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January 1, 2026

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

Aswin Kumar Janakiraman Taha Hassan Shenglin Li Lujie Chen Jiaqi Gong

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Key Points

The aim is to develop a system that streamlines the creation and annotation of data-oriented narratives in educational contexts.
Design an agentic system for interactive data collection
Integrate machine learning for improved annotation processes
Employ natural language processing to facilitate storytelling
Demonstrated faster story annotation compared to traditional methods
Showed increased engagement in educational contexts
Enhanced the quality of data-driven narratives

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Implication

This system accelerates the collection and annotation of data-driven stories, suggesting new opportunities for enhanced educational methods.

Abstract

Special Interest Group on Computer Science Education (SIGCSE),February 18 - 21, 2026,Missouri,USA

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Cite This Study

Janakiraman et al. (2026) studied this question.

synapsesocial.com/papers/6975b1a9feba4585c2d6d1ea https://doi.org/10.1145/3770761.3777345

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