Teaching Practice Evaluation of Medical Mathematical Statistics Based on Knowledge Graph

Medical mathematical statistics is a core course in the field of medicine and pharmacy, playing a crucial role in cultivating students' professional literacy. Traditional teaching methods face challenges due to the abstract nature of the theory, insufficient student interest, and difficulties in improving teaching effectiveness. To address these issues, this paper proposes an innovative approach that teaching practice evaluation of medical mathematical statistics based on knowledge graph. Firstly, knowledge graph technology is employed to visualize the course knowledge system, clearly presenting the associations and hierarchical structure of knowledge points. This provides students with an intuitive and systematic learning framework, helping them quickly build a knowledge system and deepen their understanding of complex concepts. Secondly, targeted teaching strategies are designed in conjunction with the six stages of the BOPPPS teaching model (Bridge-in, Objectives, Pre-assessment, Participatory Learning, Post-assessment, and Summary). The visualization of knowledge graphs enhances interactivity and relevance in each stage, stimulating students' enthusiasm for learning. Specifically, the Bridge-in stage clarifies learning objectives; the Participatory Learning stage uses knowledge graphs to guide group discussions and case analyses, fostering critical thinking and problem-solving skills; and the Postassessment stage reviews and consolidates knowledge through knowledge graphs to reinforce learning outcomes. Finally, this study was implemented in the medical and pharmaceutical statistics course for undergraduate students at Shaanxi University of Chinese Medicine. A comprehensive evaluation of students' academic performance, classroom participation, and learning satisfaction indicated that the innovative teaching model significantly increased students' interest and course grades, enhanced their ability to apply knowledge and innovate, and provided a new approach for course teaching reform. It also offers valuable references for teaching improvements in other professional courses.

Authors

Institutions

Publication Details

Published
2025-05-14
DOI
https://doi.org/10.1109/icaie64856.2025.11158577
Citations
1
Primary Topic
Medical Research and Treatments
Type
article
Field-Weighted Citation Impact
2.38
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Teaching Practice Evaluation of Medical Mathematical Statistics Based on Knowledge Graph

Hui Zhi, Sheng Hu, Xuan Yang, Junhua Hu et al.
1 citations
Medical Research and Treatments
2.38
article

Teaching Practice Evaluation of Medical Mathematical Statistics Based on Knowledge Graph

Hui Zhi, Sheng Hu, Xuan Yang, Junhua Hu, Xiangwen Li, Di Wu, Lingzhi Hu
article en
1 citations

Abstract

Medical mathematical statistics is a core course in the field of medicine and pharmacy, playing a crucial role in cultivating students' professional literacy. Traditional teaching methods face challenges due to the abstract nature of the theory, insufficient student interest, and difficulties in improving teaching effectiveness. To address these issues, this paper proposes an innovative approach that teaching practice evaluation of medical mathematical statistics based on knowledge graph. Firstly, knowledge graph technology is employed to visualize the course knowledge system, clearly presenting the associations and hierarchical structure of knowledge points. This provides students with an intuitive and systematic learning framework, helping them quickly build a knowledge system and deepen their understanding of complex concepts. Secondly, targeted teaching strategies are designed in conjunction with the six stages of the BOPPPS teaching model (Bridge-in, Objectives, Pre-assessment, Participatory Learning, Post-assessment, and Summary). The visualization of knowledge graphs enhances interactivity and relevance in each stage, stimulating students' enthusiasm for learning. Specifically, the Bridge-in stage clarifies learning objectives; the Participatory Learning stage uses knowledge graphs to guide group discussions and case analyses, fostering critical thinking and problem-solving skills; and the Postassessment stage reviews and consolidates knowledge through knowledge graphs to reinforce learning outcomes. Finally, this study was implemented in the medical and pharmaceutical statistics course for undergraduate students at Shaanxi University of Chinese Medicine. A comprehensive evaluation of students' academic performance, classroom participation, and learning satisfaction indicated that the innovative teaching model significantly increased students' interest and course grades, enhanced their ability to apply knowledge and innovate, and provided a new approach for course teaching reform. It also offers valuable references for teaching improvements in other professional courses.

Xi'an Polytechnic University (CN), Shaanxi University of Chinese Medicine (CN)
Openalex Percentile: Top 10%
Medical Research and Treatments
2.38
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.