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Using Data for Decision Making. S.W.I.S. School-wide Information System Teri Lewis-Palmer, Anne Todd, Rob Horner, George Sugai, & Shanna Hagan-Burke. Assumptions. School has team focused on school-wide behavior support. Team has an action plan
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Using Data for Decision Making S.W.I.S. School-wide Information System Teri Lewis-Palmer, Anne Todd, Rob Horner, George Sugai, & Shanna Hagan-Burke
Assumptions • School has team focused on school-wide behavior support. • Team has an action plan • Team meets regularly (weekly, every two weeks) • Team has access to information about student behavior
Why Collect Discipline Information? • Decision making • Professional Accountability • Decisions made with data (information) are more likely to (a) be implemented, and (b) be effective
Key features of data systems that work • The data are accurate • The data are very easy to collect (1% of staff time) • Data are used for decision-making • The data must be available when decisions need to be made (weekly?) • Difference between data needs at a school building versus data needs for a district • The people who collect the data must see the information used for decision-making.
What data to collect for decision-making? • USE WHAT YOU HAVE • Office Discipline Referrals/Detentions • Measure of overall environment. Referrals are affected by (a) student behavior, (b) staff behavior, (c) administrative context • An under-estimate of what is really happening • Office Referrals per Day per Month • Attendance • Suspensions/Expulsions • Vandalism
Office Discipline Referral Processes/Form • Coherent system in place to collect office discipline referral data • Faculty and staff agree on categories • Faculty and staff agree on process • Office Discipline Referral Form include needed information • Name, date, time • Staff • Problem Behavior • Location
When Should Data be Collected? • Continuously • Data collection should be an embedded part of the school cycle not something “extra” • Data should be summarized prior to meetings of decision-makers (e.g. weekly) • Data will be inaccurate and irrelevant unless the people who collect and summarize it see the data used for decision-making.
School-Wide Systems Non Classroom Setting Systems Classroom Systems Individual Student Support Systems Using Office Discipline Referrals for Team Planning
Sugai, Sprague, Horner & Walker, in press • 11 elementary schools, 9 middle schools • For the 9 Middle Schools • Number of students: Mean = 635 (204-1194) • Office Dis Referrals: Mean = 1535 (136-3520) • Referrals per student: Mean = 2.4 • Referrals per school day : Mean = 8.6 • % students with at least 10 referrals = 5.4% • % of referrals from top 5% of students = 40%
Focus on School-Wide System if: • More than 35% of students receive 1 or more referral • Average referrals per student is greater than 2.5
Focus on Non-Classroom Systems if • More than 35% of referrals come from non-classroom settings • More than 15% of students who receive a referral are referred from non-classroom settings.
Focus on Classroom Systems if • More than 50% of referrals are from classroom settings. • More than 40% of referrals come from less than 10% of the classrooms.
Focus on Individual Student Systems • Targeted Group Interventions • If 10 or more students have 10+ referrals • Example (check-in, check-out BEP) • Targeted Individual Interventions • Fewer than 10 students • Intense, individualized support • Wrap Around • Personal Futures Planning • Functional Assessment
Using Data for On-Going Problem Solving • Start with the decisions not the data • Use data in “decision layers” • Is there a problem? • What “system(s)” are problematic • What individuals (individual units) are problematic? • Don’t drown in the data • It’s “OK” to be doing well • Be efficient
The Decisions/Decision Questions • Initial Self-Assessment • Where to focus “investment” energy/time • On-Going Assessment/Planning • Is the action plan working? Should we change? • Decision: Maintain, Modify, Terminate • What is the problem? Where should we focus? • Decision: Allocation of time, money, skills • Do we understand the problem? • What is the smallest effort that will produce the biggest effect?
Interpreting Office Referral Data:Is there a problem? • Absolute level (depending on size of school) • Middle Schools (>6) • Elementary Schools (>1.5) • Trends • Peaks before breaks? • Gradual increasing trend across year? • Compare levels to last year • Improvement?
What systems are problematic? • Referrals by problem behavior? • What problem behaviors are most common? • Referrals by location? • Are there specific problem locations? • Referrals by student? • Are there many students receiving referrals or only a small number of students with many referrals? • Referrals by time of day? • Are there specific times when problems occur?
Combining Information • Is there a problem? • What data did you use? • What systems are problematic? • Where do you need to focus? • The next level of information needed • What information is NOT needed?
What Individuals/Specific Units are problematic? Detailed Data Sources • Individual student data • Direct observation • Faculty/Staff report
Designing Solutions • If many students are making the same mistake it typically is the system that needs to change not the students. • Teach, monitor and reward before relying on punishment.
