Competition between human learners and ChatGPT: enhancing university EFL students’ reading comprehension and critical thinking through competitive questioning
Junjie Shang, Yuhan Huang, Meixia Xu, Yi Huang, Xuantong Shen, Guoxiu Wang, Yuetian Wang, Lu Zhang · Computer Assisted Language Learning · 2025
Despite the potential of using ChatGPT to augment language learning, its impact on enhancing English as a Foreign Language (EFL) learners’ reading comprehension and critical thinking is under-researched. This quasi-experimental study aimed to explore the effectiveness of integrating ChatGPT into EFL reading activities through a competitive questioning approach. In the five-week experiment, 87 Chinese university freshmen were divided into experimental and control groups to participate in weekly learning sessions in which they conducted reading exercises and question-posing activities. During the sessions, the experimental and control groups were respectively engaged in pursuing ChatGPT-supported competitive questioning and traditional text-based questioning. With the use of machine learning techniques, all questions posed by the participants were analyzed with a six-dimension framework of critical thinking, adapted from Facione’s critical thinking framework and Day and Park’s reading comprehension taxonomy, encompassing simple and compound interpretation, simple and complex analysis, synthesis, and inference. Results showed that the experimental group achieved significant gains in reading comprehension from pre-test to post-test, outperforming the control group, whose performance declined over the same period. Regarding critical thinking, the experimental group’s posed questions were progressively more advanced in the course of the experiment. The present work underscores the potential of utilizing ChatGPT as a supportive competitor for EFL learners to improve reading comprehension and foster critical thinking.