Statistical Skills Gaps of Professors of Education at U.S. Universities and HBCUs

Abstract

Abstract This study aims to identify some perceived gaps in a selection of statistical skills and software abilities of professors of education in United States colleges and universities. In addition to a general U. S. sample, a sample of education professors in Historically Black Colleges and Universities (HBCUs) was examined in order to understand their unique needs. Results showed that many professors from both samples felt they were weak in their abilities with more advanced statistical methods such as structural equation modeling and propensity score matching. Professors of education at HBCUs, however, had significant perceived skill-need methodology gaps in most of the methodologies evaluated. The general U.S. sample indicated a skill-need gap with statistical software packages such as R, and the HBCU sample indicated a skill-need gap with all five software packages evaluated (Excel, SPSS, SAS, Stata, and R). Affordable training workshops addressing the greatest areas of perceived need should be helpful in reducing this skill-need gap.