A study of decision-making practices by urban Arizona public school principals: Data-driven decision-making praxis

The daily practices of educational leaders in today's public schools are shaped by the accountability movement as manifested in federal and state legislation. There are many areas where leaders are held accountable; among other issues today's school principals are responsible for (a) the overall performance of students within their schools upon state performance assessments, (b) ensuring alignment between mandated and delivered curriculum, (c) guarantee their schools are staffed with highly-qualified teachers, (d) testing a minimum number of students in specific sub-groups, and (e) meeting specific benchmark scores by student sub-group. In response to this external pressure is the emergence of the data-driven decision-making process, within the practices of some school administrators. The purpose of this qualitative research was to identify which aspects of the systematic use of data-driven decision-making within an iterative improvement cycle urban Arizona public school principals believe are essential to making tactical and operational decisions. The research questions guiding this inquiry were designed to investigate the depiction of data-driven decision-making relative to: (a) the process, strategies, and systems embodied within the school and individual shareholders that support effective data-driven decision-making; and (b) the data gathering and presentation processes which facilitate optimal data use in the decision-making process. Through purposive sampling eight urban Arizona public school principals who were recognized by district leadership as data-driven decision-making practitioners participated in open-ended interviews providing a robust data source pertaining to the practices and structures associated with data-use in a school environment. The theoretical framework guiding this investigation paralleled the findings of this study. The research participants noted that data-driven decision-making is an iterative improvement cycle with distinct processes described as: (a) goal and issue identification; (b) indicator selection; (c) data collection and analysis; (d) dissemination and dialogue; (e) action planning and implementation; (f) progress monitoring and documentation; and (g) continuous improvement. The use of data is supported by data which is aligned to the overarching goals established within the data-driven decision-making process. Extending beyond the theoretical framework is the identification of the impact of external forces upon the datadriven decision-making practices in public schools.