1. Specialist Workshop II Data Driven Decision Making
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2. Introduction
Name
District
Role (breadth of view in Homeroom)

3. The Basics: Creating Meaningful Subgroups in Assessments
Demo creating subgroups in assessment widget. Give work time.
Work Time: Create a student group based on assessment scores

4. The Basics: Creating Meaningful Subgroups using Strand Data
Use student group to look at an assessment with strands and sort, filter, order strand data to draw conclusions
Work Time: Look at scores for a stranded assessment group students based on performance on a strand.

5. Set Norms
Norms or Routines and Procedures aid in streamlining the DDM process to get to a final goal
Norms for Productivity: We will start on time and Norms for impact: we will use multiple sources of evidence, we will dig beyond student actions to teacher actions
What happens if someone breaks a norm?
Teachers who lead must be teachers who learn. This means admitting publicly what they don’t know and then pursuing the knowledge needed to build capacity in their school. It means taking instructional risks, discussing their failures and sharing their process for working through challenges. Seeking out support from their teacher leader cohort, principal, coach

6. Understand Individual Responsibilities
Responsibilities of Data Team Participants
Data/ Score files to team leader on time
Come with Assessments
Review contextual information related to instruction/assessment time frame prior to meeting
Attendance widget
Behavior widget
Of the data views we’ve gone through today, which would you include to frame data team conversations?

7. Data Team Process

8. The Data Decision Making Process
Data Teams transfer performance level numbers to DDM form
Examine students’ assessments to determine strengths and obstacles
Set attainable SMART goals
Identify resources, strategies that will remedy or repair learning
Determine Results Indicators

9. Step 1
Each teacher opens his/her classroom data in Homeroom Assessment Widget
Each teacher reports whole score data
Number of students assessed
Number of students at Benchmark
Number of students at Strategic
Number of students at Intensive
After step 2, each teacher will report the name and total number of students he/she believes can make benchmark on the next assessment.

10. Step 1 Example

11. Look at the numbers and the assessment
How many students are at each level?
What information does the strand data show?
What does it show about a student’s knowledge/skills to have struggled or excelled on this assessment?
Quick process: report and input of numbers

12. The Data Team Process
Data Teams transfer performance level numbers to DDM form
Examine students’ assessments to determine strengths and obstacles
Set attainable SMART goals
Identify resources, strategies that will remedy or repair learning
Determine Results Indicators

13. Strengths vs. Obstacles

14. Student Centered Teacher Centered
What did student’s know? What were students able to do?
What instruction did you give or what curriculum decisions caused students to have the skill/ knowledge?
What did students struggle with?
What instruction/curriculum choice cause students to not have the skill/knowledge?
Focus on what’s within your locus of control.

15. Dig Into the Data
Sort students’ assessments into Benchmark, Strategic and Intensive piles.
Which skills need to be in place to achieve mastery?
What specific strategies did students master to acquire the skill?
How do student answers indicate understanding vs. misconception?
Be wary of focusing on ‘symptoms’ Look for Root Causes and Underlying factors
Focus on Factors that are a part of the teaching and learning process
Talk about how item analysis level view Can help prioritize standards, provide question level information
Students ‘not caring’ is usually a symptom of a different root cause/ factor.

16. The Data Team Process
Data Teams transfer performance level numbers to DDM form
Examine students’ assessments to determine strengths and obstacles
Set attainable SMART goals
Identify resources, strategies that will remedy or repair learning
Determine Results Indicators

17. Specific, Measurable, Attainable, Results-Oriented, Time-Bound
Goals should be ambitious but feasible
Goals should be exciting, inspiring, energizing for teachers and students

18. What students to target?
Select a targeted skill that addresses deficits you identified in step 2.
Select students you believe can reach mastery if targeted with the right instructional strategies.
Enter number of students and name of students into form

19. The Data Team Process
Data Teams transfer performance level numbers to DDM form
Examine students’ assessments to determine strengths and obstacles
Set attainable SMART goals
Identify resources, strategies that will remedy or repair learning
Determine Results Indicators

21. Questions for the data team:
Is our overall instruction working?
Is our intervention instruction working?
Which skills seem to be receiving more/less impact?
Which skills are less complex?
Which skills are more complex?
Can we name the instructional practices that are impacting/not impacting these skills?

22. Choose the Right Strategies
Strategies should be logically aligned to the obstacle identified in Step 2.
Should address the root cause of the obstacle
Duration: How many weeks are needed for implementation?
Intervention History: What’s worked before? What might you layer onto strategies that improved student learning without gap closure?
Strategy driven not activity driven
Address the root cause: If vocabulary is the problem, teaching strategies to determine word meeting better diagnoses the root cause than teaching more words in isolation.

23. Strategy Implementation
How many days a week will teachers practice the strategies?
Consecutive days?
Number of times in a day?
For how long each time?
How can this strategy be connected with information the student already has? (generalizing/long term memory encoding)
Does every teacher understand how to implement the strategies?

24. Preparing for Data Decision Making
Prepare the Data View at the Meeting
Prepare the View in Advance
Benefits:
All team members contribute to creating the view- deciding on the view
Increases fluency with the process of creating data views
Drawbacks:
Takes time away from the process of digging into the data
Creates more areas for bird walks
Benefits:
Meetings begin quickly and stay focused on data
Maximizes time to spend on understanding the data
Drawbacks:
Requires a person to prepare the view in advance
Preparer must have appropriate homeroom permissions to prepare according to norms

25. The Data Team Process
Data Teams transfer performance level numbers to DDM form
Examine students’ assessments to determine strengths and obstacles
Set attainable SMART goals
Identify resources, strategies that will remedy or repair learning
Determine Results Indicators

27. Executing the Strategies
What would it look like to walk into a classroom where the strategies were being used?
What does it look like/ sound like if the strategy is working?
Variety of modalities for students to interact with the content, practice the skill and concepts.

28. What will it look like to meet our goal?
What assessment will be used to measure our results?
Aligned to the skill you are targeting and the initial assessment.
When is it given?
When will the results be available?
When is our next meeting to celebrate progress and begin the cycle again?

29. Goals
Determine which data views provide the information needed to facilitate data team meetings.
Use filters to create specific student subgroups
Monitor the progress of student groups and subgroups on assessments
Create SMART goals for student groups and subgroups based on assessment data and trends
Plan strategic interventions for student groups and subgroups to make gap closure growth

30. The Basics: Creating Meaningful Subgroups in Student Groups
Demo creating subgroups in student groups Give work time.
Services
Assessments
Credits
Work Time: Create a student group that you want to monitor