cecil j. picard center for child development university of louisiana at lafayette sessions 22a &...
DESCRIPTION
Cecil J. Picard Center for Child Development The Cecil J. Picard Center for Child Development was established in 2005 at the University of Louisiana at Lafayette. Our mission is to improve Louisiana by focusing on its children. The Center’s is dedicated to providing high quality, rigorous evaluation of programs that addresses learning from birth to adulthood. The Center is proud to partner with many state agencies including the Department of Education. Our Center’s work with DOE includes the evaluation of the implementation of Positive Behavior Support.TRANSCRIPT
Cecil J. Picard Center for Child DevelopmentCecil J. Picard Center for Child DevelopmentUniversity of Louisiana at LafayetteUniversity of Louisiana at Lafayette
Sessions 22A & 22BSessions 22A & 22BHolly Howat Oliver Winston Greg Crandall
PBS in Louisiana: PBS in Louisiana: 2006-2007 Evaluation Findings2006-2007 Evaluation FindingsUnderstanding the power of data-based decisions
Cecil J. Picard Cecil J. Picard Center for Child DevelopmentCenter for Child DevelopmentThe Cecil J. Picard Center for Child Development was established in 2005 at the University of Louisiana at Lafayette. Our mission is to improve Louisiana by focusing on its children. The Center’s is dedicated to providing high quality, rigorous evaluation of programs that addresses learning from birth to adulthood. The Center is proud to partner with many state agencies including the Department of Education. Our Center’s work with DOE includes the evaluation of the implementation of Positive Behavior Support.
Evaluation FocusEvaluation FocusSchool-wide Evaluation Tool Correlation AnalysisBehavioral CharacteristicsAcademic CharacteristicsRisk and Protective Factors
CharacteristicsQualitative Results for District-Wide
Implementation
Positive Behavioral SupportPositive Behavioral SupportSchools TrainedSchools Trained
2006-2007 School Year2006-2007 School Year
Positive Behavioral SupportPositive Behavioral SupportSchools TrainedSchools Trained
2006-2007 School Year2006-2007 School Year
School Wide Evaluation ToolSchool Wide Evaluation Tool
The more experience a sampled school has with universal level PBS, the better they are at implementing it.
Most sampled schools had strengths with monitoring and district support and had difficulty with expectations taught.
Comparison of 2006-07 SET Total Scores Across Cohorts by Years of Experience
0
20
40
60
80
100
1 Year 2 Years 3 Years 4 Years
Perc
enta
ge
Cohort 4 N=7 Schools
Cohort 3 N=11 Schools
Cohort 2 N=15 Schools
Cohort 1 N=6 Schools
SET Total and Subcategories Mean Scores for All Sampled PBS Schools
0
20
40
60
80
100
Perc
enta
ge
Total Score
Expectations Defined
Expectations Taught
Reward System
Violation System
Monitoring
Management
District Support
Correlation AnalysisCorrelation AnalysisThis graph indicates that there is statistical significant correlation between School-wide Evaluation Tool scores and Benchmarks Of Quality scores.
SET Scores Relation to Benchmark Scores
0
20
40
60
80
100
0 20 40 60 80 100
Benchmarks
SET SET - Benchmarks
Linear (SET - Benchmarks)
Behavioral Characteristics:Behavioral Characteristics:Suspension RatesSuspension Rates
Sampled schools with over two years of PBS implementation had much lower increases in in-school suspension rates.
A similar pattern existed for out-of-school suspension rates.
Change in ISS Rates from 2003-04 to 2005-06
1.05 1.04
6.73 6.86
0
2
4
6
8
10
Perc
enta
ge
Cohort 1 Cohort 2 Cohort 3 Cohort 4
Change in OSS Rates from 2003-04 to 2005-06
-2.45
0.020.45
2.67
-3
-2
-1
0
1
2
3
4Pe
rcen
tage
Cohort 1 Cohort 2 Cohort 3 Cohort 4
Academic Characteristics:Academic Characteristics:Test Scores and Retention RatesTest Scores and Retention Rates
A general pattern of decline in retention rates can be observed in this sample.
From the data collected for 2006-2007, there was no discernible correlation of PBS implementation to academic outcomes on test scores.
