Groton Data Day Accountability, Performance, and Balanced Assessments Facilitated by: Neal Capone...
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![Page 1: Groton Data Day Accountability, Performance, and Balanced Assessments Facilitated by: Neal Capone District Data Coordinator CNYRIC.](https://reader035.fdocuments.net/reader035/viewer/2022062421/56649e605503460f94b5a6a0/html5/thumbnails/1.jpg)
Groton Data DayAccountability, Performance, and
Balanced Assessments
Facilitated by:
Neal CaponeDistrict Data Coordinator
CNYRIC
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Agenda
• Grounding – Spring Synectic• Data Literacy – Accountability and Assessment• 3-8 ELA/Math Collaborative Learning Cycle
– Score Trend Comparison – Cohort Trend and Subgroup Performance
• Balanced Assessment– Rick Stiggens– Self-Evaluation
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The Region Serviced by the CNYRIC
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Data Flow
SIS (Student Management System)
PD Data System
IEP Direct
NutriKids/Transfinder
Level 2 Repository (SED)
Data Warehouse (Level 1)
Level 1 ContainerCOGNOS
DataMentor
nySTART
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Synectic
What are some popular Spring Activities?
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SYNECTIC
Data Analysis is like … because ...
Syn (bring together) Ectic (diverse elements)
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Grounding Exercise
• Name• Position• Share your Synectic
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“Using data effectively does not mean getting good at crunching numbers. It
means getting good at working together to gain insights from
student-assessment results and to use the insights to improve instruction.”
- Kathryn Boudett, Elizabeth City, & Richard Murnane, “When 19 Heads Are Better Than One,”
Education Week, December 7, 2005.
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Word Splash
Work with a partner to define as many terms as you can on the Word Splash
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Data Warehouse
SIRS
NYSSIS
Continuous Enrollment
Performance IndexAYP
AMO
Effective AMO
NYSAA
Participation Rate
Accountability Subgroups
Safe Harbor
BEDS
NYSESLAT
Accountability Cohort
AVR
Graduation Cohort
COGNOS
Diff
eren
tiate
d A
ccou
ntab
ility
Triangulatin
g Data
Word Splash
Sampling Principle
Summative AssessmentForm
ative Assessment
Scale Score --- Raw
Score
Standards-Referenced Test
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Calculation of the Performance Index (PI)
Elementary-Middle Levels:
PI = [(number of continuously enrolled tested students scoring at Levels 2, 3, and 4 + the number scoring at Levels 3 and 4) ÷ number of continuously enrolled tested students] X 100
Secondary Level:
PI = [(number of cohort members scoring at Levels 2, 3, and 4 + the number scoring at Levels 3 and 4) ÷ number of cohort members] X 100
A Performance Index (PI) is a value from 0 to 200 that is assigned to an accountability group, indicating how that group performed on a required State test (or approved alternative) in English language arts, mathematics, or science. PIs are determined using the following equations:
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Level 1: 5 students
Level 2: 15 students
Level 3: 45 students
Level 4: 10 students
PI = (15+45+10) + (45 + 10)
75
PI = 167
X 100
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Measure/Purpose Cohort Used Standard/AMO Subgroup Accountability
Performance
All grade 3-8 students) or designated ungraded students) reported in the repository as continuously enrolled (one-year continuous enrollment = enrolled BEDS day through assessment dates)
English: PI of 167Math:PI of 152Science;PI of 100
30 or more students for ELA or Math
Participation Rate
All grade 3-8 students (or designated ungraded students) reported in the repository as enrolled during assessment administration and make-up dates
ELA and Math: 95%Science: 80% for “all students”
40 or more students for ELA or Math
2010-2011 Elementary/Middle Level Accountability
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2010-2011 High School Accountability
Measure/Purpose Cohort Used Standard/AMO Subgroup Accountability
English and Math Performance
2007 Accountability Cohort (one-year continuous enrollment in fourth year of HS = enrolled BEDS day through June 30, 2011)
English: PI of 183Math:PI of 180
30 or more students for ELA or Math
English and Math Participation
All students reported in State Repository as enrolled in grade 12 on June 30, 2011 and students who graduated between July 1, 2010 and June 30, 2011
95% 40 or more students
Graduation Rate
2006 Graduation-Rate Cohort (five months’ enrollment) including transfers to GED
80% for “all students”
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An Effective AMO is the lowest PI that an accountability group of a given size can achieve in a subject for the group’s PI not to be considered significantly different from the AMO for that subject. If an accountability group's PI equals or exceeds the Effective AMO, the group is considered to have made AYP.
