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Difference analysis and thinking of online teaching for medical statistics of graduates of different cultivation types
Chen Hui, Wu Wenfang, Zhou Zhen, Zou Tong
2022, 42 (1):
70-74.
DOI: 10.3760/cma.j.cn115259-20210422-00532
Objective To investigate the situation of online teaching for medical statistics of graduates of different cultivation types. Methods A total of 240 graduate students who took part in the medical statistics courses in Capital Medical University were investigated with self-made questionnaire on the teaching effect, teaching methods, and teaching content. Results of single choice questions were analyzed by ordinal logistic regression. For multiple choice questions, results of the whole question were analyzed by generalized estimation equation with logit linkage function, while results of each option was analyzed by binary logistic regression. Results A total of 240 valid questionnaires were collected. In terms of learning status, compared with the regularly enrolled students, in-service students had more difficulty to attend classes on time (OR=2.931, 95%CI: 1.435~5.986), and spent more time on after-class review (OR=2.077, 95%CI: 1.249~3.454). From the perspective of learning process, doctoral students had higher overall requirements for homework than Master degree candidates (OR=1.792, 95%CI: 1.345~2.388), and in-service students hoped to have more teaching links than regularly enrolled students (OR=1.501, 95%CI: 1.126~2.001). From the perspective of learning gains, doctoral students gained more in all aspects (OR=3.936, 95%CI: 2.150~7.205). For the proportion of online teaching, in-service students tended to have a larger proportion (OR=2.994, 95%CI: 1.727~5.021). The above differences were statistically significant (all P<0.05). Conclusions The graduate students of different cultivation types have differences in learning time allocation, requirements for after-school homework, expected proportion of online and offline teaching, and learning gains. Online or online-offline hybrid teaching of medical statistics for graduates should be designed to meet the needs of students with different characteristics and different cultivation types.
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