Artificial Intelligence in Project-Based Learning: A Systematic Review of Its Role in English Language Acquisition and Pedagogical Innovation

Abstract

Background of Study: The integration of artificial intelligence (AI) into project-based learning (PBL) is increasingly explored as a means to enhance English language acquisition. Emerging AI technologies such as natural language processing, machine learning, and generative AI show potential to support language learning in dynamic, learner-centered environments.

Aims and Scope of Paper: This review investigates how AI has been applied in PBL contexts to support English language learning, highlighting both benefits and challenges.

Methods: Following the PRISMA framework, a systematic review was conducted of 12 studies published between 2020 and 2024 across six major databases.

Results: Seven key elements of AI-enhanced PBL were identified: (1) real-time feedback and automated assessment, (2) adaptive learning pathways, (3) contextualized language use, (4) continuous AI language support, (5) structured project guidance, (6) collaborative learning, and (7) intelligent content customization. These elements were found to improve learner motivation, engagement, and language proficiency while promoting transferable academic and professional skills. However, challenges include overdependence on AI, reduced teacher-student interaction, insufficient training in AI tools, and biases in AI-generated content. The review’s scope is limited by the small number of studies and methodological diversity.

Conclusion: AI-enhanced PBL offers promising opportunities for advancing English language education by fostering motivation, proficiency, and transferable skills. To ensure sustainable implementation, future efforts must address challenges related to pedagogy, teacher training, and ethical AI use. This review provides practical insights for educators and policymakers seeking to balance technological innovation with human-centered teaching.

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