Human-Centred AI in Language Education in Higher Education: Pedagogical Design, Agency, Assessment, and Equity

Generative artificial intelligence (AI) is reshaping language education in higher education through conversational practice, personalized feedback, content creation, and assessment support. Yet much of the evidence concerns short-term interventions, individual tools, and users’ perceptions, leaving questions about language development, teacher agency, learner autonomy, and educational equity. In this Research Topic, a human-centred approach means designing and using AI in ways that preserve learners’ active participation and agency, teachers’ pedagogical judgment, meaningful human interaction, transparency about AI use, and human responsibility for learning and assessment decisions. This approach is especially relevant where inaccurate outputs, linguistic or cultural bias, privacy risks, unequal access, and overdependence may affect language learning. Research is needed to identify pedagogical and assessment practices that use AI responsibly while strengthening linguistic development and human participation.The central problem addressed by this Research Topic is that AI is being adopted in university language education faster than evidence-based guidance for its teaching and assessment uses can develop. Poorly designed use may encourage learner dependency, weaken teacher judgment, compromise authorship and assessment validity, or reinforce linguistic and cultural bias. This collection aims to identify how AI can improve language learning while preserving learners’ intellectual effort, meaningful interaction, and human responsibility for educational decisions. It invites empirical, theoretical, and practice-oriented research on human–AI collaboration, language development, teacher and learner agency, AI literacy, feedback, assessment, inclusion, and ethics. It also welcomes studies of institutional policies and governance models specifically for AI-supported language teaching, language assessment, academic writing, and multilingual education. Together, these contributions should offer practical, evidence-informed guidance for responsible AI use across diverse higher education settings.This Research Topic welcomes research on human-centred AI in language education across higher education settings. Every submission must have a direct connection to language education, such as language proficiency, communicative competence, vocabulary, grammar, language skills, translation, language assessment, language teacher practice, English for Academic or Specific Purposes, or multilingual learning. Themes include human–AI collaboration; teacher judgment and professional roles; learner autonomy and AI dependency; AI literacy; feedback and assessment; academic integrity and authorship; privacy, bias, inclusion, and human oversight. Studies of institutional policies and governance models should focus specifically on AI-supported language teaching, language assessment, academic writing, or multilingual education. We encourage work that examines observable language learning outcomes and meaningful human participation in diverse contexts. Suitable manuscript types include Original Research, Systematic Review, Review, Mini Review, Methods, Perspective, Policy and Practice Reviews, and Curriculum, Instruction, and Pedagogy articles. Topic editors: Amr Mohamed, Fawaz Al Mahmud, Francisco D Guillen Gamez, Dalal Alqiawi Source: https://www.frontiersin.org/research-topics/86462/human-centred-ai-in-language-education-in-higher-education-pedagogical-design-agency-assessment-and-equity