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Conference Paper: Needs Analysis and Prototype Evaluation of Student-facing la Dashboard for Virtual Reality Content Creation

TitleNeeds Analysis and Prototype Evaluation of Student-facing la Dashboard for Virtual Reality Content Creation
Authors
KeywordsDashboard
Needs analysis
Prototype evaluation
VR content creation
Issue Date2022
Citation
ACM International Conference Proceeding Series, 2022, p. 444-450 How to Cite?
AbstractBeing a promising constructionist pedagogy in recent years, maker education empowers students to take agency of their learning process through constructing both knowledge and real-world physical or digital products and fosters peer interactions for collective innovation. Learning Analytics (LA) excels at generating personalized, fine-grained feedback in near real-time and holds much potential in supporting process-oriented and peer-supported learning activities, including maker activities. In the context of virtual reality (VR) content creation for cultural heritage education, this study qualitatively solicited 27 students' needs on progress monitoring, reflection, and feedback during their making process. Findings have inspired the prototype design of a student-facing LA dashboard (LAVR). Leveraging multimodal learning analytics (MmLA) such as text and audio analytics to fulfill students' needs, the prototype has various features and functions including automatic task reminders, content quality detection, and real-time feedback on quality of audio-visual elements. A preliminary evaluation of the prototype with 10 students confirms its potential in supporting students' self-regulated learning during the making process and for improving the quality of VR content. Implications on LA design for supporting maker education are discussed. Future work is planned to include implementation and evaluation of the dashboard in classrooms.
Persistent Identifierhttp://hdl.handle.net/10722/352276

 

DC FieldValueLanguage
dc.contributor.authorTzi-Dong Ng, Jeremy-
dc.contributor.authorWang, Zuo-
dc.contributor.authorHu, Xiao-
dc.date.accessioned2024-12-16T03:57:44Z-
dc.date.available2024-12-16T03:57:44Z-
dc.date.issued2022-
dc.identifier.citationACM International Conference Proceeding Series, 2022, p. 444-450-
dc.identifier.urihttp://hdl.handle.net/10722/352276-
dc.description.abstractBeing a promising constructionist pedagogy in recent years, maker education empowers students to take agency of their learning process through constructing both knowledge and real-world physical or digital products and fosters peer interactions for collective innovation. Learning Analytics (LA) excels at generating personalized, fine-grained feedback in near real-time and holds much potential in supporting process-oriented and peer-supported learning activities, including maker activities. In the context of virtual reality (VR) content creation for cultural heritage education, this study qualitatively solicited 27 students' needs on progress monitoring, reflection, and feedback during their making process. Findings have inspired the prototype design of a student-facing LA dashboard (LAVR). Leveraging multimodal learning analytics (MmLA) such as text and audio analytics to fulfill students' needs, the prototype has various features and functions including automatic task reminders, content quality detection, and real-time feedback on quality of audio-visual elements. A preliminary evaluation of the prototype with 10 students confirms its potential in supporting students' self-regulated learning during the making process and for improving the quality of VR content. Implications on LA design for supporting maker education are discussed. Future work is planned to include implementation and evaluation of the dashboard in classrooms.-
dc.languageeng-
dc.relation.ispartofACM International Conference Proceeding Series-
dc.subjectDashboard-
dc.subjectNeeds analysis-
dc.subjectPrototype evaluation-
dc.subjectVR content creation-
dc.titleNeeds Analysis and Prototype Evaluation of Student-facing la Dashboard for Virtual Reality Content Creation-
dc.typeConference_Paper-
dc.description.naturelink_to_subscribed_fulltext-
dc.identifier.doi10.1145/3506860.3506880-
dc.identifier.scopuseid_2-s2.0-85126194798-
dc.identifier.spage444-
dc.identifier.epage450-

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