Data Informed Decision Making

1. Data Informed Decision Making Evelyn Wassel, Ed.D. wasse@iu29.org October 4, 2011

2. Purpose • To understand the purpose of using data to make instructional decisions • To increase knowledge in disaggregating data to lead the staff in making informed instructional decisions • To spark ideas to develop a vision for data usage, a plan for implementation, and a course for sustainability • To develop ways to overcome obstacles that can impede vision realization

3. Consistent Factors in High Performing Schools • Teachers’ continuous reflection on student learning data to determine instructions, practices and objectives • National Center for Educational Accountability • Data based practices of setting challenging goals and provision of effective feedback • Marzano, 2003

4. What is the Purpose of School? • What do you expect the students to know and be able to do by the time they leave school? (Standards) • What do you expect students to know and be able to do by the end of the quarter or semester? (Benchmarks) • How well will the student be able to do what they want to do with the knowledge and skills they acquire by the time they leave school? (Performance)

5. What is the Purpose of School? • Why are you getting the results you are getting? Why are you not getting the results you want? (School processes) • What would your school and educational processes look like if your school were achieving its purpose, goals and expectations for student learning? (Vision) • How will you use the data you gather? (Implementation)

6. Addressing Key Issues in Schools • Complete the “Getting Started Questions” sheet with your school team. If you don’t have a team you can answer here and download a copy for use at your school.

7. What are the uses of data? • A way to assess what students are learning and the extent to which students are making progress toward goals • A means to understand what instructional changes are needed to improve student achievement. • REL 2009

8. We must help educators move from using data only for accountability to using data for continuous improvement. High stakes testing On-going planning & intervention

9. All About Data • Data tells is the symptoms: the problem is less obvious • To be most useful, data must be transformed into information via • Disaggregated analysis and interpretation • Multiyear trends • Multiple sources – formative, summative, perceptual • Root cause analysis • Informed discourse among stakeholders. • Performance Fact

10. Schools Use Data… http://www.learningpt.org/images/dataWorkshop.gif

11. What types of data are used? • Formative, Summative, Perceptual • Complete the chart on the blue paper with your team.

12. What types of data are used? Checkup Autopsy http://www6.cityu.edu.hk/obtl/images/tg_qstart_form_and_sum_table.jpg

13. Perceptual Data… http://www.flickr.com/photos/ironrodart/4537364063/meta/

14. Three Types of Data Worth Considering • Formative – early indicators • Ex. Curriculum-based assessments, benchmark assessments, class grades • Summative – end of the line indicators • Ex. Final exams, state accountability tests, SAT, AP tests • Perceptual – voice or opinion indicators • Ex. Surveys, focus groups

15. Typically, School Data Are Analyzed to: • Improve instruction • Gain instructional coherence • Provide students with feedback on their performance • Gain common understanding of what quality performance is and how close we are to achieving it. • Bernhardt, 2004

16. Typically, School Data Are Analyzed to: • Measure program success and effectiveness • Understand if what we are doing is making a difference • Make sure students do not “fall through the cracks” • Show which programs are getting the results we want • Get to the “root cause” of problems • Bernhardt, 2004

17. How Can We Most Effectively Use the Data to Make Instructional Decisions? • Make data part of an ongoing cycle of instructional improvement • Teach students to examine their own data and set learning goals • Establish a clear vision for schoolwide data use • Provide supports that foster a data-driven culture within the school • REL 2009

18. Make Data Part of an Ongoing Cycle of Instructional Improvement http://newmiddle-earth.blogspot.com/2008/10/reflective-practice-blogging-and.html

19. Making It Part of the Routine • Collect and prepare a variety of data about student learning. • Interpret data and develop hypotheses about how to improve student learning. • Modify instruction to test hypotheses and increase student learning. • Allow time for teachers to analyze the data and participate in professional discourse.

20. Teach Students to Examine Their Own Data and Set Learning Goals • Can motivate all levels by • Letting them choose accomplishments that are attainable • Showing achievement gains • Providing a choice for success

21. How to Empower Students • Explain expectations and assessment criteria. • Provide feedback to students that is timely, specific, well formatted and constructive. • Provide tools that help students learn from feedback. • Use students’ data analyses to guide instructional changes.

