Opportunities and Challenges of Using Artificial Intelligence for Grammar Assessment: A Case Study on the Perspectives of English Language Teachers in Ilam City

Abstract

The present study aimed to investigate the opportunities and challenges associated with the use of artificial intelligence-based grammar assessment tools, such as ChatGPT and Grammarly, from the perspectives of English language teachers in Ilam city, with particular emphasis on pedagogical, infrastructural, ethical, and technological dimensions. This study employed a sequential explanatory mixed-methods design combining quantitative and qualitative approaches. The statistical population consisted of 41 English language teachers working in schools and language institutes in Ilam city. In the quantitative phase, data were collected using a standard and researcher-made questionnaire designed based on the Technology Acceptance Model (TAM). The questionnaire assessed perceived usefulness, perceived ease of use, and perceived barriers associated with AI-driven grammar assessment systems. The reliability of the instrument was confirmed through Cronbach’s alpha coefficient of 0.83. In the qualitative phase, semi-structured interviews were conducted with a purposively selected subgroup of teachers representing different levels of teaching experience and educational settings. Quantitative data were analyzed using descriptive and inferential statistics in SPSS, while qualitative interview data were coded and analyzed through thematic analysis following Braun and Clarke’s six-step procedure. The findings demonstrated that teachers had highly positive attitudes toward the practical benefits of AI-based grammar assessment systems, particularly regarding accelerating the correction process (M=4.5), providing immediate corrective feedback (M=4.3), and reducing occupational workload and burnout. Inferential analysis further showed that younger teachers and those with lower teaching experience expressed greater technological acceptance and stronger perceived usefulness compared to more experienced teachers. Qualitative thematic analysis identified four major categories of challenges, including infrastructural instability and internet filtering (88%), concerns regarding reduced critical thinking and learner dependency (75%), digital inequality and limited student access to technological devices (62%), and the inability of AI systems to fully understand cultural and semantic nuances in Iranian EFL contexts (45%). The integration of quantitative and qualitative findings indicated that while teachers acknowledged the pedagogical value of AI, structural and contextual barriers significantly restricted sustainable implementation in Ilam’s educational environment.