https://scholars.lib.ntu.edu.tw/handle/123456789/638510
DC 欄位 | 值 | 語言 |
---|---|---|
dc.contributor.author | Lin, Song Yi | en_US |
dc.contributor.author | MEILUN SHIH | en_US |
dc.contributor.author | HSIN-MU TSAI | en_US |
dc.date.accessioned | 2024-01-16T00:40:40Z | - |
dc.date.available | 2024-01-16T00:40:40Z | - |
dc.date.issued | 2023-12-01 | - |
dc.identifier.isbn | 9786269689026 | - |
dc.identifier.uri | https://scholars.lib.ntu.edu.tw/handle/123456789/638510 | - |
dc.description.abstract | Measuring students' mental states, such as their understanding during class, helps improve learning efficiency. Automatic approaches implement this idea without interrupting the class by sensing students' reactions through wearable sensors or cameras and applying machine learning models to analyze the data. However, most of the previous works lack adequate annotations of understanding based on students' reactions compared to the number of concepts conveyed during lessons. This paper proposes a scalable framework for efficiently constructing and annotating datasets. Additionally, we have collected a dataset consisting of posture, facial expression, and eye movement features, and benchmarked it for measuring understanding. The results show promising accuracy of 80% even in cases where not all features are available, demonstrating the potential for widespread adoption of the proposed framework. | en_US |
dc.relation.ispartof | 31st International Conference on Computers in Education, ICCE 2023 - Proceedings | en_US |
dc.subject | machine learning | measurement of understanding | Video-based learning | en_US |
dc.title | Measuring Understanding in Video-Based Learning | en_US |
dc.type | conference paper | en_US |
dc.identifier.scopus | 2-s2.0-85181774758 | - |
dc.identifier.url | https://api.elsevier.com/content/abstract/scopus_id/85181774758 | - |
dc.relation.pages | 240 | en_US |
dc.relation.journalvolume | 2 | en_US |
dc.relation.pageend | 248 | en_US |
item.openairetype | conference paper | - |
item.openairecristype | http://purl.org/coar/resource_type/c_5794 | - |
item.fulltext | no fulltext | - |
item.grantfulltext | none | - |
item.cerifentitytype | Publications | - |
crisitem.author.dept | Liberal Education Section | - |
crisitem.author.dept | Networking and Multimedia | - |
crisitem.author.dept | Computer Science and Information Engineering | - |
crisitem.author.dept | Intel-NTU Connected Context Computing Center | - |
crisitem.author.orcid | 0000-0002-7884-433X | - |
crisitem.author.orcid | 0000-0003-1106-0722 | - |
crisitem.author.parentorg | Others: Center for General Education | - |
crisitem.author.parentorg | College of Electrical Engineering and Computer Science | - |
crisitem.author.parentorg | College of Electrical Engineering and Computer Science | - |
crisitem.author.parentorg | Others: University-Level Research Centers | - |
crisitem.author.parentorg | Others: International Research Centers | - |
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