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        <title>Resilience Infrastructure for Conversational AI-Based Educational Applications</title>
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    <abstract>Educational applications using conversational AI built on LLMs are hard to evaluate reliably because outputs vary unpredictably each turn, posing validity, reliability, fairness, and safety risks. We present a four-stage framework that combines automated and human testing to determine operational preparedness and continuously monitor deployed systems. The application of this resilience infrastructure framework is demonstrated in a case study of a conversation-based formative assessment tool for medical students to practice doctor-patient communication skills.</abstract>
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%0 Conference Proceedings
%T Resilience Infrastructure for Conversational AI-Based Educational Applications
%A Emerson, Andrew
%A Evanini, Keelan
%A Frome, Kevin
%A Ha, Le An
%A Baldwin, Peter
%Y Wilson, Joshua
%Y Ormerod, Christopher
%Y Beiting-Parrish, Magdalen
%S Proceedings of the Artificial Intelligence in Measurement and Education Conference (AIME-Con): Coordinated Session Papers
%D 2026
%8 October
%I National Council on Measurement in Education (NCME)
%C Wyndham Grand Pittsburgh Downtown, Pittsburgh, Pennsylvania, United States
%@ 979-8-9983004-2-4
%F emerson-etal-2026-resilience
%X Educational applications using conversational AI built on LLMs are hard to evaluate reliably because outputs vary unpredictably each turn, posing validity, reliability, fairness, and safety risks. We present a four-stage framework that combines automated and human testing to determine operational preparedness and continuously monitor deployed systems. The application of this resilience infrastructure framework is demonstrated in a case study of a conversation-based formative assessment tool for medical students to practice doctor-patient communication skills.
%U https://aclanthology.org/2026.aimecon-sessions.11/
%P 89-100

Markdown (Informal)

[Resilience Infrastructure for Conversational AI-Based Educational Applications](https://aclanthology.org/2026.aimecon-sessions.11/) (Emerson et al., AIME-Con 2026)

• Resilience Infrastructure for Conversational AI-Based Educational Applications (Emerson et al., AIME-Con 2026)

ACL

• Andrew Emerson, Keelan Evanini, Kevin Frome, Le An Ha, and Peter Baldwin. 2026. Resilience Infrastructure for Conversational AI-Based Educational Applications. In Proceedings of the Artificial Intelligence in Measurement and Education Conference (AIME-Con): Coordinated Session Papers, pages 89–100, Wyndham Grand Pittsburgh Downtown, Pittsburgh, Pennsylvania, United States. National Council on Measurement in Education (NCME).