Retention Rates Over Time by Year
0
5
10
15
20
2003-04 2004-05 2005-06
Perc
enta
ge
Cohort 1 N=9 Schools
Cohort 2 N=24 Schools
Cohort 3 N=17 Schools
Cohort 4 N=8 Schools
State Ave.N=1475 Sch.
Risk and Protective FactorsRisk and Protective Factors
Protective factors increased in Grades 6 and 8, particularly the rewards for pro-social behavior.
Risk factors decreased in Grades 6 and 8, particularly a low commitment to school.
PBS Sample School Results on CCYS Protective Factor: Rewards for Pro-social Behaviors
0
20
40
60
80
100
Grade 6 Grade 8 Grade 10
Perc
enta
ge
2004 N=34 Schools
2006 N=34 Schools
PBS Sample School Results on CCYS Risk Factor: Low Commitment to School
0
20
40
60
80
100
Grade 6 Grade 8 Grade 10
Perc
enta
ge
2004
2006
Qualitative Results for Qualitative Results for District-Wide ImplementationDistrict-Wide ImplementationComponent Description One District-wide PBS implementation must have
continued technical assistance from LDE, LSU and UL Lafayette in the development, implementation, and evaluation of a district-wide plan.
Two District-wide PBS implementation must include the organization of personnel, resources, and time, as well as set out goals and strategies for sustainability and expansion.
Three District-wide PBS implementation must have superintendent buy-in at the district level as well as principal buy-in at the school level.
Qualitative Results for Qualitative Results for District-Wide ImplementationDistrict-Wide Implementation
Component Description Four District-wide PBS implementation must have
training and technical assistance that is consistent and continual.
Five District-wide PBS implementation must address a systematic method for collecting, analyzing, and using data to make decisions.
Six District-wide PBS implementation must include an evaluation of the implementation across the district.
Data Driven Decision MakingData Driven Decision MakingAt the Picard Center for Child Development, we collect and analyze data to inform policy makers so they can informed decisions.
School and districts can also collect and analyze data so they can make informed decisions.
Data Driven Decision MakingData Driven Decision Making
PURPOSE:
To review critical features & essential practices of data collection and the analysis of data for interventions
Non-classr
oom
Setting Syst
ems
ClassroomSetting Systems
Individual Student
Systems
School-wideSystems
School-wide Positive Behavior School-wide Positive Behavior Support SystemsSupport Systems
Data Collection ExamplesData Collection Examples
An elementary school principal found that over 45% of their behavioral incident reports were coming from the playground.
High school assistant principal reports that over two-thirds of behavior incident reports come from our cafeteria.
Data Collection ExamplesData Collection Examples
A middle school secretary reported that she was getting at least one neighborhood complaint daily about student behavior during arrival and dismissal times.
Over 50% of referrals occurring on “buses” during daily transitions.
Data Collection ExamplesData Collection Examples
At least two times per month, police are called to settle arguments by parents & their children in parking lots.
A high school nurse lamented that “too many students were asking to use her restroom” during class transitions.
Data Collection QuestionsData Collection Questions
What system does the parish utilize for data collection?
How is the data system being used in each school setting?
How frequently are data collection system reports generated (bi-weekly, monthly, grading period and/or semester reports )?
Minimal School-Level Data Minimal School-Level Data Collection NeedsCollection Needs
Minor referrals Major referrals Referrals by staff members Referrals by infractions Referrals by location Referrals by time Referrals by student
Minimal District-Level Data Minimal District-Level Data Collection NeedsCollection Needs
Majors referrals (ODRs) Referrals by Incident Referrals by Infractions Times of incidents Locations of incidents (what school and
where in the school)
Data Analysis QuestionsData Analysis Questions How is the data displayed (graphs, tables,
etc.) and is it effective?
What are the outcomes of data review?
Are data-based decisions reached?
How are data-based decisions monitored for effectiveness?
Minimal School-Level Data Minimal School-Level Data Analysis NeedsAnalysis Needs
PBS team should be part of analysis process
Data should be reviewed to determine patterns of problem behaviors
Decisions should be based upon data presented
Decisions should include an intervention that can be successfully implemented and monitored.
Using Data to Make DecisionsUsing Data to Make Decisions What interventions are needed to respond
to problem behaviors?
How do we implement the intervention throughout the school?
What is the time table for the intervention to show a decrease in undesirable behavior?
Contact InformationContact InformationDr. Holly [email protected]
Mr. Oliver [email protected]
http://ccd-web.louisiana.edu/