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Article type: Research Article
Authors: Nyarko, Erica | Agyemang, Edmund Fosua; b; * | Arku, Dennisa
Affiliations: [a] Department of Statistics and Actuarial Science, School of Physical and Mathematical Sciences, University of Ghana, Legon, Accra, Ghana | [b] Department of Computer Science, Ashesi University, Berekuso, Accra, Ghana
Correspondence: [*] Corresponding author: Edmund Fosu Agyemang, Department of Statistics and Actuarial Science, School of Physical and Mathematical Sciences, University of Ghana, Box LG 115, Legon, Accra, Ghana; and Department of Computer Science, Ashesi University, No. 1 University Avenue, Berekuso, Accra, Ghana. E-mail: [email protected].
Abstract: The Sars-Cov-2 coronavirus outbreak significantly impacted Ghana’s educational system, driving schools to close campuses and swiftly deploy online instruction. This study evaluated e-teaching in higher education amidst the Sars-Cov-2 coronavirus by using the University of Ghana as a case study. Specifically, the study investigated university instructors’ preferences for online instructional strategies to enable higher educational institutions to transit smoothly into online teaching and learning. With the help of a face-to-face questionnaire administration, this cross-sectional study used a discrete choice experiment design to capture the responses of 230-course instructors. The analysis of the survey data obtained was possible using the multinomial logit model. Our results revealed that a recorded lecture video had the highest preference among the course instructors, breakdown of teaching content for approximately 30 to 45 minutes, providing online tutorials, and online support/video tutoring from teaching assistants were the important instructional attributes to help higher educational institutions transition into online teaching and learning.
Keywords: Discrete choice experiments, COVID-19, high-impact teaching practices, online education, instructional strategies, multinomial logit model
DOI: 10.3233/MAS-221403
Journal: Model Assisted Statistics and Applications, vol. 18, no. 2, pp. 115-123, 2023
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