Khung lí thuyết tích hợp trí tuệ nhân tạo tạo sinh trong dạy học khám phá chủ đề xác suất ở trung học cơ sở

Tóm tắt

In the context of educational digital transformation, mathematics teaching is increasingly expected to foster students’ inquiry, experiential learning, and thinking development. This paper develops a theoretical framework for integrating Generative Artificial Intelligence into discovery learning for teaching probability topics at the lower secondary level. Using a theoretical modeling approach, the study systematizes key perspectives on discovery learning, probabilistic thinking, dynamic models, and the pedagogical role of Generative Artificial Intelligence. The proposed framework comprises three components: objectives for developing students’ inquiry competence and probabilistic thinking; a discovery learning process supported by dynamic models; and a Generative Artificial Intelligence infrastructure that assists teachers in designing simulations, virtual experiments, and interactive learning materials. Theoretical analysis suggests that Generative Artificial Intelligence may help reduce technical demandsin the development of digital learning resources, support teachers in expanding instructional design ideas, and create more opportunities for students to engage in probability inquiry tasks. The paper contributes a theoretical approach to integrating emerging technologies into mathematics education and provides a basis for future empirical studies to examine the feasibility and effectiveness of the proposed framework.