22. Establish a Clear Vision for Schoolwide Data Use • Develop a culture of data • Collaboration is key

23. How Do I Realize This Vision? • Establish a schoolwide data team that sets the tone for ongoing data use. • Define critical teaching and learning concepts. • Develop a written plan that articulates activities, roles and responsibilities. • Provide ongoing data leadership.

24. Provide Supports That Foster a Data-driven Culture Within a School • Ensure everyone knows their role and has the tools for success. • Invest for the greatest returns!

25. What Supports Are Needed? • Designate a school-based facilitator who meets with teacher teams to discuss data. • Dedicate structured time for staff collaboration. • Provide targeted professional development regularly.

26. Remember, school personnel may or may not… • Have had course work in statistics • Have a comfort level working with data or numbers • Understand the idea of scientific inquiry • See learning as a quantifiable behavior

27. http://optimizationtoday.com/wp-content/uploads/2011/09/data-analysis-cartoon-1.gifhttp://optimizationtoday.com/wp-content/uploads/2011/09/data-analysis-cartoon-1.gif

28. Using the Data You Have • Typically, student achievement data are reported for whole populations, or as aggregate data. • It is not, however, until the data are disaggregated that patterns, trends and other important information are uncovered. • Disaggregated data simply means looking at test scores by specific subgroups of students.

29. Ways to Disaggregate Data • Gender • Socio-economic status • Mobility (students moving in and out of the districts at any given time) • Race and ethnicity • Special education and disability • English as a Second Language (ESL) • Enrollment patterns in courses like physics or algebra • Successful completion of specific course such as advanced placement

30. Questions to Answer • Is there an achievement gap in reading, math or science among different groups of students? Is the gap growing larger, smaller or staying the same? • Are male students performing better than female students in math? Why and how will we increase the performance of female students? • Are there more poor or minority students in special education classes than there are in advanced placement classes? What are the reasons behind the difference and what will we do about it?

31. Using the Data • Is student mobility, professional development for teachers, or parental involvement is affecting student performance? • Look at the data by • classrooms in a school • grade levels within a school or district • schools within a district, or • the amount of training a teacher has received. • Look for larger trends and patterns.

32. Are you a confident data user? • Place a dot on the poster in the quadrant the best describes your feelings about data usage. • Eric Carmen – “I don’t have a clue” • John Lennon – “I dabble in data but don’t really know if it is effective.” • BTO – “ I can use data and know it makes a difference.” • Jerry Lee Lewis – “I can train others”

33. Creating Confident Data Users • Just like when we teach new skills to students, we may need to be more explicit than implicit in our structure as we seek to create new habits of behavior. How do we scaffold our system to provide the needed support to those just learning these new behaviors?

34. How do we create confident data users? • Common language • Access to information • Collaborative communication skills • Process tools • Habits of reflection • Wellman, B & Lipton, L. (2004)

35. Moving from Data to Solutions • Through analysis of data teachers can identify areas of strength and concern. • Teachers should hypothesize why these patterns exist by looking for the root cause of the concern. • Teachers can then develop an action plan to address the needs identified by the root cause analysis.

36. Summary • A data informed school: • Uses information at multiple levels and in multiple ways • Provides structure and format for teachers to reflect on student performance and instruction • Keeps its goals front and center at all times • Recognizes that its greatest strengths are the experiences and skills of its teachers and builds on this knowledge to increase student performance.

37. What About the Resisters??? • Everybody is at least a little resistant to change. • They wonder how it will affect them daily and in the long-term. • There are ways to overcome resistance!!

38. What About the Resisters??? • Complete the blue sheet with your team. • Don’t be afraid to think out of the box!!!

39. What About the Resisters??? • Write your group’s ideas for solutions when you encounter resistance on post-its (one per idea). • Place the post-its in the appropriate space on one of the charts hanging around the room. • Take a walk around and see what other ideas people have posted. • Remember…in education we call that collaboration, not stealing

40. All handouts are available… • http://wassel.wikispaces.com/AdvancED+Conference+October+2011 • Or • http://wassel.wikispaces.com • AdvancEd Conference October 2011 (Link on left side of page)

41. Final thought… http://www.ocdqblog.com/resource/WindowsLiveWriter-Occurredadatadefecthas_B2E8-?fileId=10269733&__SQUARESPACE_CACHEVERSION=1295290252130