Data Coaching Services Data Analysis Model and Process

1. Orient Campuses to Data • Assist in Data Analysis • Provide Feedback System Data Coaching ServicesData Analysis Model and Process February 2012

2. Challenge “…take the abundance of school data generated each year and turn it into information that can lead to improvements in educational practice.” --Jeffrey C. Wayman, The University of Texas

3. Charge • Develop a systemic model and process to analyze data for student achievement • Align the model and process with Dallas ISD instructional initiatives

4. Research The understanding, use, and implementation of data analysis tools and practices are key components to improving student achievement. Best Practices and Research for Data Analysis Tools

5. Research Best practices from various sources have been studied for the development of the Data Coaching Services Data Analysis Model and Process. Best Practices and Research for Data Analysis Tools

6. Data Analysis Model and Process

7. The Data Analysis Model Layers

8. The Data Analysis Model Layers

9. Student Achievement Student Achievement(Inner Circle) The Data Analysis Process provides campus leaders and teachers tools to analyze data and develop action plans to monitor and improve student achievement.

10. District Initiatives District Initiatives(Center Ring) The Data Analysis Process is integrated with district initiatives, such as Response to Intervention (RtI), the Principles of Learning (POLs), and the Curriculum, Instruction, Assessment, and Accountability model (CIA2).

11. Embedded Data Practices Embedded Data Practices (Middle Ring) Data-driven dialogue and instructionally relevant questions should be embedded as an ongoing practice when considering data analysis.

12. Process Steps Process Steps (Outer Ring) The outer ring outlines the steps of the Data Analysis Process. These seven steps create a process to analyze data for student achievement.

13. The Data Analysis Process

14. The Data Analysis Tool Each step of the Data Analysis Tool has a corresponding section on the Data Analysis Model

15. Frame the Question The first step in the process is to determine what information and questions need to be answered. This step provides direction and focus to the process.

16. Organize for Dialogue The second step involves organizing the group which will analyze the data.

17. Collect the Data Select the source or sources which will provide the data needed to answer the question(s). Multiple data pieces should be gathered to create a complete representation of the data and information required.

18. Analyze the Data This step involves evaluating data using analytical and logical reasoning to examine each component of the data. This will be done by aggregating/disaggregating data and identifying strengths, weaknesses, and anomalies.

19. Interpret the Data At this step, discussion and investigation will take place to identify patterns, trends, and tentative conclusions and explanations.

20. Select Actions This step will address appropriate data-driven actions and measurable relevant goals.

21. Monitor Results This step will identify the process and responsible staff for monitoring progress towards relevant goals.

22. Data is like . . . A jigsaw puzzle. The separate pieces may show interesting detail, but together you can see the whole picture. It represents going from the unknown to the known. The School Portfolio Toolkit, Victoria L. Bernhardt, 2002

23. Contact Us Data Coaching Services www.dallasisd.org/datacoaching Faustina Gallagher, Directorfgallagher@dallasisd.org Entaune Tyson, Manageretyson@dallasisd.org Debbie Floyd, Data Coach dfloyd@dallasisd.org Danielle Hernandez, Data Coach dahernandez@dallasisd.org Janie Reyes, Data Coach jreyes2@dallasisd.org 2500 South Ervay St.Dallas, TX 75215(972) 749-2480