CASTCurate: An Agentic System to Accelerate the Collection and Annotation of Data-Driven Stories

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dc.contributor.authorJanakiraman, Aswin
dc.contributor.authorHassan, Taha
dc.contributor.authorLi, Shenglin
dc.contributor.authorChen, Lujie Karen
dc.contributor.authorGong, Jiaqi
dc.date.accessioned2026-01-22T16:18:58Z
dc.date.issued2026
dc.descriptionSpecial Interest Group on Computer Science Education (SIGCSE),February 18 - 21, 2026,Missouri,USA
dc.description.abstractThis study introduces an AI-powered data storytelling agent designed to support data science educators by automatically curating high-quality, real-world data stories. The system streamlines the discovery of relevant instructional examples for specific teaching activities, including assignments, quizzes, classroom discussions, and case studies, by utilizing automated classification and narrative analysis. Our prototype significantly reduces instructor preparation time while improving the diversity, quality, and pedagogical alignment of curated stories. This innovation enables educators to more efficiently source, annotate, and deploy impactful data narratives tailored to their teaching and research objectives.
dc.description.urihttps://people.cs.vt.edu/taha/pdfs/ds_curation.pdf
dc.format.extent2 pages
dc.genrejournal articles
dc.genrepreprints
dc.identifierdoi:10.13016/m2ckr3-5zfq
dc.identifier.urihttps://doi.org/10.1145/3770761.3777345
dc.identifier.urihttp://hdl.handle.net/11603/41523
dc.language.isoen
dc.relation.isAvailableAtThe University of Maryland, Baltimore County (UMBC)
dc.relation.ispartofUMBC Information Systems Department
dc.relation.ispartofUMBC Faculty Collection
dc.relation.ispartofUMBC Student Collection
dc.relation.ispartofUMBC Center for Real-time Distributed Sensing and Autonomy
dc.rightsAttribution-NonCommercial-NoDerivatives 4.0 International
dc.rights.urihttps://creativecommons.org/licenses/by-nc-nd/4.0/deed.en
dc.subjectUMBC Lab for Informatics for Human Flourishing
dc.titleCASTCurate: An Agentic System to Accelerate the Collection and Annotation of Data-Driven Stories
dc.typeText
dcterms.creatorhttps://orcid.org/0000-0002-7185-8405
dcterms.creatorhttps://orcid.org/0009-0000-6282-5102

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