A Measure of College Student Persistence in the Sciences (PITS).
Curricular changes that promote undergraduate persistence in science, technology, engineering, and mathematics (STEM) disciplines are likely associated with particular student psychological outcomes, and tools are needed that effectively assess these developments. Here, we describe the theoretical basis, psychometric properties, and predictive abilities of the Persistence in the Sciences (PITS) assessment survey designed to measure these in course-based research experiences (CREs). The survey is constructed from existing psychological assessment instruments, incorporating a six-factor structure consisting of project ownership (emotion and content), self-efficacy, science identity, scientific community values, and networking, and is supported by a partial confirmatory factor analysis. The survey has strong internal consistency (Cronbach's alpha: α = 0.96) and was validated using standard simple and multiple regression analyses. The regression analyses demonstrated that the factors of the PITS survey were significant predictors of the intent to become a research scientist and, as such, potentially valid for the measurement of persistence in the sciences. The PITS survey provides an effective method for measuring the psychological outcomes of undergraduate research experiences relevant to persistence in STEM and offers an approach to the development and validation of more sophisticated assessment tools that recognize the specificities of the type of educational opportunities embedded in a CRE.
Department of English, Indiana University of Pennsylvania, Indiana, PA 15705 hanauer@pitt.edu.
David I
DI
Hanauer
Yale Center for Teaching and Learning, Yale University, New Haven, CT 06510.
Mark J
MJ
Graham
Department of Biological Sciences, University of Pittsburgh, Pittsburgh, PA 15260.
Graham F
GF
Hatfull
D003479:Curriculum; D003710:Demography; D005260:Female; D006801:Humans; D008297:Male; D017145:Models, Educational; D011594:Psychometrics / Q000379:methods*; D012044:Regression Analysis; D012106:Research; D012586:Science; D013334:Students; D014495:Universities