Data Teams
Data Teams
Data Teams is a six-step process that allows you
to examine student data at the micro level
(classroom practitioner level).
Data Teams provide a structure for teachers to
specifically identify areas of student need and
collaboratively decide on the best instructional
approach in response to those needs.
Data Teams Definitions:
•
Data Teams use common standards, generate common
formative assessments (CFAs), and use common scoring
guides to monitor and analyze student performance.
•
Data Teams are small, grade-level, department, course, content,
or organizational teams that examine work generated from a
common formative assessment (CFA) in order to drive
instruction and improve professional practice.
•
Data Teams have scheduled, collaborative, structured meetings
that concentrate on the effectiveness of teaching and learning.
`
We are a Professional Learning Community.
We do Data Teams.
Four Critical Questions that guide a PLC:
1. What are students supposed to know and be able to
do?
COMMON CORE STANDARDS
2. How do we know when our students have learned?
COMMON FORMATIVE ASSESSMENTS
3. How de we respond when students haven't Learned?
INTERVENTION
4. How do we respond when students already know the
content? DIFFERENTIATION
Data Teams Six-Step Process
Step 1:
Collect and
Chart Data
Step 2:
Analyze Data
and Prioritize
Needs
Data
Teams
Process
Step 6:
Monitor and
Evaluate
Results
Step 5:
Determine
Results
Indicators
Step 3:
Set
SMART
Goals
Step 4:
Select
Common
Instructional
Strategies
The DATA TEAM Meeting Cycle
Meeting 1: First Ever
•
Understand the purpose of Data Teams and their
alignment with the beliefs of the school
•
Understand the purpose of Data Teams
•
Understand the six-step Data Teams process
[Note: The actions of Meetings 1 & 2 can occur at the same time if time permits.]
The DATA TEAM Meeting Cycle
Meeting 2: Before Instruction
•
Meet with the Team to determine the roles, responsibilities, and
commitments
•
Determine the common standards or areas of student learning
on which the Data Team will focus first
•
Create the short-cycle, common formative pre-assessment to
measure a small chunk of learning
•
Identify the date to administer the pre-assessment
The DATA TEAM Meeting Cycle
Meeting 3: Before-Instruction Collaboration
•
Analyze the pre-assessment results
•
Follow the Six-Step Data Teams process
(Note: Examples of the Six-Step Data Teams process follows on the next 6 slides)
Step 1: Collect & Chart Data
Teacher
# Students
# Proficient and Higher
% Proficient and Higher
# Close to Proficiency
% Close to Proficiency
Name of Students Close
to Proficiency
# Far to Go But Likely to
Become Proficient
% Far to Go But Likely to
Become Proficient
Name of Students Far To
Go But Likely to Become
Proficient
# Intervention
% Intervention
Name of Intervention
Students (Far to Go and
Not Likely to Become
Proficient)
Step 1: Collect and Chart Data
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TEAM
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Step 2: Analyze Data and Prioritize Needs
Why?
To identify causes for celebration and to identify
areas of concern
Considerations:




Performance Strengths
Needs (Errors and Misconceptions)
Performance behavior
Inference/Rationale
Step 2: Analyze Data and Prioritize Needs
Step 2: Analysis - Identify Strengths and Performance Errors or Misconceptions
Identify the prioritized need for each group of students by placing a 1 in the column next to that need.
Students Close to Proficiency
Performance Strengths
Inference
Performance Errors and/or Misconceptions
Inference
Students Far to Go But Likely to Become Proficient
Performance Strengths
Inference
Performance Errors and/or Misconceptions
Inference
Intervention Students (Far to Go But Not Likely to Become Proficient)
Performance Strengths
Inference
Performance Errors and/or Misconceptions
Inference
Step 3: Set SMART Goals
Why?
To identify your most critical goals for student achievement for each
category of students (e.g., Close to Proficient, Intervention, etc.)
Criteria:





Specific (What exactly will we measure?)
Measurable (How will we measure it?)
Achievable (Is this a reasonable goal?)
Relevant (Are goals aligned with the CIP?)
Timely (Does each goal have a defined timeframe?)
Step 3: Set SMART Goals
Step 3: SMART Goal Statement
0%
Group:
Current
Proficiency:
End of Unit
Date:
Topic:
0%
Projected
Goal:
0%
0%
Adjustment:
Assessment
Tool:
Modified Goal:
0%
Assessment
Date:
The percentage of _______students proficient or higher in _____will increase from X% to Y% by _____as measured by a(n) ______ given on________ .
Step 4: Select Common Instructional Strategies
Why?
Adult Actions will impact student achievement
Strategies are:
Considerations:




