ai-in-assessment
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- PaperLanguage Testing19 Jul 2026
Can an AI Agent Replace Human Examiners in High-Stakes Interactive Speaking Tests? A Debate
Jing Xu, Lynda Taylor, Xiaoming Xi, Yasin Karatay et al.
The paper presents arguments for and against replacing human examiners with AI agents in high-stakes interactive speaking tests, drawing on construct theory, practicality, washback, fairness, and ethics. It highlights the rapid advancement of GenAI and its integration into Spoken Dialogue Systems for language assessment, but maintains the debate is unresolved. The viewpoint emerged from a debate at the 2025 LTRC.
Original abstract
Generative artificial intelligence (GenAI) is advancing at a remarkable speed, and its promise in transforming current practice in language assessment has been articulated by applied linguistics researchers. An emerging application of GenAI is to integrate the technology into Spoken Dialogue Systems (SDSs) to simulate human interlocutors for the purpose of speaking practice or assessment. Despite rapid technological advances, the issue of whether an AI agent can replace a human examiner in one-on-one, high-stakes interactive speaking tests remains contentious. Building on a lively academic debate on this topic at the 2025 Language Testing Research Colloquium (LTRC) in Bangkok, this Viewpoint presents arguments both for and against this proposition in terms of construct theory, practicality, washback, fairness, ethical uses of AI, and so forth.
- PaperAssessing Writing18 Jul 2026
Modeling the reading-to-writing pipeline: Knowledge graph and LLM-based assessment framework for source-based writing
Byungyeon Yun, Miranda Moe, Lauren E. Flynn, Püren Öncel et al.
A framework using knowledge graphs and large language models assesses source-based writing by modeling the reading-to-writing pipeline.