Artificial intelligence in language teaching and assessment: A systematic review of research (2020-2024)

<p dir="ltr">Artificial intelligence (AI) technologies, such as big data analysis, machine learning, and natural language processing, have the potential to make language education more accessible, personalized, and efficient. This study analyzed applications of AI in language teaching and assessment by reviewing 59 articles. The scope included exploring emerging ethical, pedagogical, and technological considerations related to AI-driven tools used for language teaching, assessment, and learner support. The review focused on English language contexts, particularly studies involving AI-powered tools in EEL/ESL settings, such as natural language processing systems, automated assessment, machine learning analytics, and intelligent tutoring systems. Literature searches were conducted across major databases, including Scopus, Web of Science, ERIC, ScienceDirect, SpringerLink, and Google Scholar. The collected data were analyzed following PRISMA guidelines and with the support of MAXQDA software. The findings indicate that AI-driven language tutoring systems can provide targeted interventions, facilitate interactive learning activities, and assess learners' learning styles and proficiency levels. However, challenges include potential biases, inequitable learning environments, and unequal access to technology. Ethical concerns involve data privacy, discrimination, algorithm transparency, and accountability in AI-based tools. To ensure effective integration, pedagogical strategies should balance automated evaluation with real-world discussions and interactions to promote comprehensive language development.</p>