Data-Driven Decision Making

1. Data-Driven Decision Making Presented by The Leadership and Learning Center (800) 844-6599 www.LeadandLearn.com

2. Part One: Objectives • Develop a deeper understanding of the Decision Making for Results: Data-Driven Decision Making process • Increase awareness of the relevance of data and its impact on leadership, teaching, and learning • Reinforce the importance of collecting both cause and effect data

3. Why are We Here? • To offer a process/framework for using data as it relates to School Improvement Planning and • To make informed data-driven decisions that lead to improved classroom practices

4. CONSENSOGRAM Activity Directions: • Respond to each of the consensogam questions individually using a scale of 0-100. • Place your response on a post-it note, one per question. • Place your post-its on the prepared charts in the form of a bar graph.

5. Essential Questions • How is your school or district doing as a learning institution? • Are all students learning? • In what ways do your community, district office administrators, principals, and classroom teachers collect and use data to make decisions?

6. What do you expect students to know and be able to do by the end of each year? Do you know why you are getting the results you currently have? What is the best way to assess student knowledge and application of skills? Essential Questions

7. Seminar Overview • Introduction • Building the Foundation • Process and Application • Action Planning

8. Becoming Data-Driven How are you currently embracing a data-driven decision-making process that leads to results?

9. Results-Driven Schools • Where’s the Proof? • 90/90/90 Schools, Reeves 2003 • Education Trust, 2002 • NCREL, 2000 • Consortium for Policy Research in Education, 2000 • EdSource, 2005 • Northern Illinois University Center for Governmental Studies, 2004 Data Driven Decisions

10. Reflection “The value of the data emerges only when analysis provides insights that direct decisions for students.” White, S. (2005). Beyond the numbers. Englewood, CO: Advanced Learning Press.

11. Part Two: Building the Foundation • Cause data and effect data • Continuous improvement cycle • Principles and processes of Decision Making for Results: Data-Driven Decision Making

12. “Only by evaluating both causesand effects in a comprehensive accountability system can leaders, teachers, and policymakers understand the complexities of student achievement and the efficacy of teaching and leadership practices.” Reeves, D. B. (2006). The learning leader. Alexandria, VA: ASCD.

13. Effect data: outcomes or results Cause data: professional practices that create specific effects or results Definitions and Examples

14. The Leadership/Learning Matrix (L2 Matrix) Effects/Results Data Leadership/Teaching Practices

15. Part Three:Process and Application

16. Ocean View Elementary School – a look at collaboration

17. The Process for Results Treasure Hunt Analyze to Prioritize Inquiry;: Develop Questions Monitor & Evaluate Results SMART Goals Results Indicators Specific Strategies

18. Inquiry “Data-driven decision making begins by asking fundamental questions.” D. Reeves • What questions do you have about leadership, teaching, and learning in your school or district? • What data sources are you using to gather the specific information?

19. Step 1: Conduct a Treasure Hunt • Why? – To gather and organize data in order to gain insights about leadership, teaching, and learning practices Considerations: • Measures of data • Disaggregation • Triangulation • Reflection

20. Measures of Data • Student learning • Demographics • Perceptions • School processes – behaviors within our control: instructional and leadership strategies, programs and resources, and organization

21. Disaggregation • To separate something into its component parts, or break apart • “Disaggregation is not a problem-solving strategy. It is a problem-finding strategy.” Victoria Bernhardt, Data Analysis, 1998 Think, pair, share: What data do you disaggregate and how do you use the information?

22. Triangulation – A Look at Learning

23. Case Study • Read case study • Part 1: How did they categorize the different data sets and record their observations? • Part 2: What did they discover?

24. Conduct a Treasure Hunt Application • Review inquiry questions • Conduct a “Treasure Hunt” • Organize data on templates • Use rubric to monitor and evaluate your work

25. Find the Data • Search for multiple measures of data: student achievement, perception, processes, demographics • Organize the data to include content areas, subskills, student population, gender, grades, and year of achievement • Disaggregate data where needed • Enter group information when examining longitudinal trends and patterns.

26. Can you identify with this? “It is not so much a lack of data, but an absence of analysis, and an even greater absence of actions driven by the data.” White, S. (2005). Beyond the numbers. Englewood, CO: Advanced Learning Press.

