school improvement planning leadership council and principal meetings september/october 2010
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School Improvement PlanningLeadership Council and Principal MeetingsSeptember/October 2010
AgendaSchool Improvement Plan with Populated DataSchool Improvement Planning ProcessExample Plans and Plan CriteriaPerformance FrameworksData AnalysisRoot Cause IdentificationTarget SettingAction Planning
Colorado Unified Planning Template for SchoolsMajor Sections:
Summary Information About the School
Improvement Plan Information
Narrative on Data Analysis and Root Cause Identification
School Improvement Planning Process
Timeline for School Accreditation and Plan SubmissionDistrict Accountability Handbook p. 54
SVVSD Timeline for School Accreditation and Plan SubmissionTurnaround, Priority Improvement, Title 1 on Corrective ActionDec. 1 turn into Area Assistant Superintendent for review and feedbackJan. 7 with revisions completed turn into Area Assistant Superintendent March 30th submit revisions from State Review Panel feedback to CDE (not Title 1 schools)Other SchoolsMarch 1st to Area Assistant SuperintendentApril 8th with revisions completed turn into Area Assistant Superintendent
All Plans must be reviewed by District Accountability/Accreditation Committee before submitting to CDE
Planning TerminologyAppendix A: District Accountability Handbook, p. 23
Review each of the terms listedTerms:Performance IndicatorMeasureMetricRoot CauseMajor Improvement StrategyAction StepInterim MeasureImplementation Benchmark
School Improvement Plan (SIP)Section I: Summary InformationExamine section 1Mark sections with a that you need more clarification onDiscuss with a partnerWhat data surprised you?What data are you most proud of?At initial glance, what is an area of weakness?Questions
School Improvement Plan (SIP)Section II: Improvement Plan InformationAdditional Information about the School Most schools will not answer yes to any If you are not sure ask(usually Regina)
Improvement Plan InformationState Accountability (most schools)Plus Title 1A (some schools)If not sure ask(Regina)
Section III. Narrative on Data Analysis and Root Cause Identification
Step 1 Gather and Organize Relevant Data
Step 2 Analyze Trends in the Data and Identify Priority Needs
Step 3 Root Cause Analysis
Step 4 Create the Data Narrative
Example Plans and Criteria
High SchoolDiscuss with a partner:How is this the same as previous goal setting in our District?How is it different?
Performance Indicators, Measures, Metrics and Example Targets
Please read a couple of the examples.
Section III, Step 1:Gather and Organize DataRead Step One on p. 4 of the plan
Make a list of data your school has available for school improvement planning
What questions can your data answer?
Gather and Organize DataRequired reports: www.schoolview.orgSchool Performance FrameworkGrowth Summary ReportAYP SummariesPost Secondary Readiness DataRecommended: the use of more sources of data (elementary should definitely consider primary data like PALS)Must consider at least three years of data
Data Sources in our DistrictSchoolview.org reports listed in previous slide
Alpine Achievement Colorado Assessments - CSAP, CSAPA, CO-ACT, Colorado Growth Model, CELA, AYP ReportData Warehouse PALS, AP, DIBELS, and many more (soon to come Galileo, Theme Tests, SRI)Plans Literacy, RtI, ALP (soon 504)
Section III, Step 2 Analyze Trends in the Data and Identify Priority Needs
Data Driven Dialogue
Step 1 Predict (Activate & Engage)Step 2 Explore (Explore & Discover)Step 3 Explain (Organize & Integrate)Step 4 Take Action
Step One: Predict (Data Driven Dialogue)
The purpose: To activate interest and bring out our prior knowledge, preconceptions, and assumptions regarding the data with which we are about to work. Prediction allows dialogue participants to share the frame of reference through which they view the world and lays the foundation for collaborative inquiry.
The steps include:
Clarify the questions that can be answered by the dataMake predictions about dataIdentify assumptions behind each predictionPrediction Sentence Starters:I predict . . .I expect to see . . .I anticipate . . .
Assumption Questions:Why did I make that prediction?What is the thinking behind my prediction?What do I know that leads me to make that prediction?What experiences do I have that are consistent with my prediction?
