Bridging the Gap: Exploring the Revolutionary Application of GenAI in Language Teaching and Learning

Abstract

Objective: The objective of this research is to investigate the possibilities of Generative AI (GenAI) in language education, to suggest the ways of overcoming limitations, restructuring teaching methods, and improving language assessments. It seeks to study the influence of GenAI on the learning outcomes of language and student satisfaction and address ethical aspects. Methodology: A multi-methods approach was utilized in which demographic analysis, pre-test and post-test assessments, GenAI usage analytics, course evaluation surveys, and focus groups were conducted. Participants were divided into control and experimental groups, with the experimental group being engaged in GenAI-assisted language learning activities. Statistical analysis was carried out to compare pretest and post-test scores, to evaluate GenAI usage patterns and to analyze the survey responses. Findings: The demographic analysis indicated equally distributed across gender and age brackets with differences in technology expertise and AI exposure. Pre-test and post-test scores comparison demonstrated significant improvement in both groups but the experimental group showed significant more gains, showing GenAI- assisted learning to be very effective. GenAI utilization analytics showed significant use of GenAI by the experimental group participants. Ratings from a course evaluation survey showed a higher level of overall satisfaction and positive perception of GenAI. The study demonstrates the transformatory role of GenAI for language teaching, implying teaching techniques and student participation. Novelty: This study adds to the developing area of AI-augmented language education, as it offers empirical proof of the benefits of GenaAI in improving language learning results and increasing student satisfaction. It fills the gap in literature by investigating the effect of GenAI on various facets of language education, including teaching approaches, assessments, and student interaction. The results are a reminder of the key role of ethical issues in the application of AI technologies in education and give a direction for further research and practice.