Drivers of Student Learning Success in Business Analytics: A Model Investigating Learning Outcomes and Intentions

Authors

Mandy Yan Dang, Northern Arizona UniversityFollow
Yulei Gavin Zhang, Northern Arizona UniversityFollow
M. David Albritton, Northern Arizona UniversityFollow
Bo Wen, Northern Arizona UniversityFollow

Abstract

In response to the heavy demand for business analysts in various industries, many universities have developed business analytics-related courses and programs, which aim to develop a competent labor force that can help companies make sense of business data and generate sustainable competitive advantages. Ensuring high levels of student success in these courses and programs is essential to achieving this goal. This study developed and tested a research model investigating important psychological factors, including learning motivation, teaching presence and cognitive gains, that can influence student learning outcomes in business analytics. The results indicate that both motivation and teaching presence could significantly influence learning effort. Additionally, cognitive gains had a significant impact on the perceived usefulness of the subject. Subsequently, the combined influence of learning effort and subject usefulness significantly affected student learning outcomes, which in turn impact future learning intentions.

DOI

https://doi.org/10.62273/FGLP8225

Recommended Citation

Dang, Mandy Yan; Zhang, Yulei Gavin; Albritton, M. David; and Wen, Bo (2024) "Drivers of Student Learning Success in Business Analytics: A Model Investigating Learning Outcomes and Intentions," Journal of Information Systems Education: Vol. 35 : Iss. 4 , 512-524.
DOI: https://doi.org/10.62273/FGLP8225
Available at: https://aisel.aisnet.org/jise/vol35/iss4/10