# Abstract --- ### Specific Application The development and validation of a self-report measure of school and district policy makers' capacity to access, receive, and use research. ### Sources for This Method Penuel, W. R., Briggs, D. C., Davidson, K. L., Herlihy, C., Sherer, D., Hill, H. C., Farrell, C., & Allen, A.-R. (2017). How School and District Leaders Access, Perceive, and Use Research. *AERA Open*. https://doi.org/10.1177/2332858417705370 Penuel, W.R., Briggs, D.C., Davidson, K.L, Herlihy, C., Sherer, D., Hill, H.C., Farrell, C.C., & Allen, A-R. (2016). *Findings from a national survey of research use among school and district leaders* (Technical Report No. 1). Boulder, CO: National Center for Research in Policy and Practice. http://ncrpp.org/assets/documents/NCRPP_Technical-Report_180302.pdf ### Instrument Origins See [SPUR Survey Instrument][1]. ### Participant Selection Seven categories of district and school roles were targeted for this study: 1) deputy, associate, and network superintendents; 2) curriculum supervisors; 3) special education supervisors; 4) accountability, assessment, and research coordinators; 5) directors of federal, bilingual, and English-as-a-second-language programs; 6) “multirole” central office leaders, classified in more than one of the aforementioned roles; and 7) elementary, middle school, and K–8 principals. A sampling frame with the individuals in the above seven roles in each eligible district was purchased from MDR. This approach generated a sampling frame consisting of over 41,000 individuals in the 1,000 largest school districts, from which the study selected its final sample. A stratified random sampling approach was used to create a final sample that included 14 strata based on a crossing of the 7 roles and 2 levels of district size. Refining the sample resulted in a final field test sample consisting of 733 people from 487 school districts across 423 cities and 45 states. A smaller reservoir sample was created in case additional participants were needed due to low response rates in any stratum. ### Administration Online via Qualtrics, with an 8-week recruitment window for each respondent. ### Analysis of Survey Technical Characteristics Sampling weights used to allow for unbiased inferences for combinations and comparisons of target populations. *Internal consistency:* Cronbach’s alpha for each scale *Descriptive statistics for each scale:* Mean, Standard deviation ### Analysis of Relationships of Survey Results to Other Variables *Response frequencies by item for sample and by specific roles* *Differences in responses on open-ended item:* counts of Chi-square analyses were used to compare counts of codes between groups. ### Complementary Methods **Multiple-case study:** Penuel, W. R., Farrell, C. C., Anderson, E. R., Coburn, C. E., Allen, A.-R., Bohannon, A. X., Hopkins, M., & Brown, S. (2020). *A comparative, descriptive study of three research–practice partnerships: Goals, activities, and influence on district policy, practice, and decision making.* National Center for Research in Policy and Practice. [Used measures in study of three different RPPs] http://ncrpp.org/assets/documents/Study-2-Technical-Report.pdf **Validity study for items related to knowledge of research use:** See [Hill & Briggs (2020) - Knowledge of Causal Research Design and Statistics - Survey Validation Protocol][2] - Hill, H. C., & Briggs, D. C. (2020). Education leaders’ knowledge of causal research design: A measurement challenge. Annenberg Institute. https://doi.org/10.26300/vxt5-ws91 ### Author Contact Research community members may contact NCRPP researchers regarding questions about the survey and analyses by emailing william.penuel@colorado.edu and caitlin.farrell@colorado.edu. [1]: https://osf.io/5fpgz/ [2]: https://osf.io/vfz7h/