Competency 7

Use evidence to solve problems and discover opportunities.

Educational leaders must have the ability to:

• Plan for data collection and use.
• Understand the difference between normal variation and data trends.
• Analyze and interpret data.
• Examine data to find opportunities for the institution.
• Decide which data to use when planning and problem solving, and how to use it.
• Understand the context of evidence and data to inform, not determine, decisions.

Effective educational leaders must work with data within a context of continuous inquiry, goal-setting, and evaluation. Not all data is equally useful in informing thinking, planning, and teaching. Much depends on the immediate goal, the question being asked, or the decision to be made.

Data-informed strategies include framing appropriate questions and problems, establishing and evaluating measurable goals, becoming knowledgeable about assessment purposes and practices, and understanding a cycle of inquiry for the improvement of classroom instruction and student achievement. "Focusing on data throughout the school improvement cycle, rather than on intuition, tradition, or convenience, marks a great change in what educational leaders have used in the past to drive their decision making regarding student learning" (North Central Regional Educational Laboratory [NCREL], 2001).

Data only become useful when they are appropriate to a particular purpose. Bernhardt (2004) identifies four types of measures to consider when seeking data to answer questions: demographic data, perceptual data, student learning data, and school processes/programs data. 

Educational institutions routinely collect many types of data; deciding which data serve a particular purpose deserves careful consideration. Additional data involving one or more of these measures may need to be collected before certain questions can be answered. "More and better quality information can be found by digging deeper into the data through different levels of analysis in which one type of measure is analyzed and compared with other measures, over time," according to Bernhardt (p. 22). For example, two measures intersect in the question "is there a gender difference in students' perceptions of the learning environment? (Perceptions by Demographics)" (p. 25).

The Annenberg cycle of inquiry similarly addresses the need to identify goals, ask questions, examine and analyze existing data, plan action, evaluate impact of the action, and begin the cycle anew (Barnes, 2004). A cycle of inquiry for educational leaders works in a similar way. Schmoker (2003) writes, "Data can give educators the answer to two important questions: How many learners are succeeding?  What are the areas of strength or weakness? The answers to these two questions set the stage for targeted, collaborative efforts that can pay immediate dividends in achievement gains."

The Capella EdD in Educational Leadership and Management focuses on relevant research and is based upon the scholar-practitioner model. The Action Research focus is more fully explained in the Research tab of this Program Guide.

Subsets for the use of evidence and data to help solve problems and discover opportunities include the skills to:

• Evaluate the role of summative and formative data in relationship to goal attainment.
• Differentiate leadership behavior and organizational responses to trends in data versus episodic data blips.
• Consider the opportunities for divergent and unique growth pathways while utilizing data.
• Examine the processes leaders use when making key organizational decisions based on traditional data and other key systemic artifacts.
• Look for emerging patterns.
• Determine when not to use data.
• Keep data in context.

As stated in a recent monograph by Anthony Picciano (2004) from Hunter College, "The simplest definition of data-driven decision making is the use of data analysis to inform when determining courses of action involving policy and procedures. It is important to note that data analysis is used to inform and does not replace the experience, expertise, intuition, judgment, and acumen of competent educators. Inherent in this definition is the development of reliable and timely information resources to collect, sort, and analyze the data used in the decision making process."

References

Barnes, F. D. (2004). Inquiry and action: Making school improvement part of daily practice. Annenberg Institute for School Reform. Retrieved August 29, 2004, from http://www.annenberginstitute.org/tools/guide/ SIGuide_intro.pdf.

Bernhardt, V. L. (2004). Data analysis for continuous school improvement (2nd ed.). Larchmont, NY: Eye on Education.
North Central Regional Educational Laboratory. (2001). Using data to bring about positive results in school improvement efforts. Retrieved July 22, 2004, from http://www.ncrel.org/toolbelt/tutorial.pdf.

Picciano, A, (2004), www.hunter.cuny.edu/leadershipcenter/assets/data-driven-decisionmaking.pdf
Schmoker, M. (2003). First things first: Demystifying data analysis [Electronic version]. Educational leadership, 60(5). Retrieved April 14, 2004, from Academic Search Premier database.

The NEA Foundation for the Improvement of Education, 5. (2003). Using data about classroom practice and student work to improve professional development for educators. Retrieved September 11, 2004, from http://www.nfie.org/publications/usingdataIB.pdf.