ChatGPT’s Capabilities in Spotting and Analyzing Writing Errors Experienced by EFL Learners

The recent Large Language Models (LLMs) use advanced algorithms to identify areas where sentence structure and word choice can be improved detect grammar, syntax, spelling mistakes in sentences. This study aimed investigate the effectiveness of Chat Generative Pre-trained Transformer (ChatGPT) detecting English as a foreign language (EFL) learners’ writing errors compared human instructors. examines ChatGPT LLM analyzing processing EFL issues. paper provides valuable insights into potential benefits challenges integrating Artificial Intelligence (AI) education. Our results revealed that successfully identified most surface-level but could not related deep pragmatics. Conversely, teachers spot these These findings suggest while tool identifying errors, it cannot replace instructors’ expertise nuanced understanding more complex aspects writing. error types (data) are statistically analyzed. descriptive analysis displays reliability data its implications, F-score, which measures statistical model accuracy, is found 1.5. In meantime, p-value score, shows probability obtaining extreme detected data, calculated 0.23. collected significant, further may yield insights.