Teacher Evaluation Through the Eyes of the Principal: How Individual and School Contexts Shape Perceptions of Practice

ABSTRACT

The current study explores how principals (n = 568) experience a new teacher evaluation model under Race to the Top. Findings suggest that principals felt the least confident in their ability to identify teacher behaviors associated with student achievement gains and placed the least value on student achievement data. Evaluation experience predicted principals’ knowledge and ability, which, in turn predicted valuation of data sources. Principals’ valuation of data sources varied by accountability and locale. Findings help policymakers, principal educators, and professional development providers understand the role of individual and school contexts in how principals approach new teacher evaluation models.

Acknowledgments

We would like to thank the participants in our research study and pilot study who shared their voices and experiences related to teacher evaluation, and the two organizations that supported study recruitment. We would like to extend our gratitude to Caroline Reina for her help in writing an earlier version of the text, Tom Good for feedback on earlier stages of the research, and Karine Ivy and Michelle O’Connor for their help with manuscript preparation. This work was supported, in part, by a research sabbatical and a summer research grant from Roosevelt University.

Disclosure statement

No potential conflict of interest was reported by the authors.

Notes

1. The new model requires 3 formal and 3 informal observations – a number that principals felt was too high.

2. Tschannen-Moran and Woolfolk Hoy (2007) found that self-efficacy levels of novices are determined, in part, by access to resources and support.

3. Cannata et al. (2017) found that central offices played a key mediating role in how principals thought about and used teacher evaluation data in hiring decisions. Principals in high-structure systems that were held accountable for using data in hiring decisions were more likely to do so.

4. Reinhorn et al. (2017) examined the implementation of teacher evaluation policy in six high-performing, high-poverty schools.

5. These new RTTT teacher evaluation models require more measures of teachers’ effectiveness, particularly for beginning teachers and those in need of improvement. Teacher evaluation models are based on multiple measures of teaching effectiveness (e.g., observational data, student achievement gains, lesson plans, student work, teachers’ reflections on teaching, parent feedback, student surveys). Student achievement growth must be one significant measure of teacher effectiveness, with most states assigning the greatest weights to principal observation data followed by student achievement (USDOE, 2010). States and districts may also use teacher evaluation data to inform hiring, firing, and the granting of tenure (e.g., District of Columbia Public Schools, 2016).

6. This response rate is slightly lower than the average response rate of 30% for online surveys (see Nulty, 2008 for an extended discussion).

Additional information

Funding

This work was funded by an internal grant through an institution, Roosevelt University.