Education leaders must build data literacy skills

January 27, 2020
Rhoads_Matthew_RYCU
Matthew Rhoads, Ed.D., an educational specialist out of San Diego, wrote the dissertation “Educational Leadership Efficacy: The Relationship Between Data Use, Data Use Confidence, Leadership Efficacy, and Student Achievement” for his doctorate of education degree from Concordia University, Irvine, 2019. The following is a summary of that dissertation, which is available in full on ProQuest. Data is changing 21st century K-12 education. Educational leaders like superintendents, principals, assistant principals, coordinators and teacher-leaders are bombarded with new technology and data within classrooms, schools and districts. Due to this overwhelming amount of data that is collected, educational leaders need to learn how to make data-driven decisions to improve outcomes for the students and teachers they serve. Therefore, there has been a call from prominent researchers like Mandinach, Fullan and Bernhardt for increased data use and literacy among educational leaders in K-12 schools and districts because leaders must learn to harness the power of data to improve their capacity to make decisions for the educational organizations they lead.   In his study, Matthew Rhoads set out to determine whether relationships exist between the following variables: data use, data use confidence, educational leadership efficacy and student achievement. Also, the study set out to further evaluate how educational leaders employ data practices in their capacity as a leader, as well as how they establish and participate in data-driven cultures in K-12 settings.  Rhoads employed a mixed-methods methodology that includes a quantitative methodology utilizing a correlational research design and a qualitative research methodology. There were six quantitative research questions and two qualitative research questions utilized for the study. Key variables used in the study included data use, data use confidence, educational leadership efficacy, and student achievement.  Data use related to self-efficacy in terms of the types of data an educational leader utilizes (i.e., attendance, discipline records, test scores, school climate data, etc.), the amount of data they use in their capacity as a leader, and the supports in place within K-12 schools and districts to help them make data-driven decisions.   Data use confidence referred to the self-efficacy of educational leaders regarding utilizing various data practices in their capacity as leaders (i.e., accessing data, warehousing the data, conducting basic/advanced statistical analysis, applying data to making decisions, etc.).   Educational leadership efficacy was related to the self-efficacy of educational leaders in leadership skills (i.e., establishing a positive school environment, working with teachers on instruction and professional development, coping with the challenges of the job and facilitating learning, etc.).   Lastly, student achievement was the 2017-2018 ELA and mathematic CAASPP scores, which were derived from the schools and districts who participated in the study.  Each variable except the CAASPP scores was measured via surveys, which were sent out across California schools and districts using snowball convenience sampling. The surveys primarily asked participants to rate their self-efficacy regarding data use, leadership ability and confidence in various data practices. Ultimately, 111 educational leaders throughout California participated in this study, which produced the quantitative and qualitative data collected for data analysis. There were noteworthy findings from the quantitative and qualitative aspects of the study. First, the quantitative findings of the study related to how educational leaders believed they were highly efficacious regarding their data use, educational leadership, and data use confidence. Positive weak and moderate relationships were found between these variables. From these findings, it was noted that the majority of the participants had their lowest efficacy in conducting data analysis that included basic descriptive statistics and employing more complex statistical analysis like correlations/regressions. Second, the data that was most used by educational leaders were types of data that are currently being tracked on the California Department of Education Dashboard, as well as data relating to funding mechanisms and student formative and summative test scores. It must be noted, the data use, data use confidence, and educational leadership efficacy variables did not relate to the student achievement variable when correlations were calculated. Third, for the qualitative findings, participants noted educational leaders need to model data-driven cultures and data practices as well as how data is to be used in various contexts within the classroom and/or in school and district setting(s). In addition, participants felt there was a need for professional development to learn the skills necessary to become data literate. Fourth, qualitative findings also demonstrated that the lack of time for data analysis and resistance from teachers and staff to employing data throughout school sites and district was consistent in the findings.  Overall, conclusions derived from the findings of the study depict a scenario where educational leaders believe they are utilizing various types of data and have confidence in employing some data practices to make improvements and monitor goals. Another major conclusion produced from the study described how educational leaders need training in the form of professional development and/or within administrative and teacher credentialing programs in the following areas: how to access and warehouse data from student information systems, utilizing various data practices and how to apply them to classroom and school/district settings, articulating data findings to stakeholders, and integrating new technology and practices within a school culture. Lastly, the study concluded that schools and districts need to provide time in an organized manner for educational leaders and teachers to learn data practices, access and disaggregate data, and make decisions as a team for school and/or district improvement.

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