We now have data. What do we do next?
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Transcript of We now have data. What do we do next?
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We now have data.What do we do next?
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DATA . . .“Policy and Practice”
Dr. Doug Christensen
Commissioner, Nebraska Department of Education
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We Have . . .
• Created a “lofty” place for data
• Making data a “commodity”
– systems are being designed to “create” data
• Data is now a product– can be packaged– can be marketed– can be sold
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Commoditizing Data
• Creates new language . . . New questions
• “Data driven” . . .
• What does the data say?
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Few Paying Attention To
• Credability of data
• Accuracy of data
• Prinicples of data collection and use
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“He who has the data, rules . . . the _________”
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Wheatley• “. . . We increasingly depend on numbers to
know how we are doing for virtually everything.”
• “. . . The measures define what is meaningful rather than letting the greater meaning of the work define the measures.”
• “As the focus narrows, people disconnect from any larger purpose and only do what is required of them.”
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Wheatley
• “. . . Dethrone measurement from its godly position, . . .”
• “. . . Offer measurement a new job – that of helpful servant.”
Margaret Wheatley (1999)
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The purpose of data is information.
. . . To “inform”
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Data informs . . .
• Does not “tell”
• Does not “conclude”
• Does not “drive”
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Inform
• The public . . . about value of the public enterprise (how well it is doing)
• The educators . . . to energize and inform the process of continuous improvement
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Three Dimensions of Accountability
• Collecting appropriate, valid and useful data
• Reporting data in understandable ways to our public and stakeholders
• Using the data to inform continuous improvement
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Accountability is a policy of “information”
. . . data is the tool
Data
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Data
• More than test or assessment results• Data includes information about
– processes– inputs– contexts– capacities– –
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Major policy question . . .
• Where does data come from?– Outside?– Inside?– Neither?– Both?
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Rocket to Moon
• Off course 95% of the time
• Instruments that fed data to rocket engines and navigation systems were on board the rocket– Not remote– Not on the ground
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Data about student learning
• Must come from– Assessments of learning (not tests)– Assessments of
• Processes• Inputs• Contexts• Capacities• •
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Assessments of Learning
TestsDemonstrationsPerformancesPortfolios (over time)Observations
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Test data is far too narrow to inform.
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Here is our point . . .
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Data from classroom (point of activity) tends to create change by informing the engagement of the key players.
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Data from the classroom empowers
• Informs individuals about what doing and how well
• Provides feedback for self direction• Provides feedback to system re supports
needed• • •
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Primary goal of data is empowering the learner . . .
• Learn what is expected
• Learn to self determine level beyond expectations
• Learn beyond content
• Learn how to learn and direct own learning
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Data should inform key education decisions and decision-makers . . .
– Who is learning? What?– Who is not learning? What?– What do we do about both?
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Data should inform key policy questions
Excellence –
How well . . .?
How much . . .?
Equity –
For whom?
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What is a “good” school?
Overall achievement is highSubgroup achievement mirrors the
whole groupBoth trend lines are moving upwardGaps are narrowing
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Data Should InformAlignment and Rationality
Programs, Practices
School Aims and Goals
District Aims and Goals
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Data should inform . . .
• Strengths
• Areas of concern
• Possible strategies
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Policy Pitfalls of Data
• Indicators Outcomes• About process not technology• Data threatens . . .
– People– Conventional wisdom– Current authority–
• Does not save time• Bad data = bad decision-making
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Einstein
Not everything that can be counted counts, and not everything that counts can be counted.
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We now have data.What do we do next?
Dr. Pat Roschewski
Statewide Assessment Director, NE Department of Education
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The Continuous Improvement
Model
The “No Fear” Model
Data,
Data,
Data
Where are we?
What should be our goals?
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Organizing For Data Analysis
Who Should be Involved In . . .
Collecting Data Displaying Data Analyzing Data Sharing Results of Data Other Local Uses of Data
Involve AllAll – 100% have a voice
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Organizing For Data Analysis
Grouping for Involvement Grade levels Departments Subject Areas Staff, Students, Parents, Support Staff,
Community Members, Board Members
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Organizing For Data AnalysisWhen? Pre-service, early out, late starts, mid-year, summer,
common planning times
How Often? Frequency Multiple Sessions
Format Big Picture – District Data – 1st session Building, grade level disaggregated – 2nd session By standard by student – 3rd and subsequent sessions
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Understanding Data Basics
Data Sources
Data for Specific Purposes
Clarification of Data Types
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Ground Rules
No blaming students No blaming teachers Data is just information Use data for instructional
purposes “De-emotionalize” data
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Analyzing Data
What do these data show? Factual Information
Why might this be? Hypotheses
How should we respond? Planning for action
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Reading_____________________________________________________________________________________________________________________________________
Math_____________________________________________________________________________________________________________________________________
Question One: What do these data show us?(Factual Information)
1. How many students are involved?
2. How many students met the standards?
3. How many students are in each proficiency level?
4. How great are the differences in grade levels?
5. What stands out in the data?
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Question Two: Why Might this be?(Hypotheses)
1. Does the assessment measure what we teach? Why/why not?2. How does the timing of assessment impact the outcomes?3. What trends do we see in the data? Why?4. Skill strengths? Weaknesses?5. What differences are there in grade level or sub-groups? Why?
Reading_____________________________________________________________________________________________________________________________________
Math_____________________________________________________________________________________________________________________________________
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Question Three: How should we respond?(Planning for Action)
1. How do we match instruction to skill needs? Do we have the skill as a staff to do that?2. How can we obtain the knowledge of instructional strategies
for all staff?3. In what ways do we offer remediation or acceleration? In classroom,
summer, flexible grouping, curricular adjustment?4. How can we effectively monitor, support, and evaluate classroom
effectiveness?
Reading_____________________________________________________________________________________________________________________________________
Math_____________________________________________________________________________________________________________________________________
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We now have data.What do we do next?
David D. Hamm
Superintendent, Plainview Public Schools
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Questions to Ponder
Why is it important to be able to produce evidence of what the school achieves for its students?
Is accountability a matter of compliance or responsibility?
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When playing golf, which shot is the most important?
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A Data ‘Rich’ Environment Board of Education
Administrative Team
Leadership Team
Teachers
Community
Students
How does ‘this’ benefit kids?
Live it every day!!!
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It all starts with data ‘mining.’
Define the essential questions that matter most to your school system.
Describe the types of evidence you will need in order to answer the questions.
Identify the measures that will be needed to collect the necessary evidence.
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We now have data.What do we do next?
Jan K. Hoegh
Statewide Assessment, NE Department of Education
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Good ‘old’ days
Good ‘new’ days
TELL me! SHOW me!
versus