Step One (Chart Paper) (Data Driven Dialogue) PredictionsAssumptions
Step One: Predict Hints(Data Driven Dialogue)Predictions may go fairly quickly at this point because staff members have already seen some of the dataDevelop assumptions concurrentlyGroups do not need to agree upon theseGive groups a mostly blank data table to help with predictions (so they have some idea of what data they are predicting)
1000OverallGrade 4Grade 5BoysGirlsFRLNonFRLELLnonELLIEPnonIEPCSAP Growth Percentile
Step Two: Explore (Data Driven Dialogue)
The purpose: Generate priority observations or fact statements about the data that reflect the best thinking of the group.
The steps include:
Interact with the data (highlighting, creating graphical representations, reorganizing)Look for patterns, trends, things that pop outBrainstorm a list of facts (observations)Prioritize observationsTurn observations into priority needs
Avoid: Statements that use the word because or that attempt to identify the causes of data trends.
Sentence starters:It appears . . . I see that . . . It seems . . .The data shows . . .
Step 2: Explore - Hints (Data Driven Dialogue)It is very important to take the time to really explore the dataremind people to not jump to because or action steps and to really look at what the data is telling themGive people one piece of data at a timeRefine Observations:In math 58% of 5th graders were proficient or advanced compared to 52% of 4th graders.The ELL population increased from 10% last year to 30% this year.
UIP - Section III, Step 2:Analyze Trends in the Data and Identify Priority Needs
Read this section on p. 4
Identify areas of strengthIdentify areas of needPrioritize needs
***the first two columns (trends and priority needs) of the data analysis worksheet on p. 5 can now be filled out
How good is good enough?State Performance Indicators:School and District Performance FrameworksState expectations defined for each performance indicator
Federal Performance Indicators:Annual AYP TargetsSee, AYP Proficiency Targets and Safe Harbor
Trends and Priority NeedsTrends must include at least 3 years of data.
Priority needs must be identified for at least every performance indicator for which school performance did not meet state or federal expectations:AchievementGrowthGrowth GapsPost Secondary/Workforce Readiness)
Step Three: Explain (Data Driven Dialogue)The Purpose: Generate theories of causation, keeping multiple voices in the dialogue. Deepen thinking to get to the best explanations and identify additional data to use to validate the best theories.
The steps include:Generate questions about observations Brainstorm explanationsCategorize/classify brainstormed explanationsNarrow (based on criteria)PrioritizeGet to root causesValidate with other data
Guiding Questions:What explains our observations about out data? What might have caused the patterns we see in the data?Is this our best thinking? How can we narrow our explanations?What additional data sources will we explore to validate our explanation?
Step 3: Explain Hints (Data Driven Dialogue)
Help groups stay open to multiple interpretations of whydevelop multiple theories of causation
Separate the generation of theories of causation from theories of action (do not go to action steps in this step)
UIP Section III, Step 3 Root Cause Analysis
A cause is a root cause if:The problem would not have occurred if the cause had not been presentThe problem will not reoccur if the cause is dissolvedCorrection of the cause will not lead to the same or similar problems***the school should have control over the root cause
Steps in Root Cause AnalysisGenerating explanations (brainstorm)Categorize/classify explanationsNarrow (eliminate explanations over which you have no control)PrioritizeGet to root causeValidate with other data
Non-examples of Root CauseStudent attributes (poverty level)Student motivation
Brainstorm a few ideas with your table team of explanations that might appear to be root causes but dont qualify
Root Cause ExamplesThe school does not provide additional support/interventions for students performing at the unsatisfactory level Lack of clear expectations for tier 1 instruction in math.Lack of intervention tools and strategies for math. Limited English language development.Inconsistency in instruction in the area of language development.Low expectations for all subgroups. Low expectations for IEP students.
Five Whys (Explanation)Why?Because:
5 Why ExampleELL students are not engaged in learning in the core content classes.
Why? BecauseCore curriculum is not accessible to ELL students.
Why? BecauseELL students English skills are not proficient enough to participate in discussions, ask questions, and comp