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January 25, 20260 citationsOpen Access

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

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AJAswin Kumar JanakiramanTHTaha HassanSLShenglin Li

Key Points

  • The research aims to develop an AI-powered system that automates the collection and annotation of data-driven stories for educational purposes.
  • Developed an AI-driven agent for curating data stories.
  • Used automated classification techniques to organize stories.
  • Conducted narrative analysis to improve story relevancy for teaching activities.
  • Significantly reduced preparation time for instructors.
  • Increased the diversity and quality of curated data stories.
  • Achieved better pedagogical alignment with teaching objectives.

Abstract

This 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.

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Cite This Study

Janakiraman et al. (2026) studied this question.

synapsesocial.com/papers/6975b1eafeba4585c2d6d777https://doi.org/10.13016/m2ckr3-5zfq
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