DATA COACHING: ESTABLISHING THE RIGHT...
Transcript of DATA COACHING: ESTABLISHING THE RIGHT...
© 2015, Battelle for Kids. All Rights Reserved
Data Coaching Learning Lab Components
An Overview of
Data Coaching
Establishing the
Right Conditions:
Culture and
Structure
Establishing the
Right Conditions:
Access and
Data Quality
The Data
Coaching
Process
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Data-literate educators…
are comfortable discussing data
in a safe environment…
can freely access multiple sources of data…
have regular opportunities to discuss and
act upon data to make informed decisions…
and use only high-quality data.
© 2015, Battelle for Kids. All Rights Reserved
Learning Targets for Learning Lab #2: Culture and Structure
Identify the importance of culture and structure in
building a data-literate team
Understand how to build a culture that promotes
data literacy
Understand how to create structures to support
data-informed decisions
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ESTABLISHING A CULTURE THAT PROMOTES DATA LITERACY
Culture represents the norms, values,
and traditions which establish the expectations for collaboration.
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In other words…
“This is the way we do things.”
“This is what we value.”
“This is how we interact.”
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A Congenial Culture
Preserves harmony and avoids conflict
Works comfortably in isolation
Limits discussions about professional practice
A Collegial Culture
Engages in cognitive conflict
Values sharing practices and decision-making
Maximizes knowledge and experience
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Congenial or Collegial?
Planning a shower in honor of a teacher’s upcoming wedding
Visiting another teacher’s classroom to gather ideas for classroom management
Sharing classroom data with a fellow teacher and comparing instructional strategies
Displaying diagnostic data and thanking everyone for their hard work
Congenial
Collegial
Congenial
Collegial
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Creating a Culture of Collegiality
Identify and share structures and expectations for
collegial interaction to improve teaching and learning
Showcase and reinforce collegial behaviors
Model collegiality through shared problem-solving
Establish a growth mindset
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Consider this Scenario…
A first year high school math teacher is eager to learn
from the expertise of a respected colleague. The new
teacher asks if she can observe his classroom. The
seasoned teacher politely declines the request and
tells her that he became a successful teacher through
trial and error and recommends this approach.
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Leveraging a Collegial Culture to Build Data Literacy
Consider multiple measures when analyzing and using data.
Use data to identify and act on areas of strengths.
Use data to identify and act on opportunities for improvement.
Identify contributing factors when analyzing and using data.
Model and supporting the appropriate use of data.
Share ownership and model a spirit of collaborative inquiry.
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Unresponsive Emotional Reflective
• Does not believe student learning is improved by data
• Does not believe professional practice can be informed by data
• Protects the status quo
• Does not trust or value the underlying measures that generated the data
• Believes data is tied to labels that indicate professional worth
• Thinks data will be misinterpreted and therefore misused
• Worries that the data might necessitate reflection and change
• Examines data for areas of strength and opportunities for professional growth
• Uses data to identify contributing factors and analyze cause and effect
• Commits to ongoing professional growth in support of students
Understanding Responses to Data
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Consider this Scenario…
The principal is meeting with each teacher to have a
collaborative conversation about data that was
calculated through student growth measures. The
teacher walks into the principal’s office, looks at the
results of recent assessments, and responds
emotionally.
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ESTABLISHING THE RIGHT STRUCTURE
Structure refers to the opportunities
available to educators to discuss data.
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Teams Time Expectations
Collaborative
teams based on
purpose:
• Grade-level
• Departmental
• Vertical
• Interdisciplinary
• Operational
Regularly
scheduled meeting
times:
• Daily
• Weekly
• Every Two Weeks
• Monthly
• Quarterly
Clearly defined
expectations:
• Processes
• Guidelines
• Agendas
• Monitoring
• Follow-Up
Structures for Data-Informed Decisions
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To what extent do you
feel this is happening
in your setting?
Review and discuss
the
survey results.
Data Coaching Reflection on Culture and Structure
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Complete the activities in the Facilitation Guide
Reflection: Culture and Structure Reflection
Collegial Scenarios
Responding to Data Scenarios
Collaborative Time
Data Team Meetings and Expectations
Begin Learning Lab #3: Data Quality and Access
Next Steps