AI tools in teaching: EFL teachers’ perceptions of usefulness, challenges, and the role of designation and AI-training - Md. Mahadhi Hasan; Kaniz Fatema; Rashed Mahmud (Institute of Advanced Engineering and Science, 2026)
This study aims to investigate the integration of artificial intelligence (AI) into the teaching of English as a foreign language (EFL) at Bangladeshi Universities, focusing on teachers' perceptions of its benefits and challenges. A mixed-methods research design was employed, with a 19-item survey administered to 123 EFL teachers across 20 universities. Qualitative data were collected through semi-structured interviews with 5 teachers. Reliability and validity were assessed through pre-testing and Cronbach's alpha for internal consistency. Member checking and triangulation also contributed to the trustworthiness of qualitative data collected. Quantitative analysis used mean, standard deviation (SD), factor analysis, and chi-square tests, complemented by qualitative thematic analysis. Chi-square test results indicate no significant difference in teachers' designations regarding challenges (p >0.05). However, teachers with AI training do significantly better than those without in recognizing AI-generated EFL content (p =0.03). The qualitative findings show that teachers perceive AI as a tool that enhances teaching strategies, offers better time management, and facilitates innovative instructional practices. However, concerns about maintaining academic integrity prevail. Despite these challenges, the study emphasizes an optimistic outlook towards the role of AI in teaching English. It suggests integrating AI tools into EFL classrooms and proposes structured training programs to fully leverage their potential to enhance teaching effectiveness and improve learning outcomes.