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This is a Quantitative Study study.

September 12, 2025

Study on the Effectiveness of Blended Learning in a Big Data Statistical Analysis Course based on the BOPPPS Teaching Model

Key Points

The implementation of the BL+BOPPPS model enhances student autonomy and critical thinking skills, fostering innovation.
Results indicate improved learning outcomes in online and offline settings, compared to traditional instruction methods.
Analyses showed significant pedagogical effectiveness, suggesting the BOPPPS model optimizes instructional strategies in data science education.
This approach contributes to the theoretical framework necessary for effective teaching practices in big data statistical analysis.

Abstract

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.

Study on the Effectiveness of Blended Learning in a Big Data Statistical Analysis Course based on the BOPPPS Teaching Model

Key Points

Abstract

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