Role of Course and Individual Characteristics in the Course-level Persistence Intentions of Online Undergraduate Engineering Students: A Path Analysis

Javeed Kittur, Samantha Brunhaver, Jennifer Bekki, Eunsil Lee

Research output: Chapter in Book/Report/Conference proceedingConference contribution

1 Scopus citations

Abstract

Online learning is increasing in both enrollment and importance within engineering education. Online courses also continue to confront comparatively higher course dropout levels than face-to-face courses. This research paper thus aims to better understand the factors that contribute to students' choices to remain in or drop out of their online undergraduate engineering courses. Path analysis was used to examine the impact of course perceptions and individual characteristics on students' course-level persistence intentions. Specifically, whether students' course perceptions influenced their persistence intentions directly or indirectly, through their expectancies of course success, was tested. Data for this study were collected from three ABET-accredited online undergraduate engineering programs at a large public university in the Southwestern United States: electrical engineering, engineering management, and software engineering. A total of 138 students participated in the study during the fall 2019 (n=85) and spring 2020 (n=53) semesters. Participants responded to surveys twice weekly during their 7.5-week online course. The survey asked students about their course perceptions related to instructor practices, peer support, and course difficulty level, their expectancies in completing the course, and their course persistence intentions. This work is part of a larger National Science Foundation-funded research project dedicated to studying online student course-level persistence based on both students' self-report data and course learning management system (LMS) activity. The survey sample was consistent with reports indicating that online learners tend to be more diverse than face-to-face learners. Findings from the path analysis revealed that students' perceptions of course LMS fit, perceived course difficulty, and expectancies of course success positively and significantly predicted persistence intentions, making them the most important influences. Expectancies of course success had a direct effect on persistence intentions. The findings underscore needs to elucidate further the mechanisms through which expectancies of success influence persistence.

Original languageEnglish (US)
Title of host publication9th Research in Engineering Education Symposium and 32nd Australasian Association for Engineering Education Conference, REES AAEE 2021
Subtitle of host publicationEngineering Education Research Capability Development
EditorsSally Male, Sally Male, Andrew Guzzomi
PublisherResearch in Engineering Education Network
Pages316-324
Number of pages9
ISBN (Electronic)9781713862604
DOIs
StatePublished - 2021
Event9th Research in Engineering Education Symposium and 32nd Australasian Association for Engineering Education Conference: Engineering Education Research Capability Development, REES AAEE 2021 - Perth, Australia
Duration: Dec 5 2021Dec 8 2021

Publication series

Name9th Research in Engineering Education Symposium and 32nd Australasian Association for Engineering Education Conference, REES AAEE 2021: Engineering Education Research Capability Development
Volume1

Conference

Conference9th Research in Engineering Education Symposium and 32nd Australasian Association for Engineering Education Conference: Engineering Education Research Capability Development, REES AAEE 2021
Country/TerritoryAustralia
CityPerth
Period12/5/2112/8/21

Keywords

  • course perceptions
  • Online learning
  • persistence

ASJC Scopus subject areas

  • General Engineering
  • Education

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