Coaching Data Teams

1. Coaching Data Teams DEVELOPED BY JANE COOK LITERACY & TECHNOLOGY COACH, EASTCONN jcook@eastconn.org & BETH MCCAFFERY SCHOOL IMPROVEMENT COORDINATOR, LEARN bmccaffery@learn.k12.ct.us Revised 10/14/10

2. Purpose of Training • To highlight characteristics of high quality coaching practices and review the roles of a Data Coach • To examine the coaching process and learn tools to use as a Data Coach to improve Data-Driven Decision Making (DDDM) • To provide opportunities to apply coaching practices

3. Objectives for Learners Participants will: • Examine the research on coaching that supports DDDM. • Identify the roles and responsibilities of a coach and effective models for coaching. • Observe and apply coaching behaviors that influence best practices and result in high student achievement.

4. Connecticut Accountability for Learning Initiative (CALI)

5. SRBI Framework for Student Achievement Assessment Instruction Strategic Decision-Making

6. Essential Questions • What does the research say an effective Data Coach needs to know and be able to do? • What tools can Data Coaches employ to help educators use data to inform curriculum, instruction and assessment?

7. Norms for Collaboration • Pausing • Paraphrasing • Probing for specificity • Putting ideas on the table and pulling them off • Paying attention to self and others • Presuming positive intentions • Pursuing a balance between advocacy and inquiry Source: Center for Adaptive Schools, http://csi.boisestate.edu/Improvement/7%20Norms.pdf These norms have been updated in The Data Coach’s Guide to Improving Learning for All Students by Nancy Love, 2008

8. Tools for Coaching Data Teams:Affinity Data • Spatial and interactive • Allow for quick and easy data collection • Ensures that everyone’s ideas are heard • Gives all ideas equal weight • Encourages looking from other people’s perspectives • Helps group to identify natural connections among ideas

9. Affinity Diagram: Characteristics of an effective Data Coach Directions (See pp. 3-5 in your handout): • Individually write 5 characteristics that an effective coach should possess on the post it notes provided.

10. Affinity Diagram: Characteristics of an effective Data Coach (continued) Directions (See pp. 3-5 in your handout): • At your table, share your responses and eliminate any that are exact duplicates. • Have one member of your group place your group’s large post it note responses on the chart paper posted around the room.

11. Affinity Diagram: Characteristics of an effective Data Coach (continued) Directions (See pp. 3-5 in your handout): • When directed, go to the chart paper and organize the post it notes into logical groupings, building an Affinity Diagram. • When asked, suggest a logical header for each group. The trainer will write a header card based on the group’s suggestions. • Reflect and Write: Using the modified T-chart on p. 5 in the handout, list Characteristics of Affinity Diagrams and respond to the following questions: • How can I use Affinity Diagrams? • When can I use Affinity Diagrams?

12. Reflect and Write • Consider the most important characteristics of Affinity Diagrams. List them on your T-chart on p. 5. • Reflect and Write: Respond to the following questions on your T-chart on p. 5: • How can I use Affinity Diagrams? • When can I use an Affinity Diagram in my work as a Data Coach?

13. Tools for Coaching Data Teams:Jigsaw • Cooperative learning strategy with a 30 year track record that serves as a catalyst for discourse • Time effective strategy which allows all to the learn the content by splitting up the work (Many hands make light work) • Participants become experts on one piece of the content and share their expertise with a home group • Each person is a critical member in the learning

14. Data Coaches Jigsaw Activity Directions: • Count off by 4’s and get into your Expert Group by number. • Read the following sections in the chapter on pp. 8-10 in your handout: • The 1’s will read the Introduction section. • The 2’s will read the Knowledge and Skills section. • The 3’s will read the Challenges section • The 4’s will read the Snapshot of a Coach as a Data Coach section • In your group, develop a method and materials to teach your Home Group about your section. You’ll have 2.5 minutes to teach your section.

15. Data Coaches Jigsaw Activity (continued) Directions: • Return to your Home Group. • Refer to p. 8 in your handout and assign roles for your Home Group. • Teach your section to your Home Group. You’ll have 2.5 minutes to teach your section. • Each group will report out the insights from their learning in 1 minute or less.

