A Bayesian analysis of the institutional and individual factors influencing faculty technology use

Abstract

This study answered questions about which faculty come to use technology in their teaching and used a novel statistical analysis to develop a model that captures the primary factors influencing faculty technology use. It used a sample of 16,914 faculty within the 2004 National Study of Postsecondary Faculty to explore explanations for faculty technology use. A total of 41 variables were included to capture individual-level influences (both demographic and professional) and institution-level influences (e.g., level of resources, Carnegie classification, public or private control) on technology use. All of the variables were incorporated into a Bayesian network analysis that produced a model of seven variables that classified 69% of the sample accurately. Four of the seven variables point to the important influence of the faculty's instructional workload on whether and how much faculty use technology. Carnegie classification was the only institution-level variable to make it into the final model. The faculty's highest degree and teaching/research field also had direct and moderating influences on technology use. This model offers insights into who is using technology, why they do so, and how more faculty may be encouraged to acquire greater skills in using technology.