The Evaluations Gap: Benchmarking AI for Effective Language Education

Existing AI evaluations in education typically focus on narrow tasks like exam accuracy or mistake identification, but effective language teaching requires nuanced pedagogical methodology that current benchmarks fail to capture. This mismatch leaves educators, institutions, and learners unable to make informed decisions about AI adoption, potentially undermining learning outcomes and wasting resources.

Oxford University Press are developing "ELT-Bench" to address this critical gap and standardize the testing of AI in language education. Rather than measuring what AI systems can do in isolation, ELT-Bench measures their capabilities to perform tasks across the full spectrum of competencies required of a "learning experience designer" in English Language Teaching (ELT), grounded in established teaching frameworks that ensure practical relevance to real-world classroom contexts.

ELT-Bench offers a pathway to accelerate the development of effective AI-powered educational solutions, ultimately seeking to improve learning outcomes for millions of language learners worldwide.

View the presentation in full here:

Edgell, J. (2025). The Evaluations Gap: Benchmarking AI for Effective Language Education. AIEOU Inaugural Conference, University of Oxford. Zenodo. https://doi.org/10.5281/zenodo.17537892

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