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Realizing the Promise of the Common Core:
A Five-Step Data Teams Process
Lissa Pijanowski, Ed.D.
Associate Superintendent
Forsyth County Schools
Steve Ventura
Professional Development Associate
The Leadership and Learning Center
Journal of Staff Development
August 2012/ Data
Pijanowski Home Contact Information:
Ventura Home Contact Information:
475 White Rose Trace
1645 Granache Way
Alpharetta, GA 30005
Templeton, CA 93465
404-512-7388 cell
805-975-3853 cell
Pijanowski Professional Contact Information:
Ventura Professional Contact Information:
Forsyth County Schools
The Leadership and Learning Center
1120 Dahlonega Highway
317 Inverness Way South, Suite 150
Cumming, GA 30340
Engelwood, CO 80122
770-887-2461 ext. 202239 office
303-504-9312 Ext. 566
Word Count: 2,311 including title, text, chart, and references
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You’ve written your school improvement plan after much deliberation over state
assessment data. Your departments/grade levels have set end-of-year goals for
improvement and set forth action steps to accomplish those goals throughout the year.
So, now what? We would argue that the highest leverage action that should be included
on every school improvement plan is the implementation of Data Teams. The promise of
Common Core, or any set of rigorous performance standards, will be realized only if we
empower our teachers with a process that turns assessment results into actionable data
that drives instruction. The Data Teams process does just that.
Create a Data Mind Set:
Begin by creating a data-mind set with teachers that takes analysis of data from a
beginning of the year activity to a continuous process. Doug Reeves (2006) provides a
Leadership and Learning Matrix that allows for reflection on current practice (Table 1).
Are you losing, lucky, learning, or leading? You decide. Plot your current results on the
matrix. Now, do you know how you achieved those results (effects)? What were your
antecedents of excellence (causes)? As defined, antecedents of excellence are the
measurable indicators of leadership, teaching practices, curriculum, parent involvement,
and other factors that influence results (p.6). You must be able to make inferences about
the causes of the effects you are getting. Not only is inference making central to student
reading comprehension, it is also central to leadership decisions. Inference making means
choosing the most likely explanations for student performance data or other data trends
and patterns. When leaders and teachers analyze process data, demographic data, student
learning data, or perception data (Bernhardt, p.15) they must be able to draw
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Achievement of Results: Effect Data
Table 1: Leadership and Learning Matrix
Lucky
Leading
High results, low understanding of
antecedents
High results, high understanding of
antecedents
Replication of success unlikely
Replication of success likely
Losing
Learning
Low results, low understanding of
antecedents
Low results, high understanding of
antecedents
Replication of failure likely
Replication of success likely
Antecedents of Excellence: Cause Data
Reeves, D. (2006). The Learning Leader: How to focus school improvement for better results.
Alexandria, VA: ASCD.
conclusions or judgments based on that data. Making informed predictions about the
outcomes of potential actions supports the data teams process. More over, making
inferences and predictions about student performance data leads teachers to think deeply
about student needs. Over time and with practice, teachers can make inferences with
more validity.
Organizing Data Teams:
Professional learning communities are how we are organized as adult learners and where
Dufour and Eaker (1998) pose four critical questions - What are students supposed to
know and be able to do? How do we know when our students have learned? How do we
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respond when students haven’t learned? How do we respond when students already
know the content? The Data Teams Process is how professional educators, within
PLCs, answer those questions.
To set up Data Teams for success, school leaders must encourage teachers to prioritize
the standards that are essential for student success using the criteria of those standards
that are essential for life, school, and the state assessment. Once priority standards have
been articulated, unwrap the standards to clarify the concepts, skills, and level of rigor
required for student mastery (Ainsworth,2010). The unwrapped standards guide the
assessment process and subsequent instructional design. The next step in preparing the
data teams for success is choosing a formative assessment that all teachers will use as a
pre and post assessment of the standard(s). Mike Schmoker, in his book Focus,
emphasizes checks for understanding, or formative assessment, as critical to effective
lessons and that although the practice can be traced back to Madeline Hunter’s lesson
design from the 60s and not revolutionary to the education process, it is sometimes over
complicated and not common practice. (p.54)
Data Teams Process:
Outlined below are the five steps developed by The Leadership and Learning Center that
make collaboration an intentional activity that engages teachers and serves as an
antecedent of excellence within any school.
