The Question Development Model in Generative AI-Based Reading Education: From Imagination to Logic

This study proposes a reading instruction model utilizing generative AI, specifically ChatGPT, in university liberal arts classes to foster students’ autonomous questioning and expand literacy skills. ChatGPT, designed to provide rapid information and knowledge in response to user queries, can enhance reading class engagement and facilitate knowledge expansion by stimulating active questioning among students. Traditional reading classes have typically focused on post-reading activities, like debates or critical reviews, which often make students passive and less engaged. To address this, this model positions ChatGPT as a personalized learning tutor, guiding students through a structured process to formulate, extend, and refine questions. The model consists of four stages: reading the text, forming foundational questions, interacting with ChatGPT for expanded inquiry and critical thinking, and integrating information for meaningful writing. This approach allows students to start with basic or imaginative questions, gradually developing more structured and logical queries. Emphasizing the process over the final written output, the model prioritizes active engagement and the ability to discern relevant information through inquiry. The ChatGPT-based model also highlights the value of personalized learning in AI-assisted environments, potentially increasing motivation and cognitive engagement. Overall, this instructional approach aims to address the evolving literacy needs in an AI-driven era, promoting autonomous exploration and sustained learning interest.