Identifying factors in AI Chatbot Adoption Among EFL Teachers in Tehran: A Binary Logit Modeling Approach

The rapid development of artificial intelligence (AI) has created new opportunities for improving language education through AI-based tools, particularly chatbots. However, the successful integration of these technologies depends largely on teachers’ willingness to adopt and use them in educational practices. This study aims to identify the factors influencing English language teachers’ adoption of AI chatbots and quantify their effects using a binary logit regression model. A questionnaire-based survey was conducted among ۳۲۰ English language teachers in Tehran to examine the role of demographic characteristics, perceived benefits, and technology-related concerns in AI adoption decisions. The results indicate that age, perceived cost reduction, time-saving benefits, academic background, fear of cheating, and trust in AI significantly influence teachers’ adoption behavior. The findings show that increasing age reduces the probability of AI acceptance, while higher trust in AI and perceived efficiency improvements encourage greater adoption. Sensitivity analysis demonstrates that the probability of AI adoption decreases substantially with age, reaching approximately ۲۰% among older teachers compared with nearly ۸۰% among younger teachers. Furthermore, the analysis of time-saving benefits shows that when AI tools save approximately one hour per week, the probability of adoption is around ۵۱%, increasing to nearly ۶۷% when weekly time savings reach seven hours. The findings highlight that trust-building, professional training, and addressing concerns related to academic integrity are essential for promoting responsible AI adoption in language education. The study provides empirical evidence for educational institutions and policymakers seeking to develop effective strategies for integrating AI chatbots into teaching practices.

کلیدواژه ها:

Artificial Intelligence ، AI Chatbots ، English Language Teaching ، Technology Adoption ، Binary Logit Modeling ، Teacher Acceptance