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Transcript of Leadership Academy “Data Analysis” June 2010. Some thoughts about data analysis… We have moved...
![Page 1: Leadership Academy “Data Analysis” June 2010. Some thoughts about data analysis… We have moved from a system where hunches and “cardiac data” were followed,](https://reader035.fdocuments.in/reader035/viewer/2022070414/5697c00f1a28abf838cca819/html5/thumbnails/1.jpg)
Leadership Academy“Data Analysis”
June 2010
![Page 2: Leadership Academy “Data Analysis” June 2010. Some thoughts about data analysis… We have moved from a system where hunches and “cardiac data” were followed,](https://reader035.fdocuments.in/reader035/viewer/2022070414/5697c00f1a28abf838cca819/html5/thumbnails/2.jpg)
Some thoughts about data analysis…
We have moved from a system where hunches and “cardiac data” were followed, to a system that is data driven.
We have moved from assuming good things are happening to insisting good things are happening and proving this is so.
Teaching is an art……and becoming a science.
![Page 3: Leadership Academy “Data Analysis” June 2010. Some thoughts about data analysis… We have moved from a system where hunches and “cardiac data” were followed,](https://reader035.fdocuments.in/reader035/viewer/2022070414/5697c00f1a28abf838cca819/html5/thumbnails/3.jpg)
Learning Outcomes
• Participants will identify:– Key ideas about effective data-based decision
making– Four types of data– Challenges within our district ITBS/ITED results– Findings & results from last year’s Leadership
Academy– Effective strategies to help improve student
achievement– Ideas to include within our revised Strategic Plan
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8 Key Points
1.Data provides insight
2.Data are nothing without analysis.
3.Interpret graphs accurately
4.Improvement means more success, less failure, and less unwanted variation!
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5.Real-time, frequent data are necessary to monitor improvement.
6.Data must be accessible to users.
7.To improve results, work on both product and processes.
8.Take action!
8 Key Points (cont.)
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Leaders Ask Good Questions
What does the graph look like?
What patterns or trends do the data show?
Special or common cause?
Over-reacting or under-reacting?
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“Is this the complete picture?”
Are there other assessments we need to look at?
What other data might we need to confirm, support and or clarify what we are seeing now?
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How do I know if what I’m seeing is real? Try to use multiple data sources. Triangulation occurs if three different data sources all indicate the same thing.
ITBS scores
Unit test scores
District test score
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Why do some people dislike (fear?) data analysis?
Data
Share your thoughts with someone at your
table?
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Why do some people dislike (fear?) data analysis?
Data analysis… unlocks the door to the
traditionally private domain of the classroom,
inevitably results in a mandate for change, and
increases pressure for accountability, especially if results are poor.
Data
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What did we learn from last year’s Leadership Academy?
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Global Positioning System (GPS)
Mapping the Way
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Few credits earned
Proficient math scores
Reading scores were low.
Did not attend
Estimate time of arrival…
Commencement Day!
12th11th10th9th8th7th6th5th4th3rd2nd1stKPre K
Write data in each arrow indicating your student's successes and/or challenges at each grade level.
Student GPS Timeline
Student dropped out
Start of poor attendance
Good attendance
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Data DrillsDropouts
Struggling Students
Walkthoughs
Perception Surveys
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Four Types of Data
Classroom Data ______________
_____
______________
______________
_____
______________
_____
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Findings & Results of Last Year’s Leadership Academy
1. Struggling students & dropouts are a K-12 concern.-“Intervention Record” piloted in four elementary schools.
-Pinnacle Analytics set up to red flag struggling students & potential dropouts
2. Our data is inconsistent, poorly organized, and not effectively used to guide our instruction.
-Pinnacle Analytics has been designed to:
*Manage, organize & store our data,
*Visually help us correlate & analyze our data, and
*Help us work smarter, not harder.
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Informing Our Strategic Plan
• Last year’s Leadership Academy findings were incorporated into our Strategic Plan.
• This year’s Leadership Academy findings will be as well.
