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Enhancing Education Through Data-Based Decision Making: DLT Webinar Focus

Join the District Leadership Team for a comprehensive webinar focused on data-based decision making in education. This session will review the role of the DLT and assess district strengths and needs in implementing culturally responsive Positive Behavioral Interventions and Supports (CR-PBIS). We will delve into effective data collection and analysis strategies, identifying trends, and using demographic data to improve discipline systems across all student groups. Explore the next steps for your district and gain insights into leveraging data to foster equity in educational outcomes.

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Enhancing Education Through Data-Based Decision Making: DLT Webinar Focus

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  1. District Leadership Team Webinar #1:Data Based Decision Making Center for Education and Lifelong Learning The Equity Project at Indiana University Culturally Responsive Positive Behavioral Interventions and Supports www.indiana.edu/~pbisin

  2. Focus of Webinar • Review of the Role of the DLT • Assesses district strengths and needs related to using Data for Decision Making in CR-PBIS • Discuss Next Steps for the DLT in your District • Continued Work with PBIS-IN

  3. The Blueprint

  4. Using Data for Decision Making

  5. Data! Data! Data! • How do we collect data? • How do we analyze data? • How often? • Who? • When? • How can the data and information be used to improve our discipline system? • Applying to all students equally • Use of demographic data • Behaviors and locations • Classroom managed vs. Office managed

  6. Defining the Problem • Review your data to determine current strengths and areas of need: • Compare district enrollment numbers to current outcomes • Disaggregate data by ethnicity, gender, SES, grade level

  7. District A Composition

  8. Data-Based Decision making using ODRs • Examine ODRs( number of office referrals): • Per day per month • Based on location • Based on type of behavior • By student • By time of day • By subgroup (i.e. ethnicity, gender, special education status) • Examine consequences of referrals • Suspension and expulsion data • Disaggregated suspension and expulsion data

  9. Analyzing ODR data • Do we have a problem? • Avg./per day per month • Elem. .22/100 students per day. • MS .50/100 per day • HS .68/100 per day • Trends and Peaks • What kind of problem? • Behaviors of concern • Where? • Hot spots, cool spots

  10. Analyzing ODR data • When? • Time of Day • By Whom? • Lots of students or few students? What percentage of students have been to office? • Subgroups? • Do you have an disproportionate representation problem?

  11. District A Data Summary

  12. Next Steps for your DLT

  13. Your Next Steps

  14. Contact Us • www.indiana.edu/~pbisin • Contact us with questions: Renae Azziz • razziz@virtuosoed.com Shana Ritter • rritter@indiana.edu

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