School districts face unique challenges as they implement social and emotional learning (SEL) initiatives, particularly when choosing or developing a high-quality scale to measure non-academic competencies. Like collaborations with the CORE school districts described by West, Buckley, et al. (2018) and the Washoe County School District described by Davidson et al. (2018), Alpine School District (ASD) partnered with Brigham Young University (BYU) to develop a scale (80 items) that reflected their Vision for Learning framework. In this pilot study, I describe the collaborative and iterative process used to develop a shortened version of the ASD Social and Emotional Well-Being Scale Beta Form A (23 items), which was administered to 461 secondary level students in the Spring of 2021. I implemented a relatively novel approach of comparing the results from exploratory structural equation modeling (ESEM) with target rotation with the results obtained from the more traditional confirmatory factor analysis (CFA) as a part of the iterative process. The scores of the resulting shortened version achieved acceptable fit (CFI = .97, TLI = .96, SRMR = .03, RMSEA = .06), high factor loadings (M = .80, SD = .09), high reliability indices by sub-scale (M = .94, SD = .03), and measurement invariance across gender and school level. I discuss insights that resulted from this novel approach in the development process, and make recommendations for its use, specifically in the field of SEL measurement. I end by encouraging the collaborative efforts between practitioners and researchers as a way of increasing capacities within districts, facilitating larger scale research, and ensuring the usefulness of findings.



College and Department

David O. McKay School of Education; Educational Inquiry, Measurement, and Evaluation



Date Submitted


Document Type





structural equation models, factor analysis, measures (individuals), interpersonal competence, school culture, school surveys



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Education Commons