Asee peer logo

Impact of Students’ Backgrounds on Online Learning Behavior: Generation Z Technology Acceptance of E-Learning Technology during COVID-19

Download Paper |

Conference

2024 ASEE Annual Conference & Exposition

Location

Portland, Oregon

Publication Date

June 23, 2024

Start Date

June 23, 2024

End Date

July 12, 2024

Conference Session

NEE Technical Session 3 - Courses: development, logistics, and impact

Tagged Division

New Engineering Educators Division (NEE)

Tagged Topic

Diversity

Permanent URL

https://peer.asee.org/47564

Request a correction

Paper Authors

biography

Sanaz Motamedi University of Florida Orcid 16x16 orcid.org/0000-0002-5389-1017

visit author page

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

visit author page

author page

Viktoria Medvedeva Marcus University of Florida

Download Paper |

Abstract

The COVID-19 pandemic necessitated a swift transition from in-person to online learning, eliciting a spectrum of responses from students and prompting numerous institutions to develop online programs. Our study explores the challenges Generation Z students faced during the COVID-19 pandemic, with a specific focus on understanding how their backgrounds influenced their interactions with e-learning platforms, including their learning styles, personalities, GPA, housing, voluntariness of use, and quality of internet access. To acquire comprehensive data, we formulated an online survey targeting Generation Z university students with multiple semesters of online learning experience from multiple disciplines including engineering, business, journalism, law, fine arts, education, biology, and more. This survey aimed to collect information on their demographic details, personality traits, learning styles, and perceptions of their online learning experience using the Technology Acceptance Model (TAM) which has been used repetitively in literature. With 1000 valid responses, the survey yielded a substantial dataset for in-depth analysis. After cleaning and transforming the data, we had 948 data points with which to conduct a series of ANOVA analyses; it was found that learning style, personality, and quality of internet access had significant relationships with every TAM factor, including actual use, behavioral intention to use, perceived usefulness, and perceived ease of use. GPA and voluntariness had significant relationships with actual use and perceived usefulness. Housing had no effect on any of the TAM factors. This study provides valuable insights into how students' unique backgrounds shape their educational journeys, insights which program managers and new educators can utilize to inform the design of new programs.

Motamedi, S., & Marcus, V. M. (2024, June), Impact of Students’ Backgrounds on Online Learning Behavior: Generation Z Technology Acceptance of E-Learning Technology during COVID-19 Paper presented at 2024 ASEE Annual Conference & Exposition, Portland, Oregon. https://peer.asee.org/47564

ASEE holds the copyright on this document. It may be read by the public free of charge. Authors may archive their work on personal websites or in institutional repositories with the following citation: © 2024 American Society for Engineering Education. Other scholars may excerpt or quote from these materials with the same citation. When excerpting or quoting from Conference Proceedings, authors should, in addition to noting the ASEE copyright, list all the original authors and their institutions and name the host city of the conference. - Last updated April 1, 2015