Research on quality evaluation index system of traditional Chinese medicine classic courses

doi:10.3760/cma.j.cn115259-20230324-00307

Abstract

Abstract: Objective To construct a quality evaluation index system of traditional Chinese medicine classic courses from the perspective of student evaluation so as to provide tool support for related course quality evaluation. Methods Based on the context-input-process-product (CIPP) evaluation model, using literature research, text analysis, semi-structured interviews, and Delphi method,the evaluation index system was constructed. The analytic hierarchy process was then used to calculate the weights of the indicators. Furthermore, Cronbach′s alpha coefficient and Kaiser-Meyer-Olkin (KMO) value were calculated to examine the reliability and validity of the index system. Results A total of 15 experts from the teaching and research group of traditional Chinese medicine classics and higher education in traditional Chinese medicine at Beijing University of Chinese Medicine were selected to be consulted. The authority coefficients of the two rounds of consultation were 0.957 and 0.955, respectively. Finally, index system including 4 primary indicators, 11 secondary indicators, and 32 tertiary indicators, with specific content and indicator weights were constructed. The Cronbach′s alpha was 0.966, and the KMO value for structural validity was 0.942. Conclusions The quality evaluation index system of traditional Chinese medicine classic courses based on the CIPP evaluation model was scientific and authoritative, with good reliability and validity. It can serve as an evaluation tool for the quality of traditional Chinese medicine classic courses.

Key words: Curriculum, Chinese medicine classic courses, Course quality, Index system, Context-input-process-product evaluation model, Delphi method

CLC Number:

Wu Yue, Zhai Shuangqing, Jiao Nan, Yuan Na. Research on quality evaluation index system of traditional Chinese medicine classic courses[J]. Chinese Journal of Medical Education, 2023, 43(12): 956-960.

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