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Strategic Plan GoalsAchievement
Perception
Demographic
Classroom
NEEDS, GOAL(S), FOR STRATEGIC PLAN
Throughout the Leadership Academy, record relevant data along with corresponding needs and goals of our district that you believe
should be included in our next revision of the Strategic Plan.
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Student Achievement Data
1. What is our current reality?
2. Is it “good enough”?
3. What are we doing to cause this?
4. What will we do to maintain or
improve?
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Initial 2009-2010 ITBS/ITED Results
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Reading Comprehension Grades 3-5 FAY Students
0
20
40
60
80
100
% Pr
ofici
ent
FAY 66.7 67.5 68.9 64.9 68.3 70.3
Trajecory 69.4 69.4 69.4 75.5 75.5 75.5 81.6 87.8 93.9 100
2004 2005 2006 2007 2008 2009 2010 2011 2012 2013
Trajectory
District FAY Score Trend line
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Reading Comprehension Grades 6-8 FAY Students
0
20
40
60
80
100
% Pr
ofici
ent
Fay 58 60.2 62 61 62 63.7
Trajectory 64.4 64.4 64.4 71.5 71.5 71.5 78.7 85.8 92.9 100
2004 2005 2006 2007 2008 2009 2010 2011 2012 2013
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Reading Comprehension Grade 11 FAY Students
0
20
40
60
80
100
% Pr
ofici
ent
FAY 61.8 61.7 68.0 67.5 68.4 68.5 74.6
Trajectory 69.0 74.2 74.2 74.2 79.3 79.3 79.3 84.5 89.7 94.8 100
2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013
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Math Total Grades 3-5 FAY Students
0
20
40
60
80
100
% Pr
ofici
ent
FAY 66.3 66.9 69.1 66.4 68.3 70
Trajectory 68.8 68.8 68.8 75.1 75.1 75.1 81.3 87.5 93.8 100
2004 2005 2006 2007 2008 2009 2010 2011 2012 2013
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Math Total Grades 6-8 FAY Students
0
20
40
60
80
100
% Pr
ofici
ent
FAY 61 62.4 64.3 63 63.7 65
Trajectory 65.3 65.3 65.3 72.3 72.3 72.3 79.2 86.1 93.1 100
2004 2005 2006 2007 2008 2009 2010 2011 2012 2013
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Math Total Grade 11 FAY Students
0
20
40
60
80
100
% Pr
ofici
ent
FAY 64.0 67.7 63.8 71.2 66.6 68.6 71.5
Trajectory 69.0 74.2 74.2 74.2 79.3 79.3 79.3 84.5 89.7 94.8 100
2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013
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Science Grades 3-5 FAY Students
0
20
40
60
80
100
% Pr
ofici
ent
FAY 69.7 73.2 74 72.9 73.1 75.9
2004 2005 2006 2007 2008 2009
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Science Grades 6-8 FAY Students
0
20
40
60
80
100
% Pr
ofici
ent
FAY 68.9 69.3 74.5 72.9 73 76.6
2004 2005 2006 2007 2008 2009
![Page 29: Leadership Academy “Data Analysis” June 2010. Some thoughts about data analysis… We have moved from a system where hunches and “cardiac data” were followed,](https://reader035.fdocuments.in/reader035/viewer/2022070414/5697c00f1a28abf838cca819/html5/thumbnails/29.jpg)
Science Grade 11 FAY Students
0
20
40
60
80
100
% Pr
ofici
ent
FAY 61.8 66.8 66.4 73.8 73.6 77 77.8
2003 2004 2005 2006 2007 2008 2009
![Page 30: Leadership Academy “Data Analysis” June 2010. Some thoughts about data analysis… We have moved from a system where hunches and “cardiac data” were followed,](https://reader035.fdocuments.in/reader035/viewer/2022070414/5697c00f1a28abf838cca819/html5/thumbnails/30.jpg)
Reading Comprehension Grades 3-5 FAY Students
0
20
40
60
80
100
% Pr
ofici
ent
FAY 66.7 67.5 68.9 64.9 68.3 70.3
Trajecory 69.4 69.4 69.4 75.5 75.5 75.5 81.6 87.8 93.9 100
2004 2005 2006 2007 2008 2009 2010 2011 2012 2013
Trajectory
District FAY Score Trend line
1. What is our current reality?
2. Is it “good enough”?
3. What are we doing to cause this?
4. What will we do to maintain or
improve?