16. What does the research say? Characteristics of Effective CoachesAccording to NSDC • Beliefs • Teaching expertise • Coaching skills • Relationship skills • Content expertise • Leadership skills See page 7 in handout

17. The Roles of the Data Coach Source: The Data Coach’s Guide to Improving Learning for All Students by Nancy Love, et al, Corwin Press, 2008

18. What does the research say? The Roles of the Data Coach According to Nancy Love, et al The Data Coach is a: • Role model of a “data literate” mindset • Developer of “Data Literacy” skills in others • Facilitator • Leader for sustainability Source: The Data Coach’s Guide to Improving Learning for All Students by Nancy Love, et al, Corwin Press, 2008

19. What are the Big Ideas related to Essential Question 1 -What does the research say an effective Data Coach needs to know and be able to do? Essential Question 1 Closure

20. Reflect and Write • Consider the knowledge, skills, roles and responsibilities that coaches have. • Reflect and write • At least one aspect of the work of coaches in the left-hand column • What you need or want to work on related to this aspect of your coaching work

21. Building Data Literacy The Four Phases of the Data-Driven Dialogue: • Predict • Go visual • Observe • Infer/Question Source: The Data Coach’s Guide to Improving Learning for All Students by Nancy Love, et al, Corwin Press, 2008

22. Tools for Coaching Data Teams:Consensogram Directions: • Review background information on Consensograms on p. 14 in your handout. • Look at p. 15 and respond to each question on a small post it note (one note per question). • Place your post it notes on the chart paper.

23. Tools for Coaching Data Teams:Task Deconstruction Protocol • Share task (assessment item) with teachers. •  Direct teachers to complete the task. • Brainstorm with teachers the concepts and skills students must know and be able to do in order to successfully / accurately complete the task. • Complete the task deconstruction matrix. • Examine student work for evidence of knowledge and skills in the work presented. • Identify patterns or areas of concern presented in the data resulting from analysis of student work.

24. Deconstructing the Task A Looking at Student Work Protocol from Nancy Love Task: Draw a parallelogram. Explain in writing why the shape you drew is a parallelogram.

25. Facilitating: Coaches as Questioners • How can my use of questions probe others’ thinking? • How do I pose questions that promote reflection? • What are some examples of Data Team Leader questions? • How can these questions be adapted for use by Data Coaches?

26. Multiple Measures of Data

27. Tools for Coaching Data Teams: Concerns-Based Adoption Model IMPACT TASK SELF Source: Taking Charge of Change by Shirley M. Hord, William L. Rutherford, Leslie Huling-Austin, and Gene E. Hall, 1987

28. Mentoring & Coaching Support: The Bridge to Adoption • The left side of the bridge focuses on Self concerns which are addressed through training. • Mentoring and coaching support in a positive, safe environment address the Task concerns. • Only then can people cross the bridge to focus on Impact concerns and fully implement the Adoption of the change. Source: Barry Sweeney, International Mentoring Association http://www.mentoring-association.org/membersonly/CBAM.html

29. Sustainability • Collaborative inquiry • Professional development • Change theory • School culture • Vision • Systems thinking Source: The Data Coach’s Guide to Improving Learning for All Students by Nancy Love, et al, Corwin Press, 2008

30. Data Coach Scenarios • Scenario A • Scenario B • Scenario C • Scenario D

31. Tools for Coaching Data Teams: Collaborative Assessment Looking at Student Work Protocol • Getting Started • Describing the Work • Asking Questions About the Work • Speculating About What the Student Is Working On • Hearing from the Presenting Teacher • Discussing Implications for Teaching and Learning • Reflecting on the Collaborative Assessment Conference • Thanks to the Presenting Teacher

32. Steps for Coaching Data Teams • Build relationships • Help teams request your services with an identified need or area of concern. • Observation of Data Team • Feedback • Reflection

33. Technology Tools & Resources to Support Coaching Data Teams • Exploring http://calicoaches.wikispaces.com and other Web-based resources • Excel Templates • NSDC Coach Interaction Spreadsheet • CBAM Spreadsheet • Stoplight Highlighting of CMT or CAPT Data • Text-based resources - Bibliography on p. 48 in your handout

34. Essential Question 2 Closure: What tools can Data Coaches employ to help educators use data to inform curriculum, instruction and assessment?

35. Your Feedback • Please take the time to complete the feedback form provided. • Make sure you have signed the CALI sign- in sheet before you leave (if you have not done so already).