- Year 2019
- NSF Noyce Award # 1557273
- First Name Catherine
- Last Name Horn
- Discipline Biology, Math, Physics
Paige Evans, University of Houston, pkevans@Central.UH.EDU
Donna Stokes, University of Houston, dwstokes@Central.UH.EDU
Vera Hutchison, University of Houston, LHutchison@Central.UH.EDU
Andrea Burridge, Houston Community College System, email@example.com
Catherine Horn, University of Houston, firstname.lastname@example.org
Much has been written about the influences on a novice teacher’s decision to remain or withdraw from the profession (e.g., Cochran-Smith, 2004; Boyd, Grossman, Ing, Lankford, & Wyckoff, 2011; Ingersoll, Merrill, & May, 2014; Papay, Bacher-Hicks, Page, & Marinell, 2015; Robertson-Kraft & Duckworth, 2014). In sum, as Guarino, Santibañez, and Daley (2006) note in a review of the related empirical literature, “the entry, mobility, and attrition patterns…indicate that teachers exhibit preferences for higher salaries, better working conditions, and greater intrinsic rewards and tend to move to other teaching positions or to jobs or activities outside teaching that offer those characteristics when possible” (p. 201).
For teacher candidates who enter and remain in the teaching profession how do Noyce and non-Noyce participants compare with respect to: individual characteristics of those who are placed in a position? characteristics of the schools and K-12 students they serve? mobility and retention patterns (within and across schools and districts?
In order to investigate retention of employed teachers in the high needs schools and in the profession overall, a set of event history analyses will be conducting using the following dichotomous dependent variables: employment in a public or charter school in the state of Texas for a given year and retention in high needs schools. A secondary competing risks analysis will assess the likelihood of leaving school versus leaving the field. The independent variables, further informed by information gathered from the focus group analyses, will include program experiences, school characteristics, and other time-invariant characteristics. Additionally, models will be run to include time-varying covariates, such as school composition, to control for its varying influence on the likelihood of retention.
The research literature on the effects of teacher preparation on teacher outcomes remains largely descriptive (e.g., Dean et al., 2005) with few large-scale studies focused on outcomes. The shift to an emphasis on student outcomes, brought about by No Child Left Behind, has left a large gap in our robust understanding concerning how teacher preparation contributes to teacher effectiveness in the classroom, and what types or components of preparation contribute either directly or indirectly to the development and retention of teachers. The wide variety of program variability within preparation has made it difficult to study preparation effects (Levine, 2006). By combining research capacity across eight institutions and their respective students and school districts, it is possible to develop a more complex lens in which to investigate preparation program components and outcomes and compare the effects of differential preparation on teacher outcomes.
As the NRC (2010), notes, the limited availability of rigorous quantitative studies means that “For many questions, researchers are grappling with fundamental issues of theory development, formulating testable hypotheses, developing research designs to empirically test these theories, trying to collect the necessary data, and examining the properties of a variety of emerging empirical models” (p. 30). Toward that end, the results of this study both inform understanding of the range of policies that are influencing educator preparation programs and may ultimately, therefore, be useful in considering how that lever might be best used.