Digital Empowerment in the Blended Teaching Design and Practice of Statistics: A Case Study on Simple Linear Regression

Under the rapid development of artificial intelligence and big data technologies, statistical education is undergoing profound paradigm transformation. This paper innovatively constructs a “four-stage, three-integration” pedagogical system from the new perspective of digital-intelligent technologies empowering education. Through organic integration of ideological-political elements, disciplinary frontiers, and STEM education, it forms an progressive cultivation path encompassing “pre-class intelligent guidance - in-class precision teaching - post-class consolidation - extracurricular capability enhancement”. Taking the classical statistical method “simple linear regression” as a teaching case and based on the BOPPPS (Bridge-in, Objective, Pre-assessment, Participatory Learning, Post-assessment, Summary) model, this study systematically elaborates the construction approach of digital-intelligence empowered hybrid teaching mode for statistics courses. Practice has demonstrated that this model, leveraging the data collection and analysis capabilities of intelligent teaching platforms, realizes a new teaching paradigm of collaborative symbiosis between teachers, students, and artificial intelligence. It effectively enhances students' statistical modeling capabilities and innovative thinking, providing a replicable paradigm for intelligent teaching reform in statistical discipline courses.