🏷️ Concept
Language Learning
Language Learning — the study of how AI supports second language (L2) acquisition, writing development, and linguistic diversity in educational settings. AI in education research in this wiki spans AI interlocutors for spoken dialogue, automated writing evaluation for L2 learners, reading support, and concerns about language bias in AI scoring systems.
Language learning has emerged as a significant AI in education domain because language is inherently interactive — making it well-suited to conversational AI — and because AI's linguistic capabilities raise both opportunities (personalized language practice at scale) and risks (systematic bias against non-native language patterns). The articles in this wiki explore both sides of this equation.
AI as language tutor and interlocutor is the most developed theme. What Changes When the Interlocutor Is an AI? examines interactional fluency and linguistic uptake when L2 learners converse with AI versus humans. TACT provides pedagogically adaptive ESL tutoring. LLM Children Reading Story Generation explores AI-generated stories for children's reading development. These connect to Intelligent Tutoring and Generative AI.
Automated writing evaluation for L2 learners evaluates AI's ability to assess non-native writing. Bannò et al. proposed a self-referential approach comparing student writing to their own prior work rather than native-speaker norms. Feser & Tschisgale found AI scoring systematically underestimates linguistically weak students — a finding that connects to Assessment Validity and Bias Mitigation concerns. GenAI Linguistic Diversity Academic Writing explores how AI affects linguistic diversity in academic contexts.
Accessibility for language learners connects to Accessible Learning: DysLexLens analyzed how dyslexic learners use AI for literacy support, and AI Tools Arab English Classrooms explored AI tools in Arabic-English classroom contexts. These studies connect language learning to Equity and Special Education.