ChatGPT-supported formative assessment in interpreter education: validity of automated ratings and perceived quality of diagnostic feedback - Liu, Wenjing; Pagano, Adriana Silvina (Cadernos de Linguagem e Sociedade, 2026)
Formative assessment plays a critical role in teaching and learning. Recent advances in large language models (LLMs) have enabled their application as automated assessment systems and feedback providers. This study explores the validity of ChatGPT-based assessment and the perceived quality of its feedback in interpreter education. To this end, ChatGPT-4o was used to assess 60 Chinese–Portuguese simultaneous interpreting tasks, producing rubric-based quantitative ratings and qualitative diagnostic feedback. To examine its effectiveness, three types of validity (concurrent, predictive, and know-group) were examined by comparing ChatGPT-generated scores with those of nine trained human raters. A post-hoc questionnaire was also administered to collect raters’ subjective perceptions of the feedback. Results show strong alignment between the model and human scores, with ChatGPT demonstrating robust predictive power and discriminative ability. Raters viewed the feedback favorably and supported its use as a complement to teacher feedback, highlighting the pedagogical value of LLMs in interpreter training.