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Step 1: Collect and Chart Data
Start by organizing data so that there is purposeful and intentional discussion about how
students perform on assessments. Using formative assessments is the best way to
determine specific student needs. Some teachers use formative assessment to assign a
letter grade, when the purpose of these assessments is to determine student understanding
of the standards in focus. The essential purpose of assessment is summed up by W. James
Popham: “Teachers use test (results) in order to make inferences about their students’
cognitive status. Once those score-based inferences have been made, the teacher then
reaches instructional decisions based (at least in part) on those inferences. Educational
assessment revolves around inference making.” (emphasis added, 2003, p. 60). Use a
chart like the one below to disaggregate the results of the common pre-assessment (Table
2). Ask teachers to come to the Data Team meeting with their class results and chart
them to illuminate the instructional needs.
Students Needing
Intervention
% Needing Intervention
# Needing Intervention
Students Far to Go
% Far to Go
# Far to Go
Students Close to
Proficiency
% Close to Proficiency
# Close to Proficiency
% Proficient or Higher
# Proficient or Higher
# Students
Teacher
Table 2: Step 1 Template
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The Data Teams Process is also a great support for Response to Intervention as teachers
are analyzing and prioritizing needs they are essentially determining which tier a student
is in and the level of intervention needed to attain proficiency.
Step 2: Analyze and Prioritize Needs
It is difficult to select appropriate instructional strategies for individual students until we
can determine what they need first. During this part of the meeting, teachers look at four
groups of student assessment results; those students that are already proficient, those
students who are close to proficiency, those that are far, and those who need deeper levels
of intervention. Using a team created scoring guide (Table 3) the analysis moves beyond
the numbers to a review of student work. Analysis should identify specific areas of focus
that, when addressed, will take the learner to the next level. Once a determination can be
made about what students need, we can select appropriate goals for student success.
Table 3: Step 2 Template
Students Proficient or Higher
Performance Strengths
Performance Errors and Misconceptions
Students Close to Proficient
Performance Strengths
Performance Errors and Misconceptions
Inference
Inference
Inference
Inference
Students Far to Go
Performance Strengths
Inference
Performance Errors and Misconceptions
Inference
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Students Needing Intervention
Performance Strengths
Inference
Performance Errors and Misconceptions
Inference
Step 3: Set, Review, and Revise Incremental SMART Goals
SMART goals are the best way to set incremental growth targets for student success.
Rather than using static growth formulas (all students will be proficient by the year 20132014), SMART goals help teachers create realistic expectation for student growth
between pre and post assessments. High stakes accountability only motivates a small
percentage of educators. Classroom results and professional practice lead to better
overall achievement.
Table 3: Step 3 Template
SMART Goals
Try this . . .
Specific
The percentage of grade ____ students scoring proficient or higher in
Measurable
___________________ will increase from _______% to _______%
Achievable
by the end of _____________ as measured by ___________________
Relevant
administered on _______________.
Timely
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Step 4: Select Common Instructional Strategies
Without question, the selection of instructional strategies is paramount to this process.
Strategic selection of research based instructional strategies is no longer based on
whether or not teachers like the strategies; strategies are selected based on student need, a
moral imperative when adhering to the Data Team process. Additionally, we must know
the difference between a researched based instructional strategy and an “activity.”
Strategies can be instructional, organizational, or programmatic as long as they are
selected based on a prioritized student need, not teacher preference. This step in the
process is an excellent way to map out differentiation of instruction where all members of
the team can leverage their strategy toolbox and share those that are tried and true.
Pulling from the inferences made in Step 2, teachers can outline the prioritized next steps
or needs to guide strategy selection.
Table 4: Step 4 Template
Students Proficient or Higher
Prioritized Next Step: (from Step 2)
Selected Instructional
Learning
Frequency
Materials for
Strategy
Environment and Duration
Teachers and
Students
Assignments
and
Assessments
Students Close to Proficient
Prioritized Need: (from Step 2)
Selected Instructional
Learning
Frequency
Materials for
Strategy
Environment and Duration
Teachers and
Students
Assignments
and
Assessments
Students Far to Go
Prioritized Need: (from Step 2)
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Selected Instructional
Learning
Frequency
Strategy
Environment and Duration
Materials for
Teachers and
Students
Assignments
and
Assessments
Students Needing Intervention
Prioritized Need: (from Step 2)
Selected Instructional
Learning
Frequency
Materials for
Strategy
Environment and Duration
Teachers and
Students
Assignments
and
Assessments
Step 5: Determine Results Indicators
Now that your team has come to consensus on the instructional strategy, you must
determine your results indicator. A results indicator is a hypothesis, or an “if, then”
statement. Simply defined, these indicators are designed to monitor the effectiveness of
instructional strategies. Used as an interim measurement, results indicators help to
determine midcourse corrections, particularly if the strategy is not effective. Using the
template provided (Table 5), teams can outline adult behaviors, student behaviors and
what to look for in student work for each group of students.
