Online assessment in two consequent semesters during COVID‑19 pandemic: K‑means clustering using data mining approach
نویسندگان
1 Department of Community Medicine, School of Medicine, Birjand University of Medical Sciences, Birjand, Iran
2 Department of Oral and Maxillofacial Medicine, School of Dentistry, Infectious Diseases Research Center, Birjand University of Medical Sciences, Birjand, Iran
3 e‑Learning Center, Birjand University of Medical Science, Birjand, Iran
4 Department of Epidemiology and Biostatistics, School of Health, Social Determinants of Health Research Center, Birjand University of Medical Sciences, Birjand, Iran
5 Department of Infectious Diseases, School of Medicine, Infectious Diseases Research Center, Birjand University of Medical Sciences, Birjand, Iran
doi
چکیده
BACKGROUND: Education and assessment have changed during the COVID‑19 pandemic so thatonline courses replaced face‑to‑face classes to observe the social distance. The quality of onlineassessments conducted during the pandemic is an important subject to be addressed. In this study,the quality of online assessments held in two consecutive semesters was investigated.MATERIALS AND METHODS: One thousand two hundred and sixty‑nine multiple‑choice onlineexaminations held in the first (n = 535) and second (n = 734) semesters in Birjand University ofMedical Sciences during 2020–2021 were examined. Mean, standard deviation, number of questions,skewness, kurtosis, difficulty, and discrimination index of tests were calculated. Data mining wasapplied using the k‑means clustering approach to classify the tests.RESULTS: The mean percentage of answers to all tests was 69.97 ± 19.16, and the number ofquestions was 34.48 ± 18.75. In two semesters, there was no significant difference between thedifficulty of examinations (P = 0.84). However, there was a significant difference in the discriminationindex, skewness, and kurtosis of tests (P < 0.001). Moreover, according to the results of the clusteringanalysis in the first semester, 43% of the tests were very hard, 16% hard, and 7% moderate. In thesecond semester, 43% were hard, 16% moderate, and 41% easy.CONCLUSION: To evaluate the tests’ quality, calculating difficulty and discrimination indices isnot sufficient; many factors can affect the quality of tests. Furthermore, the experience of the firstsemester had changed characteristics of the second‑semester examinations. To enhance the qualityof online tests, establishing appropriate rules to hold the examinations and using questions withhigher taxonomy are recommended.
