An AI-Driven Approach to TIMSS Item Verification and Alignment

Bezirhan, Ummugul von Davier, Matthias
(2026)
This study investigates the feasibility of using artificial intelligence (AI) to automate the alignment of assessment items with the Trends in International Mathematics and Science Study (TIMSS) framework. Specifically, it evaluates prompt-based large language models (LLMs) and supervised machine learning approaches across three classification dimensions: content domain, cognitive domain, and item difficulty.