Abstract:

Artificial intelligence (AI) is increasingly reshaping language education by introducing tools that personalize instruction, promote interaction, and deepen cognitive engagement. This paper introduces the use of vibe coding for language acquisition. Vibe coding is a programming approach where one prompts AI to generate, refine, and execute code. Therefore, students can use natural language to generate custom mini-games, simulations, and interactive tools through AI platforms. This approach reconceptualizes AI’s educational role from passive content provider to a co-creative agent that supports constructing personally meaningful language experiences.

This study draws on contemporary research in metacognitive strategy, intrinsic learner motivation, and self-efficacy in language acquisition to demonstrate how vibe coding facilitates self-regulated learning. Learners actively engage in goal setting, progress monitoring, adaptive decision-making, and reflective evaluation. Students first design AI-powered language activities using tools such as ChatGPT, Scratch-with-AI, and Google AI Studio, then engage in structured peer feedback and guided reflection, empowering learners to design and direct their own learning pathways. This framework offers practical insight for educators and curriculum designers seeking to integrate AI meaningfully into language instruction while advancing essential cognitive and reflective skills.

Keywords:

Vibe coding, AI-assisted learning, metacognitive strategies, second language acquisition, flipped classroom, learner autonomy.