AI in Foreign Language Assessment

Abstract

AI is reshaping language assessments across diverse classrooms, pushing forward a three-layer setup—Technological Validity, Pedagogical Alignment, and Ethical & Contextual Fairness to juggle automation with real evaluation in foreign language assessment (FLA). No one-size-fits-all fix here, discussion digs into 2024 chats with ESL instructors in multilingual setups in Southeast Asia, using tools like ChatGPT's tuned models and Grammarly's adaptive scoring, backed by fresh research. Cultural skew, ethical hiccups, and teaching mismatches linger. It needs human oversight and feedback loops that adapt to learners' shifting needs. The chapter hands practical tips to educators, developers, and policymakers, zeroing in on openness, cultural tune-in, and better reach for learners in tight-budget spots. Looking ahead, it pushes for inclusive AI rules and policies that keep fairness front and center in AI-driven language tests.

Ähnliche Arbeiten