Skip Navigation
REL Appalachia

[Return to Blogs]

Understanding Data Culture: What Data Do Education Leaders Use and How Do They Use Them?

September 28, 2018

SRI International
   Myles McMurchy, REL Appalachia
Education Development Center
   Camille Lemieux, REL Appalachia

Building a Culture of data use

At both the K–12 and postsecondary levels, leaders' capacity to use data for the intended purposes may vary depending on the presence of a culture of data use. A culture of data use results when an education organization commits to using data for continuous improvement at the school and classroom levels and embodies that commitment by emphasizing collaboration and empowering teachers and school leaders to make decisions for which they will be held accountable.i To promote a culture of data use, leaders must set expectations with school/university staff and personnel to encourage data use in multiple areas of the school system. Developing a clear communication plan may help collaborations and partnerships. Ensuring that the data collected can be accessed easily and analyzed efficiently is also helpful. Finally, the data that are collected should clearly align with systems-wide goals.

Stakeholders across the Appalachia region have reported that they suffer from DRIP syndrome: they are Data Rich and Information Poor, and they are motivated to change that reality. The Regional Educational Laboratory Appalachia (REL AP) Cross-State Partnership on Using Data and Evidence to Facilitate Action is working with education leaders in Kentucky, Tennessee, Virginia, and West Virginia to address DRIP syndrome by identifying opportunities to strengthen capacity among local data users to access, understand, and use state data to draw insights and facilitate action. To begin this work partnership members asked,
“What skills, structures, and supports do district and state leaders need to create a culture of data-driven decision making?”

To answer this question, REL AP staff first scanned existing literature and resources to:

  • Understand what data leaders use and how they use them.
  • Compile tools and guides to support use of data.
In this blog post we share what we learned from the literature scan, first describing the types of data commonly used at the K–12 and postsecondary levels and how education leaders have used these data and then providing resources for overcoming DRIP Syndrome in the education system. Education leaders in Kentucky, Tennessee, Virginia, and West Virginia will build on these lessons as they work with REL AP to conduct research around data use in their states.

K–12 data use

K–12 school administrators and teachers alike use data to inform decision-making at the school and classroom levels. School administrators use student outcomes data to meet accountability reporting requirements, inform school/district goals, and measure the effectiveness of outreach. Administrators rely primarily on student data from state assessment tests, although local assessment data use and district benchmark assessment data use are becoming more common. Administrators may also use discipline records, attendance records, and dropout and graduation data to better understand student performance.ii

Teachers also use student achievement data to improve curricula and instruction, inform student course placement, and provide differentiated student supports.iii Teachers also make instructional decisions based on teacher evaluation and teacher effectiveness data, as well as surveys of students, teachers, and parents. These data sources may also inform teachers' and school administrators' professional development opportunities.iv

Postsecondary data use

In the higher education sphere, college/university administrators and faculty develop assessment systems that measure students' progress toward learning objectives and use data from these assessments to inform teaching and learning. Similar to educators at the K–12 level, college/university administrators and faculty use formative and summative student assessment data to develop and revise program and unit curricula and improve student outcomes.v

Administrators rely on student achievement data, admission and acceptance data, and credential and degree completion data to inform education plans, meet accountability and accreditation requirements, and develop equity standards. Administrators also base policy decisions on data from curriculum documents, student surveys and evaluations, and course management systems.vi The literature also describes ways that secondary and postsecondary leaders can collaborate to share data that inform postsecondary transition policy and planning. vii

Tools and guides to support data use

Our review uncovered many tools, guides, and other resources from the U.S. Department of Education to support data use. These resources include frameworks for building a culture of data use, examples of ways state and district leaders have implemented data-driven decisionmaking strategies and disseminated information, and protocols to support district leaders in planning and implementing their own strategies.

