Published May 18, 2021 | Version original
Journal article Open

Impact of Remote Work during Pandemic COVID-19 in University Education

  • 1. 1College of Medicine, Imam Abdulrahman Bin Faisal University, P. O. Box. 1982, Dammam 31441, Saudi Arabia.
  • 2. 2College of Dentistry, Imam Abdulrahman Bin Faisal University, P. O. Box. 1982, Dammam 31441, Saudi Arabia.
  • 3. 3Department of Chemistry, College of Science, Imam Abdulrahman Bin Faisal University, P. O. Box. 1982, Dammam 31441, Saudi Arabia.
  • 4. 4Deanship of Scientific Research, Imam Abdulrahman Bin Faisal University, P. O. Box. 1982, Dammam 31441, Saudi Arabia.
  • 5. 5Deanship of eLearning & Distance Learning, Imam Abdulrahman Bin Faisal University, P. O. Box. 1982, Dammam 31441, Saudi Arabia.
  • 6. 6Deanship of eLearning & Distance Learning, Imam Abdulrahman Bin Faisal University, P. O. Box. 1982, Dammam 31441, Saudi Arabia.
  • 7. 7Deanship of Quality and Academic Accreditation, Imam Abdulrahman Bin Faisal University, P. O. Box. 1982, Dammam 31441, Saudi Arabia.

Description

Background: COVID-19 pandemic and second wave precautions has dramatically affected the health, education, and economy of human society. The present medical emergency has suddenly affected onsite routine working environments of University including administration, academic and research. A survey conducted to study the impact of remote working of faculty members in Imam Abdulrahman Bin Faisal University (IAU).

Methods - The study evaluates six major feel parameters using QuestionPro survey, assessed the reliability and constructed variables associated with remote work efficiency. A total of 484 faculty and staff members of IAU has responded to the survey. Out of them, 287 completed surveys were received with the response rate observed as 59.3%. Faculty perception are considered with regard to demographic differences. The reliability value of Cronbach’s a coefficient indicated high degree and reliable (0.83). Percentage of respondents was analysed on working variables. Structural equation modeling (SEM) was used to estimate the variables associated with the model.

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