with 54 participants, we explored three levels of personalization
(high, moderate, none) in a Neapolitan pizza-making task, measuring attention
and cognitive load through fixation duration, saccade duration, and pupil
diameter. Results indicate that high personalization increased engagement by
64.1% over no personalization (p < 0.001). Furthermore, regression analysis
reveals specific eye-tracking metrics significantly predict gameplay duration,
underscoring eye-tracking's potential to capture real-time engagement. These
findings support the use of eye-tracking to inform the development of adaptive
VR learning experiences. Future work may integrate subjective assessments to
better understand users' underlying motivations.</description><subject>Computer Science - Human-Computer Interaction</subject><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2024</creationdate><recordtype>article</recordtype><sourceid>GOX</sourceid><recordid>eNqFj82KwkAQhOfiQdQH8LT9AmbNGiF4WyT-gIqIeA2N206aHXukM5E1L7GvvIns3VMd6quiyphhPI6SdDodv6P-8D36SOI4itNkknbN75609IKOa_qCJQkpBr4TfK6BBU4HuHiFTAqUcwNkYtHSlSTMIHvQ6Kh4_maxsJaSbRHKJhQ8zCsXKkUHK1IOTQI2hCotGAr1lS1gR3jzrjEF9lzXCFtsi_qmc0FX0uBfe-ZtkR3nq9Fzen5TvqI-8vZC_rwweU38AR10U3Q</recordid><startdate>20241127</startdate><enddate>20241127</enddate><creator>Lau, Ka Hei Carrie</creator><creator>Sen, Sema</creator><creator>Stark, Philipp</creator><creator>Bozkir, Efe</creator><creator>Kasneci, Enkelejda</creator><scope>AKY</scope><scope>GOX</scope></search><sort><creationdate>20241127</creationdate><title>Personalized Generative AI in VR for Enhanced Engagement: Eye-Tracking Insights into Cultural Heritage Learning through Neapolitan Pizza Making</title><author>Lau, Ka Hei Carrie ; Sen, Sema ; Stark, Philipp ; Bozkir, Efe ; Kasneci, Enkelejda</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-arxiv_primary_2411_184383</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2024</creationdate><topic>Computer Science - Human-Computer Interaction</topic><toplevel>online_resources</toplevel><creatorcontrib>Lau, Ka Hei Carrie</creatorcontrib><creatorcontrib>Sen, Sema</creatorcontrib><creatorcontrib>Stark, Philipp</creatorcontrib><creatorcontrib>Bozkir, Efe</creatorcontrib><creatorcontrib>Kasneci, Enkelejda</creatorcontrib><collection>arXiv Computer Science</collection><collection>arXiv.org</collection></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext_linktorsrc</fulltext></delivery><addata><au>Lau, Ka Hei Carrie</au><au>Sen, Sema</au><au>Stark, Philipp</au><au>Bozkir, Efe</au><au>Kasneci, Enkelejda</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Personalized Generative AI in VR for Enhanced Engagement: Eye-Tracking Insights into Cultural Heritage Learning through Neapolitan Pizza Making</atitle><date>2024-11-27</date><risdate>2024</risdate><abstract>Virtual Reality (VR) and Generative Artificial Intelligence (Gen-AI) are
transforming personalized learning, particularly in intangible cultural
heritage (ICH) education. However, designing immersive experiences that enhance
engagement without overwhelming learners presents a challenge. This study
examines the impact of personalized AI narration on user engagement and
attention in a VR environment through eye-tracking metrics. In a controlled
experiment with 54 participants, we explored three levels of personalization
(high, moderate, none) in a Neapolitan pizza-making task, measuring attention
and cognitive load through fixation duration, saccade duration, and pupil
diameter. Results indicate that high personalization increased engagement by
64.1% over no personalization (p < 0.001). Furthermore, regression analysis
reveals specific eye-tracking metrics significantly predict gameplay duration,
underscoring eye-tracking's potential to capture real-time engagement. These
findings support the use of eye-tracking to inform the development of adaptive
VR learning experiences. Future work may integrate subjective assessments to
better understand users' underlying motivations.</abstract><doi>10.48550/arxiv.2411.18438</doi><oa>free_for_read</oa></addata></record> |
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| subjects | Computer Science - Human-Computer Interaction |
| title | Personalized Generative AI in VR for Enhanced Engagement: Eye-Tracking Insights into Cultural Heritage Learning through Neapolitan Pizza Making |
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