AI-Generated versus Human-Developed Assessment Tasks in EFL Context: Insights from TPCK Model

This study aimed to compare the pedagogical and content quality of AI-generated assessment tasks with those developed by humans in English language teaching, using a sequential-explanatory mixed-methods design. To accomplish this, 6 human-developed lesson plans from American English File 3 and 6 equivalent AI-generated lesson plans were analyzed. Twenty experienced EFL teachers were invited to evaluate and rate 52 assessment tasks from these lesson plans based on a TPCK-aligned rubric. Follow-up interviews were conducted to better understand the teachers’ ratings. Quantitative results showed no statistically significant differences between AI- and human-developed tasks across eight quality criteria. More specifically, teachers preferred AI-generated grammar and vocabulary tasks, while favoring human-developed reading, listening, writing, and speaking tasks. Moreover, qualitative analysis highlighted AI’s strengths in generating tasks quickly, providing a diverse range, and managing rule-based content. The study also emphasized the importance of teacher mediation to ensure personalization and contextual relevance. Overall, the findings emphasize the need for human-AI collaboration in EFL assessment design. In other words, AI tools are useful as initial resources rather than complete replacements for human-created assessments.