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arXiv · 2509.08355

Automatic Detection of Inauthentic Templated Responses in English Language Assessments

Yashad Samant·Lee Becker·Scott Hellman·Bradley Behan·Sarah Hughes·Joshua Southerland
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Abstract

In high-stakes English Language Assessments, low-skill test takers may employ memorized materials called ``templates'' on essay questions to ``game'' or fool the automated scoring system. In this study, we introduce the automated detection of inauthentic, templated responses (AuDITR) task, describe a machine learning-based approach to this task and illustrate the importance of regularly updating these models in production.

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Yashad Samant, Lee Becker, Scott Hellman, Bradley Behan, Sarah Hughes, Joshua Southerland. 2025-09-10. Automatic Detection of Inauthentic Templated Responses in English Language Assessments. https://arxiv.org/abs/2509.08355

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