REL resources

  • The Toolkit for a workshop on building a culture of data use helps school and district teams apply research to practice as they establish and support a culture of data use in their educational setting. The field-tested workshop toolkit guides teams through a set of structured activities to develop an understanding of data-use research in schools and to analyze examples from practice.
  • Research Review: Data-driven decision making in education agencies helps decisionmakers plan to use data to meet the needs of classroom teachers, school administrators, district-level leaders, and state education agency officials. This two-page infographic emphasizes the importance of using data that are relevant to decisionmakers and diagnostic for the issue at hand.
  • What four states are doing to support local data-driven decisionmaking: policies, practices, and programs documents how four state education agencies are supporting local data-driven decisionmaking through their policies, practices, and programs for creating data systems, improving data access and use, and building district and school capacity to use data. In addition to state policies, the study also identified five state programs supporting district and school data use.
  • How are teacher evaluation data used in five Arizona districts describes how educators in five Arizona school districts used results from new multiple-measure teacher evaluations in 2014/15, with each district administering its own local evaluation system developed to align with overarching state evaluation regulations passed in 2011. The findings of this REL West study suggest benefits from organizational structures that support the review of data during the school year, such as standards-based observation frameworks, benchmark assessments, professional learning communities, and instructional coaching and feedback.
  • A district's use of data and research to inform policy formation and implementation analyzes the Syracuse (New York) City School District's development and implementation of a new discipline policy, the Syracuse Code of Conduct, Character and Support. The descriptive study suggests components of a coherent strategy for using data and research to inform policy and practice that other districts might consider.
  • The Guide to using the Teacher Data Use Survey provides step-by-step instructions to help district and school planners conduct the Teacher Data Use Survey to query teachers, administrators, and instructional support staff about how teachers use data to support instruction, their attitudes toward data, and the supports that help teachers use data. This survey provides school or district leaders evidence on which to base decisions such as how to appropriate resources to support teacher data use and develop district policy around data use.
  • The materials from the REL AP cross-state partnership's June 2018 workshop Using Data and Evidence to Facilitate Action: Developing a Research and TCTS Agenda include more information on the cross-state partnership and the research questions we are addressing related to using education data for strategic planning and continuous improvement. The research agenda describes connections between the partnership's logic model, research questions, and research and coaching activities. More information from the literature scan described in this blog post, with additional citations related to these topics is available in the presentation and handouts.

What Works Clearinghouse resources

Footnotes:

iGerzon, N., and Guckenburg, S. (2015). Toolkit for a workshop on building a culture of data use (REL 2015–063). Washington, DC: U.S. Department of Education, Institute of Education Sciences, National Center for Education Evaluation and Regional Assistance, Regional Educational Laboratory Northeast & Islands. Retrieved from https://ies.ed.gov/ncee/edlabs/regions/northeast/pdf/REL_2015063.pdf.

iiDougherty, C. (2015) Use of Data to Support Teaching and Learning: A Case Study of Two School Districts. ACT Research Report Series. Retrieved from https://eric.ed.gov/?id=ED558033.

iiiSupovitz, Jonathan A. and Klein, Valerie. (2003). Mapping a Course for Improved Student Learning: How Innovative Schools Systematically Use Student Performance Data to Guide Improvement. CPRE Research Reports. Retrieved from https://repository.upenn.edu/cpre_researchreports/39.

ivMakkonen, R., Tejwani, J., & Venkateswaran, N. (2016). How are teacher evaluation data used in five Arizona districts? (REL 2016–142). Washington, DC: U.S. Department of Education,Institute of Education Sciences, National Center for Education Evaluation and Regional Assistance, Regional Educational Laboratory West. Retrieved from https://ies.ed.gov/ncee/edlabs/projects/project.asp?projectID=4525.

vBaker, G. R., Jankowski, N. A., Provezis, S., & Kinzie, J. (2012). Using assessment results: Promising practices of institutions that do it well. Urbana, IL: University of Illinois and Indiana University, National Institute for Learning Outcomes Assessment (NILOA). Retrieved from http://www.learningoutcomesassessment.org/documents/CrossCase_FINAL.pdf; Millett, C. M., Payne, D. G., Dwyer, C. A., Stickler, L. M., & Alexiou, J. J. (2008). A culture of evidence: An evidence-centered approach to accountability for student learning outcomes. Educational Testing Service. Retrieved from https://eric.ed.gov/?id=ED499994.

viCubarrubia, A., & Perry, P. (2016). Creating a thriving postsecondary education data ecosystem. Institute for Higher Education Policy. Retrieved from http://www.ihep.org/sites/default/files/uploads/postsecdata/docs/
resources/postsecondary_education_data_ecosystem.pdf
; Coughlin, M. A. (2014). Engaging evidence: how independent colleges and universities use data to improve student learning. Council of Independent Colleges. Retrieved from https://eric.ed.gov/?id=ED561079; Hora, M. T., Bouwma-Gearhart, J., & Park, H. J. (2017). Data driven decision-making in the era of accountability: Fostering faculty data cultures for learning. The Review of Higher Education, 40(3), 391-426; Dowd, A. C., & Liera, R. (2018). Sustaining change towards racial equity through cycles of inquiry. Education Policy Analysis Archives, 26(65), 1–46. Retrieved from https://eric.ed.gov/?id=EJ1182138.

viiGrady, M. (2016). How high schools and colleges can team up to use data and increase student success. Ready or Not: It's Time to Rethink the 12th Grade Series. Jobs For the Future. Retrieved from https://eric.ed.gov/?id=ED567871.