Virtual Conference
July 26, 2021
July 26, 2021
July 19, 2022
Industrial Engineering
17
10.18260/1-2--37956
https://peer.asee.org/37956
1025
Sanaz Motamedi is faculty member at Industrial and System Engineering, the University of Florida after her postdoctoral fellowship at the California Partners for Advanced Transportation Technology program, University of California, Berkeley. Her research interests are human factors, user experience, engineering education, and transportation safety.
The COVID-19 pandemic disrupted instructional practices at educational institutions. Countermeasures included transitioning the majority of classes from primarily in-class learning to primarily eLearning. This shift has been met with varied levels of resistance and acceptance, while one study showed that 85% of higher education students prefer in-class learning [1]. Models developed years ago don’t account for the dynamic nature of the education world and the students within it. As a result, there is demand for an understanding of the unique set of needs presented by Generation Z, the population born between 1997 and 2015, during their college years.
The purpose of this study is to explore factors influencing Generation Z students’ eLearning acceptance by considering students' backgrounds such as behavioral and personality traits, level of academic success, and course of study. In this study, we conducted focus group discussions to explore all factors influencing eLearning acceptance of Generation Z. These focus groups were conducted with three groups of Industrial and Systems Engineering (ISE) students who have three or more courses at the University of Florida during the pandemic. As a result, the most relevant factors for Generation Z user acceptance that mentioned in the focus group discussions are compatibility, perceived cognitive absorption, perceived usefulness, service quality, system quality, information quality, accessibility, and privacy/security. Based on the findings from focus group discussions, theoretical foundations, and empirical evidence, we will hypothesize an innovative and integrated technology acceptance model for eLearning. In near future, we will analyze reliability of the models, fitness of the measured models, and convergent validity by performing confirmatory factor analysis (CFA). We also plan to study racial bias in E-learning. The framework and outcome of this study provide valuable guidelines for ISE departments that allow better understanding of Generation Z students' needs and their acceptance of e-learning.
Motamedi, S., & Marquis, K., & Levine, H. (2021, July), Understanding E-Learning Acceptance of Gen Z Students: An Extension of the Technology Acceptance Model (TAM) Paper presented at 2021 ASEE Virtual Annual Conference Content Access, Virtual Conference. 10.18260/1-2--37956
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