This study examines the pedagogical effectiveness of a blended learning approach integrated with the BOPPPS (Bridge-in, Objective, Pre-assessment, Participatory Learning, Post-assessment, Summary) instructional model, situated within the context of advancing artificial intelligence and data science education. Using the course ‘big data statistical analysis’ as a case study, we compare traditional lecture-based instruction with the “BL+BOPPPS” framework to evaluate its impact on online and offline learning outcomes. Our implementation of the “BL+BOPPPS” model demonstrates its effectiveness in fostering student autonomy, enhancing critical thinking skills, and cultivating innovation capabilities. Furthermore, this study contributes to the theoretical foundation for teaching big data statistical analysis, offering evidence-based insights to optimize instructional effectiveness in this discipline.
Wu et al. (2025) studied this question.