Reducing Affective Filters through AI-Supported English Learning for Korean Adult Learners

Korean adult learners often struggle with communicative English due to grammar-focused instruction, test-driven evaluation, and cultural anxiety around making mistakes. These factors raise the affective filter, limiting willingness to speak and reducing learner confidence. Although generative AI tools such as ChatGPT have rapidly expanded, little research has explored how they might lower affective barriers or support intercultural competence for Korean adult EFL learners. This field project examines how AI-supported instruction can create psychologically safe, culturally responsive, and meaningful English learning experiences for adults in Korea. Drawing on Krashen’s Affective Filter Hypothesis, Schumann’s Acculturation Model, and research on language anxiety, the study reviews emotional and cultural barriers in traditional Korean EFL contexts and synthesizes current findings on AI-assisted learning. Literature suggests that AI can reduce anxiety, offer personalized and non-judgmental practice, and increase opportunities for spontaneous communication. To address these needs, the project introduces Into the World: An AI-Supported, Culturally Responsive English Handbook for Korean Adult Learners, a four-unit curriculum incorporating QR-linked ChatGPT speaking tasks, pronunciation practice, and contextualized dialogues. Developed through fieldwork in community workplaces in Busan, the handbook provides low-pressure, authentic opportunities for adult learners to develop confidence and communicative ability. The project concludes with recommendations for educators and researchers seeking to integrate AI into adult EFL education.