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Data-Driven Dialogue - Copyright 2006 – MiraVia LLC – All rights reserved Data Driven Dialogue: Facilitating Collaborative Inquiry Developed by Bruce Wellman.

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Presentation on theme: "Data-Driven Dialogue - Copyright 2006 – MiraVia LLC – All rights reserved Data Driven Dialogue: Facilitating Collaborative Inquiry Developed by Bruce Wellman."— Presentation transcript:

1 Data-Driven Dialogue - Copyright 2006 – MiraVia LLC – All rights reserved Data Driven Dialogue: Facilitating Collaborative Inquiry Developed by Bruce Wellman and Laura Lipton Day Four

2 Data-Driven Dialogue - Copyright 2006 – MiraVia LLC – All rights reserved Seeing Systems 3 – 2 – 1 +1 H/O p. 26 3 – Strong suits 2 – Growth areas 1 – point to ponder

3 “Now this little model is special-made for committees……………. It comes equipped with one gas pedal, four steering wheels and ten sets of brakes.”

4 Data-Driven Dialogue - Copyright 2006 – MiraVia LLC – All rights reserved The “D’s” of Data DenyDiscover DistortDetermine DefendDecide DeleteDeliberate

5 Data-Driven Dialogue - Copyright 2006 – MiraVia LLC – All rights reserved A Change Formula Change =AxBxC>X A- Shared dissatisfaction B- Shared vision C- Knowledge of practical next steps X- Cost of change

6 Data-Driven Dialogue - Copyright 2006 – MiraVia LLC – All rights reserved Seeing Systems 3 – 2 – 1 +1 3 – Strong suits 2 – Growth areas 1 – point to ponder

7 Leading Systems Clear and Agreed Upon Standards Technological Infrastructure: How we know Managing Data Identifying Organizing Accessing Displaying

8 Leading Systems Clear and Agreed Upon Standards Organizational and Individual Capacities: What we talk about Structural Capacities Aligned curriculum Aligned instruction Aligned assessments Technical Capacities Assessment literacy Data analysis skills Learning-focused instruction Learning-focused supervision Learning-focused professional development Standards-based grading/reporting Professional Capacities Knowledge of the structure of the content discipline(s) Knowledge of self (values, beliefs, standards Knowledge of teaching skills and strategies Knowledge of learners and learning

9 Leading Systems Clear and Agreed Upon Standards Sociological Infrastructure: How and why we talk Attention to Task Learning-focused Time and energy efficient Data-driven Attention to Process Shared tools and structures Learning-focused conversations Data-driven dialogue Attention to Relationship Shared norms and values School culture Professional community

10 Data-Driven Dialogue - Copyright 2006 – MiraVia LLC – All rights reserved Compass Points North – Just get it done. East – Look at the big picture. South – Consider everyone’s feelings West – Pay attention to details.

11 Data-Driven Dialogue - Copyright 2006 – MiraVia LLC – All rights reserved Compass Points Go to your compass point of preference. Form clusters of 3-4. Create a T-Chart listing the strengths and limitation of that preference. Strengths Limitations

12 When a person pauses in mid sentence to choose a word, that’s the best time to jump in and change the subject.

13 “It’s like an interception in football! You grab the other guy’s idea and run the opposite way.”

14 The more sentences you complete. The higher your score. The idea is to block the other guy’s thoughts and express your own. That’s how you win.

15 “Conversations aren’t contests.” OK. A point for you. But I’m still ahead.

16 Data-Driven Dialogue - Copyright 2006 – MiraVia LLC – All rights reserved Blocks to Understanding: “I” Listening Be aware of Personal Referencing Personal Curiosity Personal Certainty Pg. 20

17 Data-Driven Dialogue - Copyright 2006 – MiraVia LLC – All rights reserved Join your and share some of your experiences with these listening patterns. Pair and Share

18 Data-Driven Dialogue - Copyright 2006 – MiraVia LLC – All rights reserved “I” Listening Personal referencing

19 Data-Driven Dialogue - Copyright 2006 – MiraVia LLC – All rights reserved “I” Listening Personal curiosity

20 Data-Driven Dialogue - Copyright 2006 – MiraVia LLC – All rights reserved “I” Listening Personal certainty

21 Data-Driven Dialogue - Copyright 2006 – MiraVia LLC – All rights reserved Intervening with “I” Listening Personal Referencing “How much detail do you need to move forward with this item?” Personal Curiosity “How many of you are interested enough in this topic to stick with it at this point in time?” Personal Certainty “How many of you are still exploring possibilities here and are not yet ready to move to solutions or proposals for action?” Pg. 20

22 Data-Driven Dialogue - Copyright 2006 – MiraVia LLC – All rights reservedBREAK Please return at 10:15

23 Data-Driven Dialogue - Copyright 2006 – MiraVia LLC – All rights reserved COLLABORATIVE LEARNING CYCLE - Pg.44 Managing Modeling Mediating Monitoring Activating and Engaging Exploring and Discovering Organizing and Integrating

24 Data-Driven Dialogue - Copyright 2006 – MiraVia LLC – All rights reserved COLLABORATIVE LEARNING CYCLE Managing Modeling Mediating Monitoring Activating and Engaging Surfacing Experiences and Expectations What are some predictions we are making? With what assumptions are we entering? What are some questions we are asking? What are some possibilities for learning that this experience presents to us?

