AI-assisted language learning for preschoolers: Krashen’s second language acquisition theory

Abstract

The integration of technology in early education presents new opportunities for second language (L2) acquisition. Grounded in Stephen Krashen’s influential theory, this study investigates the potential of Artificial Intelligence (AI) based on Krashen’s language acquisition theory to create an optimal learning environment for young children. The primary purpose was to determine the effectiveness of an AI-assisted learning system on the linguistic skills and affective development of preschool-aged L2 learners. This study employed a 24-week, quasi-experimental, mixed-methods design. Sixty children aged 3–6 were assigned to either an experimental group using the AI system or a control group receiving conventional instruction. The AI platform was engineered to provide comprehensible input and real-time feedback within a gamified, low-anxiety setting. Quantitative data were sourced from pre- and post-tests measuring receptive skills, productive skills, and speaking fluency. Qualitative data were gathered through classroom observations, interviews with stakeholders, and teacher focus groups. The results indicate that the experimental group achieved significantly higher gains across all tested language domains compared to the control group. Furthermore, learners using the AI system demonstrated notable improvements in affective factors, reporting higher motivation and engagement alongside lower language anxiety. Qualitative analysis corroborated these findings, revealing increased confidence, enjoyment, and spontaneous language use among children in the experimental group. This study provides strong evidence that a theoretically-grounded AI system can effectively facilitate L2 acquisition in early childhood. By fostering a rich, interactive, and emotionally supportive environment, such technology offers significant implications for designing and implementing advanced language curricula for young learners.