Is Policymaking Data-Driven? A Mixed Methods Study on the Use of Teacher Assessment Results for Professional Development Policies in Peru

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Abstract/Contents

Abstract: This study explores the purpose of Peruvian professional development policies and the extent to which they are driven by results from national teacher assessments. Using a mixed methods approach, the author analyzes the convergence of the policies with the results of the Prueba Única Nacional. The findings suggest that although the policies highlight the need to strengthen teachers’ pedagogical skills, they leave the implementation of professional development unclear and fail to establish a data collection mechanism that allows for a systematic review of teachers’ needs. The study concludes that data resulting from national assessments are not being used effectively to inform PD policy design, and provides policy recommendations regarding teacher professional development in Peru.

Type of resource	text
Date created	August 2020

Author	Gamboa Zapatel, Daniela

Subject	teacher professional development
Subject	education policy
Subject	teacher assessment
Subject	datadriven
Subject	mixed methods
Subject	Peru
Subject	Stanford Graduate School of Education International Education Policy Analysis
Genre	Thesis

Related item	Title Stanford Graduate School of Education International Comparative Education
Location	https://purl.stanford.edu/sp870sp0120

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License: This work is licensed under a Creative Commons Attribution Non Commercial 3.0 Unported license (CC BY-NC).

Graduate School of Education International Comparative Education Master's Monographs

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