Year: 2025
Type: preprint
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.
Source: arXiv (Cornell University)
Authors: Samant, Yashad, Becker, Lee, Hellman, Scott, Behan, Bradley, Hughes, Sarah, Southerland, Joshua
Language: English
Subfield: Safety Research
Field: Social Sciences
Domain: Social Sciences
SDG: Quality education
Open Access status: green
OpenAlex ID: W4417065210