 Instructional Strategies
should be the main focus
during the Data Teams
process
Action-oriented
Measurable
Specific
Research-based
Step 4: Select Common Instructional Strategies
Step 4: Select Instructional Strategies
Review the list below and record selected strategies in the chart.
Name of Students Close to Proficiency
Identified Need:
Inference:
Selected Instructional Strategy
Learning Environment
Time - Duration of the Teaching
of Specific Concepts and Skills
Materials for Teachers and Students
Assignments, Assessments - Where will students be required
to use the strategy?
Name of Students Far To Go But Likely to Become Proficient
Identified Need:
Inference:
Selected Instructional Strategy
Learning Environment
Time - Duration of the Teaching
of Specific Concepts and Skills
Materials for Teachers and Students
Assignments, Assessments - Where will students be required
to use the strategy?
Name of Intervention Students (Far to Go and Not Likely to Become Proficient)
Identified Need:
Inference:
Selected Instructional Strategy
Learning Environment
Time - Duration of the Teaching
of Specific Concepts and Skills
Materials for Teachers and Students
Assignments, Assessments - Where will students be required
to use the strategy?
Step 5: Determine Results Indicators
Why?
To Describe explicit behaviors (both student and adult) we expect to see as
a result of implementing the instructional strategies plan. How will you
know that the strategies are working? Look-fors and evidence of learning?
What are proficient students able to do successfully?
Considerations:




Serve as an interim measurement
Used to determine effective implementation of a strategy
Used to determine if strategy is having the desired impact
Used to help determine midcourse corrections
Step 5: Determine Results Indicators
Step 5: Results Indicators
Name of Students Close to Proficiency
Identified Need:
Inference:
Results
Indicators:
Selected Strategy:
Adult Behaviors:
Student Behaviors:
Look fors in Student Work:
Name of Students Far To Go But Likely to Become Proficient
Identified Need:
Inference:
Results
Indicators:
Selected Strategy:
Adult Behaviors:
Student Behaviors:
Look fors in Student Work:
Name of Intervention Students (Far to Go and Not Likely to Become Proficient)
Identified Need:
Inference:
Results
Indicators:
Selected Strategy:
Adult Behaviors:
Student Behaviors:
Look fors in Student Work:
The DATA TEAM Meeting Cycle
Monitoring Meetings
•
Occur between Meeting 3 and Meeting 4
•
Discuss the strategies. Are they working? Are the strategies
having the desired impact on student learning?
•
Bring student work samples showing evidence of effectiveness of
strategies
•
Make mid-course corrections if necessary
•
Model the strategies to ensure fidelity of implementation if needed
Step 6: Monitor and Evaluate Results
Why?
To engage in a continuous improvement cycle that:
•
Identifies midcourse corrections where needed
•
Adjusts strategies to ensure fidelity of implementation
Example of Step 6 (Monitor and Evaluate Results):
Monitoring Plan Template
Cluster or School
Team
Date
Goal
Targeted Strategies
Has This Strategy Been Implemented?
Not Implemented
Partially Implemented
Implemented Fully
Has This Activity Had Impact?
Yes
No
Dates of Next Monitoring Cycle
Reasons Expected Impact Did or Did Not Occur:
Reasons Implementation Was Incomplete or Did Not Occur?
Evidence of Actual Impact on Instructional Practice and/or Student Learning:
Suggested Adjustments or Recommendations:
Reflections:
Other Relevant Information:
The DATA TEAM Meeting Cycle
Meeting 4: After-Instruction Collaboration
•
Review Post-Assessment Data
•
If the incremental goal was met, create or select
the next pre-assessment
•
If the goal was not met, repeat steps of the
Data Teams process
The DATA TEAM Meeting Cycle
The Cycle Continues
•
Meeting before instruction (same as Meeting 3)
•
Monitoring Meetings
•
Meeting after instruction (same as Meeting 4)
Additional Support:
Data Teams Refresher Courses will be offered during the
2013-14 SY. Check MyPLC for updates and to register.
Always Feel free to Contact your Regional Data Analysts
in the Department of Research & Evaluation for School Improvement:
•
•
•
•
•
East Region – Stacey L. Johnson (johnsonsl@atlanta.k12.ga.us)
West Region – Curtis L. Grier (clgrier@atlanta.k12.ga.us)
South Region – Adrienne T. Johnson (adtjohnson@atlanta.k12.ga.us)
North Region – Holly Hayes-Morrisey (hmorrisey@atlanta.k12.ga.us)
CLL – Adam Churney (achurney@atlanta.k12.ga.us)