![Page 31: Leadership Academy “Data Analysis” June 2010. Some thoughts about data analysis… We have moved from a system where hunches and “cardiac data” were followed,](https://reader035.fdocuments.in/reader035/viewer/2022070414/5697c00f1a28abf838cca819/html5/thumbnails/31.jpg)
MathTotal Grades 6-8 FAY Students
0
10
20
30
40
50
60
70
80
90
100
% Pr
ofici
ent
2006 72.1 51.1 73.8 46.2 47.3
2007 71.1 50.4 64 40.9 48.3
2008 71.6 51.8 64.2 42.6 51.5
2009 73.3 58.2 65.9 47.6 53.1
White Native Am. Asian African Am Hispanic
% Proficient Trajectory
![Page 32: Leadership Academy “Data Analysis” June 2010. Some thoughts about data analysis… We have moved from a system where hunches and “cardiac data” were followed,](https://reader035.fdocuments.in/reader035/viewer/2022070414/5697c00f1a28abf838cca819/html5/thumbnails/32.jpg)
Reading Comprehension Grades 3-5 FAY Students
0
10
20
30
40
50
60
70
80
90
100
% P
rofic
ient
2006 68.9 58.9 33.8 50.1
2007 64.9 54.4 28.1 46.9
2008 68.3 60.6 33.8 51.7
2009 70.3 62.3 34.9 52.6
FAY Students Low SES IEP ELL
% Proficient Trajectory
1. What is our current reality?
2. Is it “good enough”?
3. What are we doing to cause this?
4. What will we do to maintain or
improve?
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Full Academic Year (FAY) StudentsCohort Group from 3rd Grade to 11th Grade
40
60
80
100
% P
rofic
ient
Reading 64 69.8 69.3 55.3 63.7 63.3 56 63.2 74.6
Math 54.7 66.2 62.4 56.8 63.1 64.8 66 59.4 71.5
Science 64.9 76.6 72.6 65.8 70.1 77.4 75.9 69.8 77.8
3rd 4th 5th 6th 7th 8th 9th 10th 11th
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FINAL District AYP Results of 2008-09 Iowa Tests
Elementary
MathElementary
ReadingMiddle Math
Middle Reading
High MathHigh
Reading
All MissedMet - Safe
HarborMissed Missed Missed Missed
Low SES Missed Missed Missed Missed Missed Missed
IEP MissedMet - Safe
HarborMissed Missed
Met - Safe Harbor
Missed
ELL MissedMet - Safe
HarborMet - Safe
HarborMissed
Met - Safe Harbor
Missed
African American Met- GHS Missed Missed Met - GSHMet - Safe
HarborMet - Safe
Harbor
Asian MissedMet - Safe
HarborMet
Triennium Met - Trien Met
Met Triennium
Hispanic MissedMet - Safe
HarborMissed Missed Missed Missed
Native American Missed Missed Missed MissedMet - Safe
HarborMissed
White Met Met Met - Trien Met - Trien Met - Trien Missed
“Final” District AYP Results of 2008-09 Iowa Tests
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Reading Math Partic Reading Math Partic Reading Math Partic
