Coffi Martinien ZOUNHIN TOBOULA, University of Abomey Calavi (UAC), Benin

The COVID-19 pandemic has disrupted traditional language learning, leading to a shift towards online teaching and requiring new approaches to language education. This study examines the effectiveness of AI-powered collaborative and interactive Natural Language Processing (NLP) applications on English as a Foreign Language (EFL) instruction in a post-COVID-19 online education environment. The study used a mixed-methods approach, incorporating statistical and in-depth qualitative data gathering and processing strategies. EFL teachers and students from the University of Abomey-Calavi (UAC) in Benin were surveyed, interviewed, and observed during online language learning sessions. The data were analysed using both descriptive and inferential statistics. The study employed questionnaire surveys to analyse quantitative data and used the thematic (content) analysis method to isolate the most important trends and themes hidden within the qualitative data collected through semi-structured interviews and online class observations. Results showed the challenges and opportunities of using AI-powered collaborative and interactive language learning in EFL teaching, the learning methodologies and assessment approaches used in AI-enabled collaborative e-learning, the role of technology in supporting pervasive learning, and the impact of professional development for teachers in ICT on integrating AI-assisted collaborative e-learning in EFL instruction. The findings offer new perspectives on the effects of AI-supported collaborative and interactive language learning on EFL teaching and its implications for EFL teachers and students in the post-pandemic era.

AI-powered, Collaborative and Interactive Language Learning, NLP Apps, Post-COVID-19, Online EFL Teaching