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Journal of Tuberculosis and Lung Disease ›› 2024, Vol. 5 ›› Issue (2): 168-171.doi: 10.19983/j.issn.2096-8493.20230129

• Original Articles: Teaching • Previous Articles     Next Articles

Evaluation the application of information-based hybrid teaching model in thoracic imaging diagnosis education

Wu Ning1, Tang Ke2, Sun Weirong1()   

  1. 1Department of Radiology, the Eighth Medical Center of Chinese PLA General Hospital, Beijing 100091, China
    2Department of Neurosurgery, Chinese PLA General Hospital, Beijing 100091, China
  • Received:2023-12-08 Online:2024-04-20 Published:2024-04-11
  • Contact: Sun Weirong


Objective: To explore the teaching effect of clinical medical undergraduates in chest imaging diagnosis with the information-based mixed teaching mode. Methods: A total of 62 medical imaging undergraduates undergoing rotation training in the Department of Radiology of the Eighth Medical Center of PLA General Hospital from September 2018 to September 2022 were selected and divided into the Observation Group (with information-based mixed teaching model) and the control group (with traditional teaching model). The improvement of self-regulated learning ability of the two groups was evaluated by questionnaires, and the innovation ability was evaluated using scientific research design and simulated report, the problem-solving ability was assessed through film review and case analysis. A total of 62 questionnaires were distributed and 62 valid questionnaires were recovered. Results: The self-regulated learning ability scores of the two groups were (4.52±0.57) and (3.35±0.75), respectively, the difference was statistically significant (t=6.836, P<0.001); the scores of innovation ability were (3.94±0.73) and (2.84±1.01), respectively, with significant difference (t=4.928, P<0.001); and the scores of problem solving ability were (76.90±3.71) and (68.81±4.57), respectively, the difference was also statistically significant (t=7.651, P<0.001). Conclusion: The information-based hybrid teaching mode can improve the ability of self-directed learning, innovation, and problem-solving in the diagnosis of chest imaging for clinical medical undergraduate students.

Key words: Teaching, Lung, Radiographic image interpretation, computer-assisted

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