Understanding Academic Engagement and Context Through Multimodal Data

dc.contributor.author Kong , Runzhi
dc.contributor.author Hu, Xiao
dc.contributor.author Yuen, Allan H.K
dc.date.accessioned 2020-01-04T07:51:05Z
dc.date.available 2020-01-04T07:51:05Z
dc.date.issued 2020-01-07
dc.description.abstract The Internet has penetrated the life of adolescents and become a new space for learning, socializing and entertainment. Physical exercise and sleep remain crucial for the development of adolescents. However, the influence of these critical contextual factors on learning and life is insufficiently explored, partially due to the difficulty of measuring these factors. To bridge the gap, a semi-automated Day Reconstruction Method was proposed which leverages 24-hour multimodal data collected by smart wristband (Fitbit Versa), paired mobile phone (Red Mi 6), and time management application (RescueTime). A pilot study was conducted to verify the feasibility of this proposed method and is reported in this paper. As academic engagement among adolescents is widely concerned by stakeholders, this pilot study also explores the relationship between the aforementioned contextual factors and academic engagement. With some interesting patterns, revealed, this study contributes to furthering our understanding of how context shapes adolescents’ academic engagement using a more objective and nonintrusive method.
dc.format.extent 9 pages
dc.identifier.doi 10.24251/HICSS.2020.411
dc.identifier.isbn 978-0-9981331-3-3
dc.identifier.uri http://hdl.handle.net/10125/64153
dc.language.iso eng
dc.relation.ispartof Proceedings of the 53rd Hawaii International Conference on System Sciences
dc.rights Attribution-NonCommercial-NoDerivatives 4.0 International
dc.rights.uri https://creativecommons.org/licenses/by-nc-nd/4.0/
dc.subject Design and Application of Body Sensor Systems in Healthcare
dc.subject academic engagement
dc.subject context
dc.subject internet use
dc.subject multimodal data
dc.subject physical exercise
dc.subject sleep
dc.title Understanding Academic Engagement and Context Through Multimodal Data
dc.type Conference Paper
dc.type.dcmi Text
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