1. Welcome Please sit in groups. Thanks. January 10 & 25, 2017
Margie Johnson, Ed.D.
Business Intelligence Coordinator

2. Today’s Purpose and Outcome
Our purpose is to foster a culture of collaboration to support student success.
Our outcome for today’s meeting is to use culture and climate data and model the collaborative inquiry process to generate theories of causation and next steps.

3. Groups at Work – 2011 MiraVia LLC – All rights reserved
Culture is like…..
Because……..
Groups at Work – 2011 MiraVia LLC – All rights reserved

4. Data have no meaning. Meaning is imposed through interpretation
(Wellman & Lipton, 2004, pp. ix-xi).

5. MNPS Collaborative Inquiry
Collaborative Inquiry is a data-based team process that consciously uses the collaborative learning cycle (activating and engaging, exploring and discovering, and organizing and integrating) and the qualities of effective groups (fostering a culture of trust, maintaining a clear focus, taking collective responsibility and data-informed decision-making).
MNPS Collaborative Inquiry Community of Practice

6. Collaborative Learning Cycle
Activating and Engaging
What assumptions do we bring?
What are some predictions we are making?
What questions are we asking?
What are some possibilities for learning?
Organizing and Integrating
What inferences, explanations, or conclusions might we draw?
What additional data sources might verify our explanations?
What solutions might we explore?
What data will we need to guide implementation?
Managing
Modeling
Mediating
Monitoring
Exploring and Discovering
What important points seem to pop out?
What patterns, categories, or trends are emerging?
What seems to be surprising or unexpected?
What are some ways we have not yet explored these data?
--Lipton, L. & Wellman, B. (2012). Got data? Now what? Bloomington, IN: Solution Tree, Inc.

7. Observations

8. Observations
Because

9. Organizing and Integrating

10. Causal Categories
Now that we have activated, engaged, explored, and discovered observations about the data, let’s begin organizing and integrating the data to generate theory. During this phase, we move from problem finding to problem solving. When looking at causation, theories fall into these five causal categories----
Let’s take few minutes to work in your small groups to complete the Theories of Causation worksheets.
--Lipton, L. & Wellman, B. (2012). Got data? Now what? Bloomington, IN: Solution Tree, Inc.

11. Individually generate a couple of theories of causation.
Students lack social emotional and self-regulatory skills.
Teachers’ instructional methods are not engaging to students.
Teachers lack the knowledge and skills to facilitate learning in their classrooms.

12. What might be some next steps for this work?

13. Exit Ticket Reflection
What might be some actions you take as a result of our time together today?

14. Feedback--- How Was Today’s Meeting
Individually
Use post-it notes to provide feedback.

15. Wrap-Up….

16. MNPS Collaborative Inquiry Toolkit

17. References
Lipton, L. & Wellman, B. (2012). Got data? Now what? Bloomington, IN: Solution Tree. Lipton, L. & Wellman, B. (2011). Groups at work: Strategies and structures for professional learning. Sherman, CT: MiraVia, LLC. Love, N. (2009). Using data to improve learning for all: A collaborative inquiry approach. Thousand Oaks, CA: Corwin. Love, N., Stiles, K.E., Mundy, S., & DiRanna, K. (2009). The data coach’s guide to improving learning for all students: Unleashing the power of collaborative inquiry. Thousand Oaks, CA: Corwin.

18. Thanks for all you do for our students!
Hope you have a wonderful day!