Data systems, in general, support data collection and analysis. Often in education, data systems refer to the technical aspects of how data is organized and stored. In contrast, this strategy focuses on a Decision Support Data System (NIRN, 2016), which is a system that supports identifying, collecting, and analyzing data in order to support continuous improvement. This mirrors a 2010 recommendation from the U.S. Department of Education: “Think of data-driven decision making as an ongoing systematic process rather than a one-time event centered on the acquisition of a data system” (USDOE, 2010, page xix). For the purposes of the portal, all references to "data system" are inclusive of a Decision Support Data System.
Historically, data use in education refers to the processes by which educators examine assessment data to identify student strengths and deficiencies and apply those findings to their practice. An important aspect of this strategy is the use of multiple measures for continuous improvement, including the use of fidelity and programmatic data in addition to student outcome data. Both fidelity and programmatic data help us understand whether we implemented what we determined would improve student outcomes. When the goal is to increase student learning in a standards-based education system, using data to make decisions about how to support changes in instruction and curriculum is paramount. “The moral of the story is, if we want to get different results, we have to change the processes that create the results. Just looking at student achievement measures focuses teachers only on the results, it does not give them information about what they need to do to get different results.” (Bernhardt, 1998.)
When a Decision Support Data System is running well, teams can use data to make decisions about effective instructional practices and the supports needed for educators to implement them successfully.
Ingram et al (2004) uncovered seven barriers to the use of data to improve practice. They include:
Developing, maintaining, or refining a data system is important to fully implementing a standards-based education system.
Data help organizations:
Data help individual educators and teams of educators:
Data help students and families:
(adapted from https://dataqualitycampaign.org/why-education-data/)
Policies and Plans: for support in communicating about data with stakeholders and involving stakeholders in decision-making.
Bernhardt, V. L., (1998, March). Invited Monograph No. 4. California Association for Supervision and Curriculum Development (CASCD). https://nces.ed.gov/pubs2007/curriculum/pdf/multiple_measures.pdf, last retrieved August 13, 2019.
Ingram, D., Seashore Louis, K. and Schroeder, R. G. (2004). “Accountability Policies and Teacher Decision Making: Barriers to the Use of Data to Improve Practice,” Teachers College Record, Vol. 106, No. 6, pp. 1258–1287.
National Implementation Research Network (NIRN), AI Hub website, “Handout 28: Drivers Ed - Decision Support Data Systems,” (2016.) https://nirn.fpg.unc.edu/resources/handout-28-dsds, last retrieved August 13, 2019.
U.S. Department of Education, Office of Planning, Evaluation, and Policy Development, Use of Education Data at the Local Level From Accountability to Instructional Improvement, Washington, D.C., 2010. https://files.eric.ed.gov/fulltext/ED511656.pdf, last retrieved August 13, 2019.