Coaching Data Teams JANE COOK LITERACY & TECHNOLOGY COACH, EASTCONN BETH MCCAFFERY SCHOOL IMPROVEMENT COORDINATOR, LEARN

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 develop an action plan for implementing data coaching practices to support DDDM

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. Apply coaching behaviors that influence best practices.

Essential Questions Why are Data Coaches needed? What is the theory behind data coaching? What is an effective Data Coach? What do effective Data Coaches do? What tools can Data Coaches employ to help educators use data to inform curriculum, instruction and assessment?

What are the characteristics of an effective Data Coach? Directions (See pp. 3-6 in your handout): Individually write 5 characteristics that an effective coach should possess. Share your response with another person.

What are the characteristics of an effective Data Coach? (continued) Directions (See pp. 3-6 in your handout): Join another partner group to form a group of four Select 5 distinct responses to the question. Write each response on sentence strips.

What are the characteristics of an effective Data Coach? (continued) Directions (See pp. 3-6 in your handout): Place sentence strip responses on chart paper posted around the room and build an Affinity Diagram. Summarize the results gathered by the coaches. Debrief the activity.

What does the research say? Characteristics of Effective Coaches Beliefs Teaching expertise Coaching skills Relationship skills Content expertise Leadership skills See page 7 in handout

The Roles of the Data Coach The Data Coach: 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

Data Literacy The Four Phases of the Data-Driven Dialogue: 1.Predict 2.Go visual 3.Observe 4.Infer/Question Source: The Data Coach’s Guide to Improving Learning for All Students by Nancy Love, et al

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?

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

Reflecting on Coaching As an individual, review the quotes on p. 16 in your handout. Put an asterisk in front of the one or two that most intrigue you. Spend three minutes writing about why those quotes resonate for you and how they apply to coaching. Form a triad and use the Microlabs Protocol to discuss these quotes. See Activity Questions at the bottom of p. 17 in your handout.

Coaches Help Mine the Data Creating safe environments Accessing and organizing data Analyzing and interpreting Sustaining Professional Learning Communities

Text Rendering Protocol Read through the text completely. Mark the sentence or phrase that holds particular significance for you. Re-read and reflect until everyone is finished reading.

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

Resources Exploring Text-based resources: See bibliography on p. 26 in your handout

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).