Predicting the Performance of Faculty Members of Medical Universities in Providing Virtual Learning in the Covid-19 Pandemic in terms of Problem-Solving Methods and Their Individual Social Characteristics: A Data Mining Study

Sattari, Mohammad; Samouei, Rahele

Volume 80, Issue 12 (March 2023) Tehran Univ Med J 2023, 80(12): 986-991 | Back to browse issues page

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Sattari M, Samouei R. Predicting the Performance of Faculty Members of Medical Universities in Providing Virtual Learning in the Covid-19 Pandemic in terms of Problem-Solving Methods and Their Individual Social Characteristics: A Data Mining Study. Tehran Univ Med J 2023; 80 (12) :986-991
URL: http://tumj.tums.ac.ir/article-1-12194-en.html

Predicting the Performance of Faculty Members of Medical Universities in Providing Virtual Learning in the Covid-19 Pandemic in terms of Problem-Solving Methods and Their Individual Social Characteristics: A Data Mining Study

Mohammad Sattari ^*

¹, Rahele Samouei²

1- Health Information Technology Research Center, Isfahan University of Medical Sciences, Isfahan, Iran.
2- Social Determinants of Health Research Center, Isfahan University of Medical Sciences, Isfahan, Iran.

Abstract: (871 Views)

Background: In the Covid-19 Pandemic, virtual education in universities became essential and came with some challenges, especially for professors who had the role of presenters. In this regard, the study was conducted to predict the performance of professors in providing virtual training in Covid-19 in terms of problem-solving methods and their demographics.
Methods: A descriptive-analytical study was performed on 252 professors of Iranian universities of medical sciences from 2021 April to 2021. Also, demographic characteristics such as gender, field of study, position, job rank and work experience were asked. The faculty members' performance questionnaire in providing virtual training (α=0.89) and the problem-solving methods questionnaire (α=0.75) was administered virtually and the data were analyzed by Random forest, CHAID and ID3 techniques.

Results: Based on used data mining methods findings, factors related to teachers' satisfaction with their performance in providing virtual education were "the possibility of monitoring the performance of homework", "establishing order and regulations", "preparing standard educational content", "using multimedia content", "Mastery of software, educational systems, and multimedia content", and "possibility of examining the quality and quantity of students' learning". Also, interpersonal problem-solving methods, such as "believing in the role of personality traits of people in their behavior", "solving problems with effort and follow-up", "notifying people's mistakes in interpersonal interactions", "giving people the opportunity to check their behavior", "proposing solutions to solve problems for the benefit of both parties", and "dividing big problems into smaller parts" have played a big role in professors' satisfaction about their teaching methods. These characteristics are related to more basic areas such as self-regulation, pursuit and challenge, agreeableness, and realism.
Conclusion: The results of the study showed that the performance of teachers in providing virtual education is influenced by some behavioral factors and individual situational abilities. However, despite the virtual training implementation difficulties, it is a productive opportunity that can be used in the days of returning for conditions (after-covid 19 condition) without physical distance along with face-to-face training.

Keywords: pandemic covid 19, problem solving, virtual education.

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Type of Study: Original Article |