Analysis for the influencing factors of item difficult in China's National Medical Licensing Examination

doi:10.3760/cma.j.issn.1673-677X.2017.02.034

Abstract

Abstract: In this paper, an analysis was presented based on ordinal logistic regression that illustrates what is the relationship between “expert judges”(or student) and influencing factors of item difficulty. The results of the study show that test purpose and cognitive skills primarily influence “expert judges”. However, the patterns shown by the student data are effectiveness of the incorrect alternative responses, connective between current practice and test content, negative questions mostly influence students. Although work from this study is limited, it suggests that the prediction item difficulty will fare well when relevant studies are conducted.

Key words: National medical licensing examination, Item difficulty, Influencing factors, Analysis

Yang Fangli, He Jia. Analysis for the influencing factors of item difficult in China's National Medical Licensing Examination[J]. Chinese Journal of Medical Education, 2017, 37(2): 312-316, DOI: 10.3760/cma.j.issn.1673-677X.2017.02.034.

References

[1] 何惧,何佳,张赛一,等.医师资格考试内容效度的质量控制措施[J].高校医学教学研究(电子版),2015,5(1):54-57.
He J, He J, Zhang SY, et al. Introduction of quality control measures to improve the content validity of National Medical Licensing Examination[J].Medical Teaching in University (Electronic Edition),2015,5(1):54-57.
[2] 董圣鸿,漆书青,戴海崎,等.题目难度、区分度参数人工赋值方法的研究[J].考试研究, 2005(1):25-32,24.
[3] 柳博.预估难度一种自学考试的试题难度确定方法[J].中国考试(研究版),2007(7): 29-34.
[4] 杨涛,辛涛,杨婷婷.试题难度的主观预估方法[J].中国考试,2014(2):3-9.
Yang T, Xin T, Yang TT. Subjective prediction methods of item difficulty estimation[J].China Examinations,2014(2):3-9.
[5] 毛竞飞.高考命题中试题难度预测方法探索[J].教育科学,2008,24(6):22-26.
Mao JF. Research on predictive methods of item difficulty in the college entrance of examination[J]. Education Science,2008,24(6):22-26.
[6] Kleinbaum DG, Klein M.Logistic regression: a self-learning text[M].3rd ed.New York:Springer Publishers,2010:168-193.
[7] 田霖,王桥影.自学考试的试题难度赋值方法述评[J].中国考试,2010(4):24-30.
Tian L, Wang QY. Item difficulty evaluation's advances in self-taught examination[J].China Examinations,2010(4):24-30.
[8] 王晓华.论高等教育自学考试试题难度的控制[J].中国考试(研究版),2008(1):48-54.
Wang XH. The discussion on the item difficulty control of the higher education self-taught examination[J].China Examination,2008(1):48-54.
[9] Lorge I, Kruglov L. A suggested technique for the improvement of difficulty prediction of test items[J].Educational and Psychological Measurement,1952, 12(4):554-561.
[10] Bejar II, Embretson S, Mayer RE. Cognitive psychology and the SAT:a review of some implications[R/OL].[2017-01-10].http://www.ets.org/research/policy_research_reports/publications/report/1987/hwpo.
[11] Quereshi MY, Fisher TL. Logical versus empirical estimates of item difficulty[J].Educational and Psychological Measurement,1977,37(1):91-100.

[1]	Zhang Xiaonan, Chen Keyong, He Xia, Zang Xiaoying. Research on preference characteristics and factors influencing medical students' willingness to participate in intergenerational programs [J]. Chinese Journal of Medical Education, 2026, 46(6): 407-412.
[2]	Wang Dongyi, Wang Ning, Cui Dongtao, Ma Yongchao, Wang Jianguo. Comparative study on the talent training scheme of clinical medicine programs in vocational colleges in China [J]. Chinese Journal of Medical Education, 2026, 46(6): 413-418.
[3]	Li Xiang, Feng Min, Li Xiaoyu, Zeng Jiwen, Shu Qi, Zhang Yan, Jiang Xuan, Hu Jing. Current status of medical students′ participation in the innovation and entrepreneurship training program [J]. Chinese Journal of Medical Education, 2026, 46(5): 326-330.
[4]	Chen Lihua, Liu Shuo, Xin Siyan, Wang Yu, Wu Hongbin. A study on the influencing factors of the use of generative artificial intelligence by clinical medicine students [J]. Chinese Journal of Medical Education, 2026, 46(3): 199-205.
[5]	Yan Kemin, Li Chen, Gong Yingying, He Wen, Yang Daya, Zhang Kunsong, Feng Shaoting, Yuan Gang. Visual analysis of the current situation of interprofessional education in medicine based on Bibliometrix [J]. Chinese Journal of Medical Education, 2026, 46(2): 81-85.
[6]	Du Wenjing, Guo Lei, Zhang Qin. Application and effectiveness analysis of the tutorial system combined with peer teaching in medical functional experiment courses [J]. Chinese Journal of Medical Education, 2026, 46(2): 101-106.
[7]	Guo Huan, Zhao Yuhan, Chen Yanglin. Current status and needs assessment of continuing medical education in a specialized cancer hospital [J]. Chinese Journal of Medical Education, 2026, 46(2): 124-129.
[8]	He Zitang, Hu Xiaoyun, Shi Di, Xia Peng, Guo Chao, Jiang Wei, Wang Lin, Li Xiaoyan, Liu Jihai, Li Yue. Design and implementation of instructor training course in medical simulation teaching [J]. Chinese Journal of Medical Education, 2025, 45(8): 596-601.
[9]	Gan Yutian, Yang Xiaojing, Tian Yinan, Qin Xiaxia, Zhang Yilin, Zhang Shue, Cao Depin, Yang Libin. Research on influencing factors of medical students′ digital resilience based on qualitative analysis [J]. Chinese Journal of Medical Education, 2025, 45(6): 419-422.
[10]	Yang Junli, Chang Yue, Wang Wenju, Liao Xingjiang, Zhou Hanni, Wang Hongmei, Zhang Keren, Luo Xiaobo. A research on the satisfaction of students with the simulation pharmacy practical training and environment in relevant colleges and universities in Guizhou Province [J]. Chinese Journal of Medical Education, 2025, 45(6): 428-432.
[11]	Sun Jingwen, Liu Jing, Li Li, Wang Ying, Fang Caimei, Wu Zhenlong, Wang Jianliu. Optimization study of the residency training program specialty directory based on comparative analysis [J]. Chinese Journal of Medical Education, 2025, 45(6): 438-443.
[12]	Wu Danni, Xia Zhouyan, Zhu Binhai. Quantitative evaluation of standardized residency training policy based on the PMC index model [J]. Chinese Journal of Medical Education, 2025, 45(6): 444-449.
[13]	Chen Haoyang, Liu Jianan, Duan Yanhan, Wang Sifan, Wu Haijiang, Zhang Xinping. Analysis of policy topics and their evolution in China′s higher medical education [J]. Chinese Journal of Medical Education, 2025, 45(5): 344-349.
[14]	Yang Xiaojing, Gan Yutian, Duan Xinyu, Lu Feng, Wang Jianye, Zhao Lijie, Zhang Shue, Cao Depin. Research on influencing factors of medical students′ death attitudes [J]. Chinese Journal of Medical Education, 2025, 45(5): 370-374.
[15]	Li Wen, Han Wei, Yang Jianjun. A study on the network relationship between educational environment perception, academic self efficacy, and learning engagementin the school of public health [J]. Chinese Journal of Medical Education, 2025, 45(2): 110-115.