School Improvement Planning Leadership Council 9/2/10.

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Presentation transcript:

School Improvement Planning Leadership Council 9/2/10

Agenda School Improvement Plan with Populated Data School Improvement Planning Process Example Plans and Plan Criteria Performance Frameworks Data Analysis Root Cause Identification

Colorado Unified Planning Template for Schools Major Sections: I.Summary Information About the School II.Improvement Plan Information III.Narrative on Data Analysis and Root Cause Identification IV.Action Plan

School Improvement Planning Process

Timeline for School Accreditation and Plan Submission District Accountability Handbook p. 54

SVVSD Timeline for School Accreditation and Plan Submission Turnaround, Priority Improvement, Title 1 on Corrective Action –Dec. 1 – turn into Area Assistant Superintendent for review and feedback –Jan. 7 – with revisions completed turn into Area Assistant Superintendent –March 30 th – submit revisions from State Review Panel feedback to CDE (not Title 1 schools) Other Schools –March 1 st – to Area Assistant Superintendent –April 8 th – with revisions completed turn into Area Assistant Superintendent  All Plans must be reviewed by District Accountability/Accreditation Committee before submitting to CDE

Planning Terminology Appendix A: District Accountability Handbook, p. 23 Review each of the terms listed Terms: –Performance Indicator –Measure –Metric –Root Cause –Major Improvement Strategy –Action Step –Interim Measure –Implementation Benchmark

School Improvement Plan (SIP) Section I: Summary Information –Examine section 1 –Mark sections with a that you need more clarification on –Discuss with a partner… What 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 Information –Additional Information about the School Most schools will not answer yes to any If you are not sure ask…(usually Regina) –Improvement Plan Information State 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 Elementary/Middle School High School Discuss 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. Plan Criteria

Section III, Step 1: Gather and Organize Data Read 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 Data Required reports: –School Performance Framework –Growth Summary Report –AYP Summaries –Post Secondary Readiness Data Recommended: 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 District Schoolview.org – reports listed in previous slide Alpine Achievement – –Colorado Assessments - CSAP, CSAPA, CO-ACT, Colorado Growth Model, CELA, AYP Report –Data Warehouse – PALS, AP, DIBELS, and many more (soon to come – Galileo, Theme Tests, SRI) –Plans – Literacy, RtI, ALP (soon – 504) Infinite Campus

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 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: 1.Clarify the questions that can be answered by the data 2.Make predictions about data 3.Identify assumptions behind each prediction Prediction 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) PredictionsAssumptions

Step One: Predict - Hints Predictions may go fairly quickly at this point because staff members have already seen some of the data Develop assumptions concurrently Groups do not need to agree upon these Give groups a mostly blank data table to help with predictions (so they have some idea of what data they are predicting)

100 0 OverallGrade 4Grade 5BoysGirlsFRLNonFRLELLnonELLIEPnonIEP CSAP Growth Percentile

Step Two: Explore The purpose: Generate priority observations or fact statements about the data that reflect the best thinking of the group. The steps include: 1.Interact with the data (highlighting, creating graphical representations, reorganizing) 2.Look for patterns, trends, things that pop out 3.Brainstorm a list of facts (observations) 4.Prioritize observations 5.Turn 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 It is very important to take the time to really explore the data…remind people to not jump to “because” or “action steps” and to really look at what the data is telling them Give people one piece of data at a time Refine Observations: –In math 58% of 5 th graders were proficient or advanced compared to 52% of 4 th 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 strength Identify areas of need Prioritize 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 Frameworks –State expectations defined for each performance indicator Federal Performance Indicators: –Annual AYP Targets –See, “AYP Proficiency Targets and Safe Harbor”

Trends and Priority Needs Trends 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.

Step Three: Explain 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: 1.Generate questions about observations 2.Brainstorm explanations 3.Categorize/classify brainstormed explanations 4.Narrow (based on criteria) 5.Prioritize 6.Get to root causes 7.Validate 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 Help groups stay open to multiple interpretations of why…develop 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: 1.The problem would not have occurred if the cause had not been present 2.The problem will not reoccur if the cause is dissolved 3.Correction 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 Analysis 1.Generating explanations (brainstorm) 2.Categorize/classify explanations 3.Narrow (eliminate explanations over which you have no control) 4.Prioritize 5.Get to root cause 6.Validate with other data

Non-examples of Root Cause Student attributes (poverty level) Student motivation Brainstorm a few ideas with your table team of explanations that might appear to be root causes but don’t qualify

Root Cause Examples The 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 Why’s (Explanation) 1.Why? Because: 2.Why? Because: 3.Why? Because: 4. Why? Because: 5.Why? Because:

Step Four: Take Action The Purpose: Prepare to take action based on the data. The critical steps include: 1.Change “observations”/problem statements into goals 2.State the goals as SMART Goals 3.Determine what will indicate that the problem has been solved or the goal(s) have been met. 4.Identify strategies and action steps that will eliminate or correct the “root cause(s)” of the problem 5.Identify what data to track over time to determine if action steps are having the desired effect Cautions Make sure that there is a direct causal link between the goal or solution and the action steps that are being taken. Clearly define what success looks like and measure it. Don’t be afraid to change course if action steps are not having the desired effect.

Next Steps Before next principal’s meeting: –Review this School Improvement Planning process with staff At the next principal's meeting we will work on the Section III of the School Improvement Plan Before the next Leadership Council –Lead staff (and possibly School Accountability Committee) though data driven dialogue (Steps 1-3) –Complete School Improvement Plan through the Data Analysis Worksheet for each of the four performance indicators

Support Area Assistant Superintendents - Amy Weed and Mark Mills Connie Syferd, Regina Renaldi, and Tori Teague Learning Center → Unified Improvement Planning