Supporting data for “Facilitating inquiry-based learning in the science classroom: A shift from structured tools to AI-driven support”

Inquiry-based learning (IBL) is recognized as a pivotal pedagogical strategy for fostering scientific literacy, theoretically enabling students to engage in iterative cycles of hypothesis generation, investigations, and evidence-based argumentation. However, translating this ideal into practice is hindered by dual challenges: the high cognitive complexity of inquiry for students and the logistical burden of orchestrating complex interactions for teachers. While digital tools have effectively provided structural support for process-oriented activities, a critical gap remains on how to facilitate deep cognitive engagement without overloading teachers’ capacity to monitor and scaffold real-time dynamics. Addressing this gap, the present study investigates the design, implementation, and efficacy of a technology-enhanced inquiry system (WeInquiry), tracing its evolution from static, structured tools to dynamic, AI-driven support.