Methods matter: A multi-trait multi-method analysis of student behavior

Autor: Faith G. Miller, Megan E. Welsh, Gregory A. Fabiano, T. Chris Riley-Tillman, Austin H. Johnson, D. Betsy McCoach, Sandra M. Chafouleas, Huihui Yu
Rok vydání: 2018
Předmět:
Zdroj: Journal of School Psychology. 68:53-72
ISSN: 0022-4405
DOI: 10.1016/j.jsp.2018.01.002
Popis: Reliable and valid data form the foundation for evidence-based practices, yet surprisingly few studies on school-based behavioral assessments have been conducted which implemented one of the most fundamental approaches to construct validation, the multitrait-multimethod matrix (MTMM). To this end, the current study examined the reliability and validity of data derived from three commonly utilized school-based behavioral assessment methods: Direct Behavior Rating – Single Item Scales, systematic direct observations, and behavior rating scales on three common constructs of interest: academically engaged, disruptive, and respectful behavior. Further, this study included data from different sources including student self-report, teacher report, and external observers. A total of 831 students in grades 3–8 and 129 teachers served as participants. Data were analyzed using bivariate correlations of the MTMM, as well as single and multi-level structural equation modeling. Results suggested the presence of strong methods effects for all the assessment methods utilized, as well as significant relations between constructs of interest. Implications for practice and future research are discussed.
Databáze: OpenAIRE
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