27. Step 2: Analyze Data to Prioritize Needs Data Analysis at Northside Middle School

29. Step 2: Analyze Data to Prioritize Needs • Why? – To identify causes for celebration and to identify areas of concern • Considerations • Strengths • Needs • Behavior • Rationale

30. “Stoplight” Highlighting Illuminating data patterns • Blue = Wow! Beyond Expectations • Green = Good – Meets Expectations • Yellow = Caution – Below Expectations • Pink = Urgent! In need of immediate improvement!

31. Define Your (Cutoff) Colors • Assign colors to your levels of expectations. What percent of students DO YOU WANT TO SEE at each levels? Is 80% of your students at proficient and above adequate in light of SRBI? • Make acolor keynext to your Data Table

32. Stoplight Highlighting(Sample Cutoffs) • Blue 80 – 100% • Green 60 – 79% • Yellow 40 – 59% • Pink 0 – 39%

33. Quality Prioritization • Why? To take immediate action on the most urgent needs • Quality prioritization requires a thorough understanding of: • Student population • Curriculum and Power/Priority Standards (leverage, readiness) • Antecedents affecting student achievement • Quality of program implementation White, S. (2005). Beyond the numbers. Englewood, CO: Advanced Learning Press.

34. Case Study • Review case study • What insights did you gain after reading analysis of student performance? • Make a recommendation: What is the most urgent need?

35. Review, Analyze, and Prioritize Application • Review data from Step 1 • Conduct analysis using the guiding questions • Prioritize urgent needs using the suggested criteria and your highlighting • Record your work on the templates

36. Step 3: Establish SMART Goals • Why? – To identify our most critical goals for student achievement based on the challenges that were identified through the inquiry process • Specific, measurable, achievable, relevant, timely

37. Goals - Application • Review prioritized needs • Review Treasure Hunt baseline data • Apply SMART goal formula, use templates to record your work • Use rubric to monitor and evaluate your work

38. Step 4: Select SpecificStrategies Let’s watch Lake Taylor High School as they dialogue about strategies.

40. Step 4: Select Specific Strategies • Why? • Adult actions will impact student achievement • Strategies are: • Action-oriented • Measurable/accountable • Specific • Research-based • Considerations: instructional, organizational, leadership, programmatic

41. Research-Based Strategies • 90/90/90 Schools, Reeves 2003 • Ten Things High Schools Can Do Right Now to Improve Student Achievement, Reeves, 2006 • What’s Happening in Schools? or Not, Learning 24/7 Observation Study, 2005

42. Additional Evidence in Support of Research-Based Strategies • Best Practice, Zemelman-Daniels, Hyde, 1998 • Art & Science, Marzano 2007 • The Kids Left Behind, Barr & Parrett, 2003 • School Leadership That Works, Marzano, Waters, McNulty, 2005

43. Let’s Do It! Guided Practice

44. Select Your Specific Strategies • Revisit your prioritized needs. • Research the best possible strategies to meet the learner needs • Group by type of strategy: instructional, organizational, programmatic, and leadership • Use rubric to monitor and evaluate your work

45. Step 5: Determine Results Indicators • Why? To monitor the degree of implementation and evaluate the effectiveness of the strategies

46. Results Indicators • Considerations • Serve as an interim measurement • Used to determine effective implementation of a strategy • Used to determine if strategy is having the desired impact • Help to determine midcourse corrections

47. Results Indicator Application • Revisit strategies (Step 4) • Develop results indicators • Use rubric to monitor and evaluate your work

48. “Improvement cycles require leadership follow-up and relentless efforts to maintain the focus on data if decisions are truly going to be driven by informed data.” White, S. (2005). Beyond the numbers. Englewood, CO: Advanced Learning Press.

49. Step 6: Monitor and Evaluate Results Why? To engage in a continuous improvement cycle that • Identifies midcourse corrections where needed • Adjusts strategies to assure fidelity of implementation

50. Develop Your Monitoring Plan • Review your work from developing questions to determining results indicators then determine how you will monitor the strategies. When you create your monitoring plan consider: • Teacher or administrator teams • Monitoring cycles • Goals • Strategies • Impact on student and adult behavior • Ability to make midcourse corrections