Sample “If, Then” Statement: If we use questioning as a strategy to access prior
knowledge, then we will see students including inferences in their responses and teachers
explicitly planning opening questions.
Table 5: Step 5 Template
Students Proficient or Higher
Prioritized Next Step (from Step 2):
Selected Instructional Strategy (from Step 4):
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Adult Behaviors:
Results
Indicators:
Student Behaviors:
What to Look For in
Student Work:
Students Close to Proficient
Prioritized Need (from Step 2):
Selected Instructional Strategy (from Step 4):
Adult Behaviors:
Student Behaviors:
What to Look For in
Student Work:
Students Far to Go
Prioritized Need (from Step 2):
Results
Indicators:
Selected Instructional Strategy (from Step 4):
Results
Indicators:
Adult Behaviors:
Student Behaviors:
What to Look For in
Student Work:
Students Needing Intervention
Prioritized Need (from Step 2):
Selected Instructional Strategy (from Step 4):
Results
Indicators:
Adult Behaviors:
Student Behaviors:
What to Look For in
Student Work:
Take the 10-day Data Team Challenge:
Short term wins will motivate teams to make best practice common practice. Teachers
will immediately see the value of leveraging team members to focus instruction and
achieve results.
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1. Choose just ONE Common Core prioritized standard or important topic that will have
the greatest impact on student achievement
2. Create a five question Common Formative Assessment with your colleagues,
assessing just that one standard.
3. Administer the assessment BEFORE you teach the content so you can determine what
prerequisite skills students already possess
4. Analyze the pre-assessment results with colleagues using the five-step Data Team
process and select instructional strategies.
5. Teach the important concepts and skills within the standard for one week.
6. Administer the same assessment at the end of the instructional week.
7. Analyze the post assessment results with colleagues, use the same five-step Data
Team process.
8. Based on post assessment results, provide time for intervention (a buffer) during
week two.
9. Provide specific intervention and differentiation strategies for individual students
10. Discuss with colleagues the benefits of focused, targeted instruction and
collaboration.
Choose your next prioritized standard and continue the process!
We must develop internal capacity within schools and districts by investing in our teacher
leaders. Collaboration through Data Teams is one of the highest leverage professional
learning activities we can offer. The promise of the Common Core will be realized only
if best practice becomes common practice. Better inference making, prioritization of
student need, and focused instructional strategies, equals results for students. With a
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commitment to the Data Teams Process, schools and districts can make great things
happen for students. It is an exciting time to be in education, and no one can argue with
the ideals of the Common Core State Standards, that all students graduate from our high
schools ready for college and career. They are our future, and this is our chance to get it
right.
For more information about Data Teams training and professional resources, please visit
The Leadership and Learning Center website, www.leadandlearn.org.
Lissa Pijanowski, Ed.D. is the Associate Superintendent for Academics and
Accountability in Forsyth County Schools. You can contact her at 770-887-2461, e-mail:
[email protected].
Steve Ventura is a Professional Development Associate with The Leadership and
Learning Center. You can contact him at 805-975-3853, e-mail:
[email protected].
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References:
Ainsworth, L. (2010). Rigorous Curriculum Design. Englewood, CA: Lead + Learn
Press.
Bernhardt, V. (1998). Data Analysis for Comprehensive Schoolwide Improvement.
Larchmont, NY: Eye on Education.
Dufour, R. & Eaker, R. (1998). Professional Learning Communities at Work: Best
practices for enhancing student achievement. Bloomington, IN: Solution Tree
Press.
Popham, W. J. (2003). Test better, teach better: The instructional role of assessment.
Alexandria, VA: ASCD.
Reeves, D. (2006). The Learning Leader: How to focus school improvement for better
results. Alexandria, VA: ASCD.
Schmoker, M. (2011). Focus: Elevating the essentials to radically improve student
learning. Alexandria, VA: ASCD.
Resources:
The Leadership and Learning Center. (2010). Decision Making for Results and Data
Teams (3rd edition). Englewood, CO: Lead + Learn Press.
www.LeadandLearn.com