Student satisfaction with R vs. Excel in Data Mining and Business Analytics: A Herzberg's motivation‐hygiene theory perspective

Abstract

AbstractApplying Herzberg's motivation‐hygiene theory, we studied the determinants of student satisfaction in using R in a Decision Support Systems course that previously used Excel to teach Data Mining and Business Analytics (DMBA). The course is a degree requirement, and prior programming experience is not a prerequisite. We hypothesized that motivators for student satisfaction with R would include: (i) an intrinsic interest in DMBA, (ii) a perception that R is a better tool than Excel for DMBA, and (iii) a favorable view of R as a facilitator of career advancement. We postulated that the hygiene factor was the compulsory course requirement to learn R, a new and challenging language to students in this study. Data from 120 students, analyzed using Principal Component Analysis (PCA) and Generalized Additive Modeling (GAM), showed that motivators were positively related to satisfaction while hygiene factors were neutral. Students showed willingness to take on a harder challenge in exchange for intrinsic and future career benefits. The model can be useful in curriculum design or career advisement to increase student satisfaction in learning new software skills while meeting market demands.