Prediction of Learner Information-Seeking Behavior and Classroom Engagement in the Advent of ChatGPT

Information source accuracy and trustworthiness are vital in undergraduates’ education in terms of how they seek teacher feedback and educational content. Nowadays, the infusion of technologies into education has led to convenient and easy access to learning materials in electronic libraries and web-based platforms or search engines. Undergraduates are expected to make rapid use of ground-breaking technologies to sift for academic information over the internet. With the advent of ChatGPT, it is estimated that undergraduates might rely on it for academic information. The theoretical study gauges the potential impact of ChatGPT on the information-seeking behavior of undergraduates and what it means for classroom engagement. To do this, we utilized the inquiry-based learning theory which emphasizes the active participation of learners in discovering new information. The study is one of the first to contribute to the ongoing discussions on the impact of large language models (LLMs) such as ChatGPT on education.