Journal of Information Systems Education
Investigating the Factors That Engage Students to Be Successful in Hybrid Business Analytics Courses
Abstract
Business analytics is an emerging and prominent tool in many industries seeking to exploit the advantages of data-driven decision making. Simultaneously, educational institutions are developing and delivering business analytics offerings to equip business professionals with the tools necessary to implement business analytics in modern businesses. In addition to traditional educational delivery methods, these courses are increasingly delivered in online and hybrid formats, which promote efficiency, productivity, effectiveness, and quality. This research investigates students’ success factors in hybrid business analytics courses. Specifically, the study seeks to determine the impact of computer self-efficacy (CSE) and math self-efficacy (MSE) on student engagement, course satisfaction, and course success in hybrid business analytics courses. Utilizing structural equation modeling (SEM) to analyze the responses of students enrolled in hybrid business analytics courses, the results indicate that computer self-efficacy leads to math self-efficacy. Additionally, math self-efficacy, rather than computer self-efficacy, impacts student engagement. Furthermore, student engagement predicts course satisfaction and student success in hybrid business analytics courses. As business schools continue to offer more hybrid courses, understanding the factors that influence a student’s success and satisfaction with these challenging courses can be beneficial in developing and teaching these courses as well as assist in keeping students on track for graduation.
DOI
https://doi.org/10.62273/CSVP4044
Recommended Citation
Carraher-Wolverton, Colleen; Lai, Guolin; Navarre, Jeremy T.; Davis, Dione; and Lanier, Patricia
(2025)
"Investigating the Factors That Engage Students to Be Successful in Hybrid Business Analytics Courses,"
Journal of Information Systems Education: Vol. 36
:
Iss.
4
, 417-431.
DOI: https://doi.org/10.62273/CSVP4044
Available at:
https://aisel.aisnet.org/jise/vol36/iss4/8
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