1. DATA INQUIRY TO IMPROVE TEACHING AND LEARNING DAY 1: GETTING STARTED WITH DATA Putnam/Northern Westchester BOCES Race to the Top Series December 8, 2011

2. Presenters Judy Powers Education Program Consultant Abby Bergman Education Program Consultant 2

3. Agenda Introductions 8:30 – 8:40 Warm-Up: Synectics Activity 8:40 – 9:00 Why Are We Here? 9:00 – 9:10 Collaborative Inquiry 9:10 – 9:30 Organizing for School Based Inquiry 9:30 – 10:15 Break/Networking 10:15 – 10:30 Models of Inquiry Cycles 10:30 – 11:30 Building a Data Inventory 11:30 – 12:00 Lunch 12:00 – 12:45 A First Look at Data 12:45 – 1:15 Working With Your District’s Scope of Work 1:15 – 2:45 Next Steps and Wrap Up 2:45 - 3:00 3

4. GOALS FOR THE DAY PARTICIPANTS WILL KNOW What is meant by data-driven instruction What is meant by collaborative inquiry How to organize for data inquiry within a school What is the function of school based inquiry teams and what they do PARTICIPANTS WILL UNDERSTAND THAT Developing data inquiry teams requires a shift in how we think about dealing with student data Structures must be put into place to promote and support data inquiry teams and data-driven instruction Looking at data for school improvement is a complex process that takes time PARTICIPANTS WILL Examine structures that can be used for school-based inquiry Review data and develop a plan for achieving Scope of Work priorities 4

5. Synectics Activity Directions: Brainstorm several ways that the image on your postcard is like using data to guide school improvement. In your teams, select your favorite comparison. Choose a spokesperson. Share your image and your comparison. 5

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7. Why Are We Here? As part of the Race-to-the-Top Initiative, each building in a school district is required to form an inquiry team -- a group of teachers and building administrators charged with analyzing data, identifying student achievement gaps, and formulating steps to close those gaps. If this were not a requirement, this structure provides an opportunity to use the data we have to improve instruction and achievement. Look at District Scope of Work. Where to find it? http://usny.nysed.gov/rttt/scopeofwork/ 7

8. Aug. – Oct. 2011 1. Defining Data Driven Instruction and School Based Inquiry so that efforts can be focused on high leverage strategies 2. Collaboratively & accurately diagnose school capacity for implementing the Inquiry/ DDI model based on the DDI key drivers 3. Build and/or identify high quality assessment tools to use in the classroom 4. Develop an implementation plan for data driven instruction that is tailored to the specific needs of schools and/or districts 5. Diagnose the quality of each school’s implementation of data driven instruction against the key drivers 6. Support the ongoing development of data driven cultures in teams of teachers and school leadership teams ensure success Oct. – May 2012 1. Linking Instruction and follow- up with analysis and action planning 2. Align instructional practices, assessments, and analysis to the rigor of the Common Core standards 3. Support and/ or lead effective analysis meetings with teachers that increase student learning 4. Monitor Progress on Action Plans and determine mid- course corrections in each school NYSED Recommendations for School-Level Network Inquiry/DDI 8

9. In our Race to the Top work we often use the terms “Data Inquiry Teams” and “Data Driven Instruction.” 1. What is the difference? 2. How do they relate to one another? Think Pair Share Data Inquiry Teams and Data Driven Instruction 9

10. Clarification of Terminology Data-Driven Decision Making: Using data to inform practice to achieve desired outcomes. Data-Driven Instruction: Using data to inform and improve instruction by shifting the focus from “what was taught” to “what was learned.” Data Inquiry Team: A group of individuals who come together to analyze data, identify student achievement gaps, and formulate steps to close those gaps. Collaborative Inquiry: A process by which all relevant groups construct an understanding of student learning problems and test out solutions together through the use of data and reflective dialogue. 10

11. AreaAway from...Toward... School Culture School culture characterized by isolation, mistrust, external accountability, acceptance of achieve gaps Collaborative culture characterized by teaming, trust, internal responsibility, a commitment to equity Collaborative Inquiry Top-down and premature data-driven decision making Ongoing data-driven dialogue and collaborative inquiry Data Used to reward or punishData as feedback for continuous improvement Student Learning Opportunities to learn for some Opportunities to learn for all – no exceptions Leadership Hierarchical leadershipDistributed leadership Professional Development Professional development as an event Professional development as ongoing, teacher-to-teacher conversations about teaching and learning CORE VALUE SHIFTS FOR COLLABORATIVE INQUIRY 11

12. Seven Norms of Collaboration 1.Pausing 2. Paraphrasing 3. Probing for specificity 4. Putting ideas on the table and pulling them off 5. Paying attention to self and others 6. Presuming positive intentions 7. Pursuing a balance between advocacy and inquiry 12

