A Blended Teaching Practice to Promote Students’ Deep Learning: A Case Study in Pharmacology of Traditional Chinese Medicine

DOI: https://doi.org/10.62517/jnse.202517410

Author(s)

Lin Li1, Linqing Wang1, Chenying Wang1, Dan Qiao1, Yuan He2, Guoxia Wang1,*

Affiliation(s)

1College of Life Sciences, Zhengzhou Normal University, Zhengzhou, Henan, China 2College of Tobacco Science and Engineering, Zhengzhou University of Light Industry, Zhengzhou, Henan, China *Corresponding Author

Abstract

Deep learning represents an important pathway to fostering human development. China Education Modernization 2035 explicitly emphasizes the integration of intelligent technologies into all aspects of teaching and learning. In the era of Education Informatization 2.0, how to effectively achieve deep learning, particularly within technology-supported environments, has become a key issue in educational development. As a significant reform strategy in higher education, blended teaching provides broad opportunities for facilitating students’ deep learning. To this end, this study takes the Pharmacology of Traditional Chinese Medicine (TCM) course as an example and employs Rain Classroom to implement blended teaching practices. Through classroom observation, questionnaires, and interviews with both teachers and students, we comparatively analyze the changes in students’ deep learning abilities before and after the course, aiming to identify effective approaches for promoting deep learning. The results indicate that this teaching model significantly enhances higher-order thinking skills and affective learning experiences, while suggesting that assessment mechanisms and resource quality still require optimization. These findings provide useful implications for improving the teaching quality of TCM pharmacology and for cultivating innovative talents in the field of traditional Chinese medicine.

Keywords

Pharmacology of Traditional Chinese Medicine; Blended Teaching Model; Deep Learning; Outcome-Based Education; Rain Classroom

References

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