Data-Based Decision Making – TTAC Link Lines

Data is a term frequently used in education. The terms data-based decision making and data-driven decision making are also often used. But what is data and what decisions are driven by this data? Merriam-Webster (2015) defines data as “facts or information used usually to calculate, analyze, or plan something”. The key to using data wisely is to identify the “something” that will be analyzed or planned before actually starting to gather the data.

Schools make many decisions that require analysis of high-quality, rich data. Such decisions inform strategic planning, school zoning, resource allocation, teacher assignment, and instructional practices. According to Earl and Katz (2006),

Getting the right data depends on asking the right questions. The value associated with data comes from skill in discerning the quality of the data, organizing it, thinking about what it might mean, and using it wisely to make decisions. (p. 27)

Data might include student demographics, school culture, environmental factors, student achievement, parents’ views, teacher knowledge and experience, and available resources. School teams must identify the indicators that provide the most valuable information to direct their planning efforts. Current, relevant data becomes meaningful when teams spend time analyzing and interpreting the data while keeping a focus on three critical questions:

“What do these data seem to tell us about our priority?
What do they not tell us?
What else would we need to know?” (Earl & Katz, 2006, p. 63).

Data at either the division or the school level is not always easily accessible to educators who need it most (Earl & Katz, 2006). Although much of the school data (e.g., standardized test data, attendance and discipline records, student demographics) is available electronically, other high-quality, meaningful, and informal data sources are not stored in this manner, including observations, testimonies, classroom records, and work samples – documents that may provide evidence needed by educators to make informed decisions with regard to the questions they are attempting to answer.

When answering questions related to student learning, standardized data may only provide a small piece of the larger picture (Tomlinson, 2015). Thus, such data does not provide information related to student engagement, thinking processes, depth of understanding, and incremental progress. Daily and weekly observation and assessment data informs teachers about students’ knowledge, understanding, and progress towards learning goals so that timely instructional adjustments and shifts can be made when necessary. It is important to focus and build upon student strengths in order to appropriately address the identified needs (Datnow & Park, 2015). The goal is to “find out daily where each student is in the learning trajectory we had in mind – and … use that information to focus our teaching so that each student moves ahead” (Tomlinson, 2015, p. 88).

Using data to inform decision making takes time and organization. Teams may work together to consider the critical issues, the questions that must be answered and the relevant data; to analyze these data; and to transform data into “knowledge that they can use” (Earl & Katz, 2006, p. 28). Although data is often discussed and used in education, not all educators have the necessary knowledge and experience to make the transformation of raw data into usable evidence. Such educators need to develop the data literacy that allows for systematic processing of data to inform critical educational decisions. Data provides the lens through which to view issues rather than the answer to the pressing questions. “And the best ideas come when people work together to share their ideas and try to make sense of the complexity” (Earl & Katz, 2006, p. 64).

There is no doubt that data analysis is a critical component in educators’ decision making regardless of the decisions to be made. It is important to note, however, that data does not drive educators. Educators take the driver’s seat in effectively and strategically using data to influence and inform the important decisions they make.

In this issue of Link Lines, Collaborative Leadership: The Forgotten Art of Formative Assessment by Christopher R. Gareis, Ed.D., provides information related to formative assessment practices in the classroom and their relationship to instruction, providing constructive feedback, and student engagement.

Donni Davis-Perry discusses how to make data meaningful to students and families in her article, Data and Learning Connections for Families and Students.

The article Strategic and Specially Designed Instruction: Leveraging Data Sources to Ensure General Curriculum Access by Cathy Buryn includes information about how IEP teams link data about specific student performance to standards, to plan for specially designed instruction that prioritizes relevant content knowledge, skills, and processes.

Master scheduling requires the use of multiple sources of data and is a critical component of supporting inclusive practices for students with disabilities. Read more in Lee Anne Sulzberger’s article, Master Scheduling for Student Success.

References

Datnow, A., & Park, V. (2015, November). 5 (Good) ways to talk about data. Educational Leadership, 73(3), 10-15.

Earl, L. M., & Katz, S. (2006). Leading schools in a data-rich world: Harnessing data for school improvement. Thousand Oaks, CA: Corwin Press.

Merriam-Webster (2015). Dictionary. Retrieved from http://www.merriam-webster.com/dictionary/data

Tomlinson, C. A. (2015, November). Different data, different roles. Are we motivating students with data? Educational Leadership, 73(3), 87-88.