Effective AMOs
Further information about confidence intervals and Effective AMOs is available at:http://www.emsc.nysed.gov/irts/school-accountability/confidence-intervals.htm
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2010–11 Safe Harbor Calculation for ELA and Math
Safe Harbor is an alternate means to demonstrate AYP for accountability groups whose PI is less than their Effective AMO. The Safe Harbor Target calculation for ELA and Math for 2010-11 using the 2009-10 PI is:
Safe Harbor Target = {2009-10 PI} + [(200 – {2009-10PI}) 0.10]*
For a group to make safe harbor in English or math, it must meet its Safe Harbor Target and also meet the science (at the elementary/middle level) or graduation rate (at the secondary level) qualification for safe harbor. To qualify at the elementary/middle level, the group must make the State Standard or its Progress Target in science in grades 4 and/or 8. At the secondary level, it must make the State Standard or its Progress Target for graduation rate.
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21
Phase
Diagnostic
Differentiated Accountability Model
Category
CORRECTIVE ACTIONIMPROVEMENT RESTRUCTURING
CURRICULUM AUDITSCHOOL QUALITY REVIEW ASSIGNMENT OFJoint Intervention Team and
Distinguished Educator
FOCUSED COMPBASIC FOCUSED COMPREHENSIVE FOCUSED COMP
SURR
Intensity of Intervention
FAILED AYP 2 YEARS
FAILED AYP 2 YEARS
Plan/Intervention CORRECTIVE ACTION PLAN & IMPLEMENTATION
OF CURRICULUM AUDIT
IMPROVEMENT PLANCREATE AND IMPLEMENT
External personnel to revise and assist school implement the most
rigorous plan or, as necessary,PHASE-OUT /CLOSURE
Oversight& Support
SED provides TA to districts: sustaining greater latitude and more responsibility for
addressing schools
SED empowers districts: gives them the support and assistance necessary to take primary
responsibility for developing and implementing improvement strategies
SED & its agents work in direct partnership with
the district
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Data Warehouse
SIRS
NYSSIS
Continuous Enrollment
Performance IndexAYP
AMO
Effective AMO
NYSAA
Participation Rate
Accountability Subgroups
Safe Harbor
BEDS
NYSESLAT
Accountability Cohort
AVR
Graduation Cohort
COGNOS
Diff
eren
tiate
d A
ccou
ntab
ility
Triangulatin
g Data
Word Splash
Sampling Principle
Summative AssessmentForm
ative Assessment
Scale Score --- Raw
Score
Standards-Referenced Test
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District Report Card
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Managing
Modeling
Mediating
Monitoring
Data-Driven DialogueThe Collaborative Learning Cycle
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"He uses statistics as a drunken man uses lamp-posts...
Andrew Lang (1844-1912)
In reference to an individual who misuses data:
…for support rather than illumination."
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Data-Driven DialogueThe Collaborative Learning Cycle
Activating and Engaging
Managing
Modeling
Mediating
Monitoring
• What are some predictions we are making?• With what assumptions are we entering? • What are some questions we are asking?• What are some possibilities for learning that this experience presents to us?
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What is a prediction you made?
What might be some assumptions that influenced your prediction?
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Data-Driven DialogueThe Collaborative Learning Cycle
Managing
Modeling
Mediating
Monitoring
Exploring and Discovering
• What important points seem to “pop out”?• What are some patterns, categories, or
trends that are emerging?• What seems to be surprising or
unexpected?• What are some things we have not yet
explored?
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Principles of Data-Driven Dialogue
• Importance of Predictions
• Conscious Curiosity
• Purposeful Uncertainty
• Visually Vibrant Information
• Third Point
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Data-Driven DialogueThe Collaborative Learning Cycle
Managing
Modeling
Mediating
Monitoring
Exploring and Discovering
• What important points seem to “pop out”?
• What are some patterns, categories, or trends that are emerging?
• What seems to be surprising or unexpected?
• What are some things we have not yet explored?
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Data-Driven DialogueThe Collaborative Learning Cycle
Managing
Modeling
Mediating
MonitoringOrganizing and Integrating
• What inferences/ explanations/ conclusions might we draw?
• What additional data sources might we explore to verify our explanations?
--------------------------------------------------• What are some solutions we might
explore . . . ?• What data will we need to collect to
guide implementation?
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“My team has created a very innovative solution,but we’re still looking for a problem to go with it.”
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Curriculum
Instructional methods and
materials
Teacher knowledge and skills
Student readiness
Infrastructure
Causal Arenas
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Theories of Causation
Observation: record three possible theories of causation re: your observation
1.
2.
3.
Circle one theory. In this space, record at least three sources of data you could use to confirm this theory.
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Data-Driven DialogueThe Collaborative Learning Cycle
Managing
Modeling
Mediating
Monitoring
Organizing and Integrating
• What inferences/ explanations/ conclusions might we draw?
• What additional data sources might we explore to verify our explanations?
--------------------------------------------------• What are some solutions we might
explore . . . ?• What data will we need to collect to
guide implementation?
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Time to Share
• Share ONE observation
• Share ONE theory of causation
• Share additional data sources that you would want to explore to confirm or disprove your theory
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Balanced Assessment