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Purpose: Teachers’ satisfaction with their jobs has reached the lowest point in 25 years. One contributing factor is when teachers experience information-poor hiring processes and do not obtain an accurate preview of their positions, their person–organization (P-O) fit, and person–job (P-J) fit. Sparked by a renewed focus on the variables that can influence teacher satisfaction, the purpose of this study was to examine the relationships among accurate job preview, P-O and P-J fit, and job satisfaction among teachers. Research Approach: Drawing on existing literature, a mediation model was hypothesized. Using existing data collected by the Center for Research, Evaluation, and Advancement of Teacher Education, a structural equation model was tested with a sample of 729 newly hired teachers. Specifically addressed was the extent to which P-O and P-J fit mediated the relationship between accurate job preview and satisfaction. Findings: Accurate job preview predicted future P-O and P-J fit. Higher levels of P-O and P-J fit were linked to higher teacher satisfaction rates. Accurate job previews worked through P-J fit and P-O fit to result in increased teacher satisfaction. Additionally, 53.3% of the variance in satisfaction with the campus was explained by the model. Implications for Research and Practice: Providing newly hired teachers with accurate job previews was related to higher satisfaction rates, so school and district leaders should consider ways to increase candidates’ knowledge during the hiring process about specific school settings and students’ needs.

The purpose of this methodological article is to provide a primer for conducting a mixed analysis—the term used for analyzing data in mixed research. Broadly speaking, a mixed analysis involves using quantitative and quantitative data analysis techniques within the same study. In particular, a heuristic example using real data from a published study entitled “Perceptions of Barriers to Reading Empirical Literature: A Mixed Analysis” (Benge, Onwuegbuzie, Burgess, & Mallette, 2010) is used with the aid of screenshots to illustrate how a researcher can conduct a quantitative dominant mixed analysis, wherein the quantitative analysis component is given higher priority and qualitative data and analysis is incorporated to increase understanding of the underlying phenomenon.

In this study, the authors examined the college-ready graduate rates of all students ( n = 1,099 high schools) in the State of Texas for the 2006-2007 school year. Data were analyzed for students’ scores in reading, in math, and in both subject areas combined. Approximately one-third of all students were determined to be college-ready in both subject areas. Statistically significant and practically relevant differences, reflecting moderate to large effect sizes, were present in reading, math, and both subjects among Hispanic, African American, and White students. Concerns are expressed about the lack of preparedness of students for college and about the presence of strong achievement differences as a function of ethnicity. Implications of these findings are discussed.

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