Grant Chandler, Director of Professional Development for MSU MI Excel, Explains phase 2 of the Collaborative Learning Cycle.

Bruce Wellman, Co-Director of MiraVia, LLC, reviews Phase Two of the collaborative learning cycle, strategies to maintain a shared group process, and the most dangerous trap to avoid.

After setting the groundwork, team members begin to review the data. This phase of dialogue involves discovery and prompts teams to remain open to possibilities, look for patterns, and observe the real stories in relation to the data. This is a time of exploration, not explanation.

Corresponds to MI School Improvement Model Phase:

Sketch of Team Activities:

  • Focus on a few key pieces of data.
  • Organize data in large, uncluttered, visually vibrant displays to facilitate group study.
  • Develop multiple descriptive statements about what the data suggest.
  • Refrain from jumping to conclusions about why the data look as they do (e.g., “because the teacher was on leave last year”).
  • Ask questions and explore further opportunities for inquiry (e.g., “Is there a difference between the various subgroups?” or “How did last year’s group do?”).
  • Share and discuss observations, ensuring all team members are included.
  • Delve deeply to understand data for each descriptive statement and discuss team members’ perspectives until all questions and suggestions are addressed.
  • Polish and refine a series of descriptive statementsabout the data.
  • Debrief the process−how did we do?


  • Delve deeply into the data.
  • Surface possible scenarios, ideas based on what the data show.

Key Questions:

  • What points seem to “pop out”?
  • What are the patterns, categories, and trends?
  • What is surprising/unexpected?
  • Are there other avenues to explore?

Why Phase Two Matters:

  • A thoughtful, well-structured exploration of data helps school teams get at the heart of learner performance, achievement gaps, system misalignments, and possible opportunities.
  • Teams learn to view data through different lenses, ask insightful questions, and pursue lines of inquiry in collaborative ways.

 Once teams understand the stories being told by their data, they are ready to act.

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