{"@context":{"@vocab":"https://cir.nii.ac.jp/schema/1.0/","rdfs":"http://www.w3.org/2000/01/rdf-schema#","dc":"http://purl.org/dc/elements/1.1/","dcterms":"http://purl.org/dc/terms/","foaf":"http://xmlns.com/foaf/0.1/","prism":"http://prismstandard.org/namespaces/basic/2.0/","cinii":"http://ci.nii.ac.jp/ns/1.0/","datacite":"https://schema.datacite.org/meta/kernel-4/","ndl":"http://ndl.go.jp/dcndl/terms/","jpcoar":"https://github.com/JPCOAR/schema/blob/master/2.0/"},"@id":"https://cir.nii.ac.jp/crid/1390023229739783680.json","@type":"Article","productIdentifier":[{"identifier":{"@type":"DOI","@value":"10.60401/ijabc.48"}}],"dc:title":[{"@language":"en","@value":"TrackThinkDashboard: Understanding Student Self-Regulated Learning in Programming Study"}],"dc:language":"en","description":[{"type":"abstract","notation":[{"@language":"en","@value":"In programming education, fostering self-regulated learning (SRL) skills is essential for both students and teachers. This paper introduces Track-ThinkDashboard, an application designed to visualize the learning workflow by combining web browsing and programming logs in one unified view. The system aims to (1) help students monitor and reflect on their problem-solving processes, identify knowledge gaps, and cultivate effective SRL strategies, and (2) enable teachers to identify at-risk learners more effectively and provide targeted, data-driven guidance. We conducted a study with 33 participants (32 male, one female) from Japanese universities—some with prior programming instruction and some without—to explore differences in web browsing and coding patterns. The dashboards revealed multiple learning approaches (e.g., try-and-error, try-and-search, and more) and highlighted how domain knowledge influenced overall activity flow. We discuss how this visualization can be used continuously or in one-off experiments, the privacy considerations involved, and opportunities for expanding data sources for richer behavioral insights."}],"abstractLicenseFlag":"allow"}],"creator":[{"@id":"https://cir.nii.ac.jp/crid/1410023229739783681","@type":"Researcher","foaf:name":[{"@language":"en","@value":"Watanabe Ko"}],"jpcoar:affiliationName":[{"@language":"en","@value":"German Research Centre for Artificial Intelligence"}]},{"@id":"https://cir.nii.ac.jp/crid/1410023229739783684","@type":"Researcher","foaf:name":[{"@language":"en","@value":"Matsuda Yuki"}],"jpcoar:affiliationName":[{"@language":"en","@value":"Okayama University"},{"@language":"ja","@value":"岡山大学"}]},{"@id":"https://cir.nii.ac.jp/crid/1410023229739783682","@type":"Researcher","foaf:name":[{"@language":"en","@value":"Nakamura Yugo"}],"jpcoar:affiliationName":[{"@language":"en","@value":"Kyushu University"},{"@language":"ja","@value":"九州大学"}]},{"@id":"https://cir.nii.ac.jp/crid/1410023229739783683","@type":"Researcher","foaf:name":[{"@language":"en","@value":"Arakawa  Yutaka"}],"jpcoar:affiliationName":[{"@language":"en","@value":"Kyushu University"},{"@language":"ja","@value":"九州大学"}]},{"@id":"https://cir.nii.ac.jp/crid/1410023229739783680","@type":"Researcher","foaf:name":[{"@language":"en","@value":"Ishimaru Shoya"}],"jpcoar:affiliationName":[{"@language":"en","@value":"Osaka Metropolitan University"},{"@language":"ja","@value":"大阪公立大学"}]}],"publication":{"publicationIdentifier":[{"@type":"EISSN","@value":"27592871"}],"prism:publicationName":[{"@language":"ja","@value":"International Journal of Activity and Behavior Computing"},{"@language":"en","@value":"International Journal of Activity and Behavior Computing"},{"@language":"ja","@value":"IJABC"},{"@language":"en","@value":"IJABC"}],"dc:publisher":[{"@language":"en","@value":"Care XDX Center, Kyushu Institute of Technology"},{"@language":"ja","@value":"九州工業大学ケアXDXセンター"}],"prism:publicationDate":"2025-07-01","prism:volume":"2025","prism:number":"1","prism:startingPage":"1","prism:endingPage":"17"},"availableAt":"2025-07-01","dataSourceIdentifier":[{"@type":"JALC","@value":"oai:japanlinkcenter.org:2014130115"}]}