Data Driven Dialogue: Having Safe Conversations about Scary Topics

Transcription

1 Data Driven Dialogue: Having Safe Conversations about Scary Topics DATAG Membership Meeting July 12, 2018 Peter McCarthy

2 Cognitive Coaching Adaptive Schools Data Driven Dialogue

3 Data Driven Dialogue: The Collaborative Learning Cycle Wellman and Lipton (2004) Organizing and Integrating Generating Theory Activating and Engaging Surfacing Experiences and Expectations Managing Modeling Mediating Monitoring Exploring and Discovering Analyzing the Data

4 Data Has No Meaning Data is simply information. Individuals and groups create meaning by organizing, analyzing, and interpreting data. Interpretation is subjective; data is objective. Frames of reference influence the meaning we derive from the data we collect. - Laura Lipton and Bruce Wellman

5 Understanding should precede planning When confronted with data, individuals and groups often assign causality and determine solutions without clear problem definitions. They seek the comfort of action rather than navigating the discomfort of ambiguity. Skilled groups cultivate purposeful uncertainty as a pathway to understanding before beginning planning processes.

6 Dialogue vs. Discussion

7 Dialogue comes from the Greek word dialogos. Logos means the word, or the meaning of the word. And dia means through it doesn t mean two. A dialogue can be among any number of people, not just two. Even one person can have a sense of dialogue within himself, if the spirit of dialogue is present. The picture or image that this derivation suggests is of a stream of meaning flowing among and through us and between us. This will make possible a flow of meaning in the whole group, out of which will emerge some new understanding. It s something new, which may not have been in the starting point at all. It s something creative. And this shared meaning is the glue or cement that holds the people and societies together. David Bohm On Dialogue

8 Facilitator s Role Remains neutral to content Focuses group energy Keeps group on task Directs processes Encourages balanced participation Ensures emotional safety The facilitator should never be the person with role or knowledge authority.

9 Paraphrasing to summarize and organize the discussion can be the most powerful facilitator s tool. There are three interpretations on the table. They are We are beginning to consider action steps, such as. Are we ready to move there?

10 Data Driven Dialogue: The Collaborative Learning Cycle Wellman and Lipton (2004) Organizing and Integrating Generating Theory Activating and Engaging Surfacing Experiences and Expectations Managing Modeling Mediating Monitoring Exploring and Discovering Analyzing the Data

11 YEAR VIOLENT PROPERTY

12 Activating & Engaging What are some predictions? What might we learn from this?

13 In the FBI s Uniform Crime Reporting Program, violent crime is composed of four offenses: Murder and non-negligent manslaughter Rape Robbery Aggravated assault. In the FBI s Uniform Crime Reporting Program, property crime includes the offenses of burglary, larceny-theft, motor vehicle theft, and arson. The object of the theft-type offenses is the taking of money or property, but there is no force or threat of force against the victims. All rates are per 100,000 persons.

14 YEAR VIOLENT PROPERTY

15 YEAR VIOLENT PROPERTY MASS SHOOTING

16 YEAR VIOLENT PROPERTY MASS SHOOTING

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18 Exploring & Discovering Analyzing the data What important points seem to pop-out? What are some patterns or trends? What seems to be surprising or unexpected?

19 Organizing & Integrating Generating Theory What explanations / conclusions might we draw? (causation) What additional data sources might we explore to verify our explanations? (confirmation) What are some solutions we might explore as a result of our conclusions? (action)

20 Data Driven Dialogue: The Collaborative Learning Cycle Wellman and Lipton (2004) Organizing and Integrating Generating Theory Activating and Engaging Surfacing Experiences and Expectations Managing Modeling Mediating Monitoring Exploring and Discovering Analyzing the Data How might you apply what you have learned today?