District delay 2 delay 2 DINA 3 DINA 3 DINA 4 DINA 4
East High watch SINA 1 SINA 1 SINA 2 SINA 2 SINA 3
North High SINA 2 SINA 3 watch SINA 3 SINA 4 SINA 1 SINA 4 SINA 5 delay 1
West High SINA 3 SINA 1 SINA 4 SINA 2 watch SINA 5 SINA 3
East Middle delay 2 watch SINA 3 SINA 1 SINA 4
North Middle watch watch SINA 1 SINA 1
West Middle SINA 3 delay 2 SINA 4 SINA 3 SINA 5 SINA 4
Central Campus delay 2 delay 2 watch SINA 3 SINA 3 SINA 1 SINA 4 SINA 4 SINA 2
Bryant watch watch SINA 1
ClarkCrescent Park watch
Emerson watch watch
Everett watch watch SINA 1 SINA 1
HuntIrving watch watch SINA 1
JoyLeeds watch watch
LincolnLongfellow watch SINA 1
Riverside watch watch SINA 1
Roosevelt watch watch SINA 1
Smith watch watch SINA 1 SINA 1
SunnysideUnity watch
WashingtonWhittier watch watch SINA 1
# of watch 1 3 2 12 10 2
# of SINA 3 5 6 1 11 14 1
# of delay 1 3 1
Disrict's & Schools' AYP Status Based Upon Previous Year's ITBS/ITED Results
2007-08 2008-09 2009-10
1. What is our current reality?
2. Is it “good enough”?
3. What are we doing to cause this?
4. What will we do to maintain or
improve?
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We are moving to spring ITBS/ITED testing next year.
How might this change help our current reality?
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Since we will continue to be evaluated by the
ITBS/ITED annual “snapshot”, how can we use our transition
to spring testing to help us better prepare
for the tests?
![Page 39: Leadership Academy “Data Analysis” June 2010. Some thoughts about data analysis… We have moved from a system where hunches and “cardiac data” were followed,](https://reader035.fdocuments.in/reader035/viewer/2022070414/5697c00f1a28abf838cca819/html5/thumbnails/39.jpg)
How can we provide a better picture of learning over a particular school year using the spring ITBS/ITED?
How can we better address our dip in transition year scores?
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How can we better address the concerns of summer learning loss?
Can we avoid having to estimate the effects of one grade level from another since we no long would take the tests only three months into the school year?
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1. How might this change help our current reality?
2. How can we use our transition to spring testing to better prepare for the tests?
3. How can we provide a better picture of learning over a particular school year?
4. How can we better address our dip in transition year scores?
5. How can we better address the concerns of summer learning loss?
6. Can we avoid having to estimate the effects of one grade level from another?
Moving to Spring ITBS/ITED
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Will simply changing to spring testing with four additional months to prepare, automatically improve our scores?
What about norms?
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Norms compare a student’s raw score, the number of problems the student got correct, with the scores from other students who took the same test at approximately the same time of the school year.
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How much a student “knows” is inferred from
their standing or rank within that comparison or
norm group.
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ITBS & ITEDNumber of Correct Items Required for Proficiency
Form
Code
ContentProficiency
Fall Midyear
Spring
# of items
3rd Grade-- Level 9
A RC Reading Comprehension
15 17 19 37
M1 Math Concepts & Estimation
16 17 19 31
M2 Math P. S*. & Data Interpret.
10 12 13 22
SC Science 13 14 15 30
B RC Reading Comprehension
17 19 21 37
M1 Math Concepts & Estimation
15 16 18 31
M2 Math P. S. & Data Interpret.
11 12 14 22
SC Science 13 14 16 30
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Simply changing to spring testing with four additional months to prepare, will not automatically improve our scores.
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We may even experience a dip in scores?
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Spring ITBS / ITED Testing
• We are confident
• Improved curriculum, instruction & assessments
• Increased ownership and motivation
• Improved student achievement and proficiency on the ITBS/ITED.
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Spring ITBS / ITED Testing?
• Beginning with the 2010-11 school year, we will be moving to spring testing.
• Consensus from all stakeholder groups
• Board acknowledgement and support
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Preparing for Spring Testing
• March 14 – April 1• Results will arrive mid-May • District Assessment Calendar Adjustments
(ELDA in Feb, DRA-2 to 4th qrt.)• Improve curriculum, instruction & assessment• Increase formative assessment & differentiation• Use Pinnacle to analyze and triangulate data
throughout the year• Increase ownership and motivation• Learn from each other
![Page 51: Leadership Academy “Data Analysis” June 2010. Some thoughts about data analysis… We have moved from a system where hunches and “cardiac data” were followed,](https://reader035.fdocuments.in/reader035/viewer/2022070414/5697c00f1a28abf838cca819/html5/thumbnails/51.jpg)
What other achievement data should we be looking at?