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Reliability of online dental final exams in the pre and post COVID-19 era: A comparative study

Author

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  • Hung Trong Hoang
  • Phuong Thao Nguyen
  • Nam Cong-Nhat Huynh
  • Tam Thi-Thanh Nguyen
  • Trang Thi Huyen Tu
  • Michael George Botelho
  • Lan Van Nguyen
  • Kaori Shima
  • Tomonori Sasahira

Abstract

Amidst the fourth COVID-19 wave in Viet Nam, national lockdowns necessitated the closure of numerous dental schools. To assess DDS (Doctor of Dental Surgery) graduation exams, this study analyzed their 2021 implementation in comparison to onsite exams conducted in 2020 and 2022 at the Faculty of Odonto-Stomatology, University of Medicine and Pharmacy at Ho Chi Minh City, Viet Nam (FOS-UMPH). The final online examination comprises two main sessions: a synchronous online examination using FOS-UMPH e-Learning for theories (consisting of 200 MCQs and 3 written tests with 3 clinical situations needed be solved) and a synchronous online examination using Microsoft Teams for practicum (comprising of 12 online OSCE stations). The final grades were evaluated using the same metrics in face-to-face final examinations in 2022 and 2020. A total of 114, 112 and 95 students were recruited for the first-time exams in 2020, 2021 and 2022, respectively. In order to analyze the reliability, histogram and k-mean clustering were employed. The histograms from 2020, 2021 and 2022 showed a striking similarity. However, fewer students failed in 2021 and 2022 (13% and 12.6%, respectively) compared to 2020 (28%), with clinical problem-solving part grades (belonging to theory session) being notably higher in 2021 and 2022. Intriguingly, the MCQ Score results showed the identical patterns. The courses of orthodontics, dental public health, and pediatrics subjects (in the group of prevention and development dentistry) stood out for their exceptional accuracy across both sessions. After examining data gathered over three years, we identified three distinct clusters: the first comprised of scattered average and low scores, the second characterized by high scores but unstable and scattered and the third cluster boasting consistently high and centered scores. According to our study, online and onsite traditional graduation exam results are relatively equivalent, but additional measures are necessary to standardize the final examination and adapt to the new normal trend in dental education.

Suggested Citation

  • Hung Trong Hoang & Phuong Thao Nguyen & Nam Cong-Nhat Huynh & Tam Thi-Thanh Nguyen & Trang Thi Huyen Tu & Michael George Botelho & Lan Van Nguyen & Kaori Shima & Tomonori Sasahira, 2023. "Reliability of online dental final exams in the pre and post COVID-19 era: A comparative study," PLOS ONE, Public Library of Science, vol. 18(5), pages 1-13, May.
  • Handle: RePEc:plo:pone00:0286148
    DOI: 10.1371/journal.pone.0286148
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    1. J. A. Hartigan & M. A. Wong, 1979. "A K‐Means Clustering Algorithm," Journal of the Royal Statistical Society Series C, Royal Statistical Society, vol. 28(1), pages 100-108, March.
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