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Adaptation of AL-TST active learning model in hybrid classroom: Findings from teaching during COVID-19 pandemic in Egypt.

Authors :
Hasnine, Mohammd Nehal
Ueda, Hiroshi
Ahmed, Mahmoud Mohamed Hussien
Source :
Procedia Computer Science; 2022, Vol. 207, p3226-3233, 8p
Publication Year :
2022

Abstract

Since COVID-19 began, the ways of teaching and learning have changed drastically. Traditional teaching methods are shifted to technology-mediated methodologies such as asynchronous online learning, hybrid learning, blended learning, hy-flex learning, on-demand learning, and competency-based online learning. Due to the COVID-19 pandemic, traditional active learning models, compelling but complex, are assumed not to fit in the hybrid classroom because of the affordance and integration of various distance learning technologies. Hence, in the research, a conceptual active learning model for a hybrid classroom, namely AL-TST (Active Learning-Theory, Strategy, Technology), is used to deliver a STEM course in an Egyptian university. The course was an 8-week-long course designed for 3rd grade (i.e., university junior) students enrolled in the university. At the beginning of the course, the instructor created student-centered lecture contents using the adopted AL-TST model in a hybrid environment. Data (N=76) were collected using the university's learning management system (LMS). Students' Course Work Grades, Final Exam Grades and Total Exam Grades are analyzed using a one-sample t-test. The analysis indicated no significant result in students' Course Work Grades, Final Exam Grades and Total Exam Grades. However, the findings indicated some valuable educational insights, such as improving a conceptual active learning model, the perception of course design, and teaching during the crisis. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
18770509
Volume :
207
Database :
Supplemental Index
Journal :
Procedia Computer Science
Publication Type :
Academic Journal
Accession number :
159755951
Full Text :
https://doi.org/10.1016/j.procs.2022.09.380