AI-Driven Innovations in Adult EFL Learning: Exploring Potentials and Practicalities

Abstract

In a worldwide world, adults must master numerous languages, which is difficult. Recent brain research reveals that high proficiency can be attained with minimal practice, while artificial intelligence (AI) advances offer targeted and efficient language education. This study analyzes how AI techniques such as active learning, intelligent tutoring, and natural language processing can improve adult EFL acquisition. AI can improve learning, feedback, engagement, motivation, and outcomes compared to traditional techniques. However, interpersonal communication is crucial. The study uses instructor-learner questionnaires to emphasize the cautious acceptance of AI technologies and the need for ethical frameworks and balanced integration with human educators. This study evaluates and compares attitudes, defines the best balance between human-human and human-AI, identifies best practices for ethical risk, age matters, and adult self-determination, and guides AI integration and framework development. Adapting these technologies to decrease risk and maximize autonomy is crucial. For the following few steps, stakeholders and joint research to develop credible AI guidelines for adult EFL teaching are essential. This study examines the views of 30 EFL teachers and 35 adult learners regarding using AI to teach English. The goals are to assess expected benefits, compare attitudes, and define ethical difficulties. Questionnaires examined AI impacts such as technology use, evaluation, and instigating variables. 100% of teachers expected engagement improvements. Student attitudes toward such assessment adoption were neutral, with 57% neutral on its validity. Statistical analysis using analysis of variance (ANOVA) revealed significant differences in attitudes regarding independence restriction and constraint (p < 0.05). AI augments instruction, not replaces it. Including adult learners in AI development, merging AI with traditional approaches, and using AI-augmented pedagogy to promote linguistic competency while addressing contextual and social restrictions are key recommendations.