13. Creating A Data Inquiry Team Who should be on the team? Is it better to tap a few individuals to become “data experts” and fulfill reporting requirements, or to build a culture in which the whole school participates in analyzing data and figuring out the implications for improving instruction? What are the benefits of choosing the more challenging route? (This does not imply that specific individuals within a team should not assume specific roles, e.g. technical assistance, organizational details.) A team may consist of teachers who face common challenges in student achievement (e.g., poor performance in 3 rd grade math or a larger issue). Everyone should be on a team. Existing structures within the school should be used. Each team should talk about data. 13

14. Possible Structure and Variety of School Teams Instructional Leadership Team Grade-Level Teams Principal/ Administrative Team School and Community Team 14

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16. Team Talk What kind of structures already exist in your school/district that you use to examine school data or might be used to examine school data? (10 minutes) Be prepared to share your conversation with the whole group. 16

17. What Do Data Teams Do? School-based inquiry teams Improve outcomes for a specific group of students for whom the school has not previously been successful, and learns from this experience to make a system-level change so that the school as a system continues to improve Analyze data for target groups of students that share common learning challenges (e.g., fifth grade ELL boys in math), investigate the root causes and skill gaps, use research-based instructional strategies to address the weaknesses at the skill level, and continually evaluate the strategies being used 17

18. How Do Data Teams Achieve Their Goals? Collect and analyze a variety of types of school data Support the development of common assessment instruments Consult research to investigate problems, causes, and best practice Use norms of collaboration Develop data-supported action plans Communicate with staff and key stakeholders about findings and plans Oversee the implementation of plans and/or implementing instructional improvement Engage a broader group of stakeholders to gain their input, involvement, and commitment Coordinate with other school or district initiatives and leaders Develop data literacy Develop content and pedagogical knowledge Exercise leadership and facilitation skills 18

19. INQUIRY CYCLE MODELS 1. Bambrick-Santoyo (Driven by Data: A Practical Guide to Improve Instruction. Jossey-Bass, 2010) 2. The DataWise Project (DataWise: A Step-by-Step Guide to Using Assessment Results to Improve Teaching and Learning. Harvard Education Press, 2010) 3. Nancy Love (Using Data to Improve Learning for All. Corwin Press, 2009) 19

20. AssessmentAssessmentAnalysisAnalysisActionAction Data Driven Culture Bambrick-Santoyo’s Data-Driven Instruction Model 20

21. Bambrick-Santoyo’s Four Key Principles Culture Create an environment in which data-driven instruction can survive and thrive. Build awareness of group competence. Assessment Develop assessment literacy. Create rigorous interim assessments that provide meaningful data. Common core alignment. Analysis Examine the results of assessments to identify the causes of both strengths and shortcomings. Formulate problem statements. Set goals. Action Teach effectively what students most need to learn. Apply research-based strategies. Reflect on outcomes for students. 21

22. Data Driven Culture Highly Active Leadership Team Introductory Professional Development Implementation Calendar Ongoing Professional Development Build by Borrowing 22

23. Assessment Common Interim Assessments Transparent Starting Point Aligned to State Tests and College Readiness Aligned to Instructional Sequence Re-assess prior learning 23

24. Analysis Immediate Turnaround Data Reports Teacher-Owned Analysis Test-In-Hand Analysis Deep Analysis 24

25. Action Planning Implementation Ongoing Assessment Accountability Engaged Students 25

26. The DataWise Improvement Process From: Data Wise. Harvard Education Press (Boudett, City, and Murname, ed) Cambridge, MA. 2010 26

27. Nancy Love’s Using Data Process A Data Coach’s Guide to Improving Learning for All Students: Unleashing the Power of Collaborative Inquiry. Corwin Press, 2008. 27

28. DESIGN YOUR OWN MODEL Now that you have seen three different models of an inquiry cycle, work in your district teams and create (in the space below) a model that would work well in your school/district. 28

29. Building a Data Inventory You Know More Than You Think You Know! At your table groups, discuss the following questions: 1.How have you used data to improve instruction in your school? 2.Define a student learning problem and discuss the various forms of data that you might use to address the problem. (Remember you can use qualitative and quantitative data.) 3.How would you obtain the data that you need to solve this problem? 4.How might you begin to build a date inventory for your school inquiry team? 29

30. A First Look at Data 30

31. A First Look at Data 1. What do you notice about this data? 2. What questions do you have about the data? 3. What would you want to explore further? 31

32. Looking At Your District’s Scope of Work Find your district’s Scope of Work at: 1.What are the Annual Performance Targets for 2011-2012? 2. Find the Student Outcome Metrics: Priorities for Improvement Outlined in the Plan 3. How would you begin to address “priorities for improvement” outlined in the plan? 4. Which group should be involved in determining the means used for achieving the goal? 5. Is there a work plan? If not, what would you need to develop one? 6. How will progress toward the goals be monitored and shared? http://usny.nysed.gov/rttt/scopeofwork/ 32