This research used multilevel modeling to investigate the perceived effect of a teacher preparation loan forgiveness program on recruiting science and mathematics majors to become teachers and teach in high-need schools. The study investigated how and which personal perceptions, characteristics, and teacher preparation program variables influenced…

Science, technology, engineering, and mathematics (STEM) teachers' perceptions about the influence of scholarship on their decision to teach and to teach in a high-needs school were examined using cluster analysis. Three hundred and four STEM scholars, who were currently teaching, and who received funding from 45 institutions located throughout…

This study examines the Noyce Program, which provides scholarships for STEM majors in return for teaching in high need schools. The perceptions of 555 scholarship recipients were investigated using hierarchical cluster analysis, confirmatory factor analysis, and Rasch analysis to determine how the scholarship influenced their commitments to…

Factor analysis was applied to analyze the Noyce Scholarship Program Evaluation Scholar Survey, and then further hierarchical linear modeling (HLM) was applied to differentiate the variance due to program effects from individual scholars' effects. This survey was constructed to determine scholars' perception of their individual teacher…