25 Data-Driven Dialogue - Copyright 2006 – MiraVia LLC – All rights reserved Question Brainstorming On your own -- generate 2-3 questions about gender and reading at the 3rd grade level. Record each of these on a post-it note. Share and categorize your post-it notes. Create labels for your categories. “Step back” from your categories. Surface the assumptions that underpin your ideas and categories.

26 Data-Driven Dialogue - Copyright 2006 – MiraVia LLC – All rights reservedLUNCH Please return at 12:15

27 “Play some Frisbee, chew on an old sock, bark at a squirrel. If that doesn’t make you feel better, eat some cheese with a pill in it.”

28 “My team is having trouble thinking outside the box. We can’t agree on the size of the box, what materials the box should be constructed from, a reasonable budget for the box, or our first choice of box vendors.”

29 “My team has created a very innovative solution, but we’re still looking for a problem to go with it.”

30 Data-Driven Dialogue - Copyright 2006 – MiraVia LLC – All rights reservedPredictions Based on this demographic information -- what are some of your predictions for? - The overall reading performance of these grade three students. - (Level 1, Level 2, Level 3, Level 4) (1 is low -- 4 is high -- 3 is the standard) - Student performance disaggregated by gender.

31 Data-Driven Dialogue - Copyright 2006 – MiraVia LLC – All rights reserved Data Samples Grade 3 Reading by gender for school. Four levels - 1 is low -- 4 is high -- 3 is the standard Grade 3 Reading Questionnaire by gender (4 questions) 1. I’m a good reader. 2. I like to read. 3. I read by myself at home. 4. I read with someone older than me at home.

32 Data-Driven Dialogue - Copyright 2006 – MiraVia LLC – All rights reserved DATA TEAMS H/O p. 13 RECORDER: Be sure to check with each team member before recording observations MATERIALS MANAGER: Organize data, display set up charts for viewing, recording

33 Data-Driven Dialogue - Copyright 2006 – MiraVia LLC – All rights reserved DATA TEAMS PROCESS CHECKER: Use the Collaborative Cycle (p.44) to guide the process: Monitor for balanced participation ENVIRONMENTAL ENGINEER: Organize the physical arrangement for team work – chairs in a horseshoe around the central displays

34 Data-Driven Dialogue - Copyright 2006 – MiraVia LLC – All rights reserved Data Station Set-Up

35 Data-Driven Dialogue - Copyright 2006 – MiraVia LLC – All rights reserved C OLLABORATIVE LEARNING C YCLE Managing Modeling Mediating Monitoring Exploring and Discovering Analyzing the Data What important points seem to “pop-out”? What are some emerging patterns, categories or trends ? What seems to be surprising or unexpected? What are some things we have not yet explored?

36 Data-Driven Dialogue - Copyright 2006 – MiraVia LLC – All rights reserved Principles of Data-Driven Dialogue  Conscious Curiosity  Purposeful Uncertainty  Visually Vibrant Information

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42 Data-Driven Dialogue - Copyright 2006 – MiraVia LLC – All rights reservedREFLECTION What are you noticing about yourself as a participant? What do you want to be aware of when you apply this phase with others?

43 Data-Driven Dialogue - Copyright 2006 – MiraVia LLC – All rights reservedBREAK Please return at 2:00

44 Data-Driven Dialogue - Copyright 2006 – MiraVia LLC – All rights reserved What are some solutions we might explore as a result of our conclusions? (action) What data will we need to collect to guide implementation? (calibration) COLLABORATIVE LEARNING CYCLE Managing Modeling Mediating Monitoring Organizing and Integrating Generating Theory What inferences/explanations/conclusions might we draw? (causation) What additional data sources might we explore to verify our explanations? (confirmation)

45 Data-Driven Dialogue - Copyright 2006 – MiraVia LLC – All rights reserved Theories of Causation - h/o p. 14 Framing: Observation, Question, Hypothesis (“story line”) Use this space to record two possible theories of causation re: your observation, question, or hypothesis 1. 2. Circle one theory. In this space, record at least three sources of data you could use to confirm this theory.

46 Data-Driven Dialogue - Copyright 2006 – MiraVia LLC – All rights reserved Walk-Around Survey Key learnings Tools to try My next steps Collaborative Inquiry

47 Data-Driven Dialogue - Copyright 2006 – MiraVia LLC – All rights reserved Walk-Around Survey Collaborative Inquiry name Key learnings Tools to try My next step

48 Data-Driven Dialogue - Copyright 2006 – MiraVia LLC – All rights reserved LEARNING PARTNERS handout p.27 _______________ ______________ _______________ Your partner’s name


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