goals for session n.
Download
Skip this Video
Loading SlideShow in 5 Seconds..
Goals for Session PowerPoint Presentation
Download Presentation
Goals for Session

Loading in 2 Seconds...

play fullscreen
1 / 46

Goals for Session - PowerPoint PPT Presentation


  • 135 Views
  • Uploaded on

Goals for Session. Define the role of data-based decision-making with the School-wide PBS approach. Propose features of Office Discipline Referral data that are most useful for decision-making in schools Provide guidelines for using data for team planning

loader
I am the owner, or an agent authorized to act on behalf of the owner, of the copyrighted work described.
capcha
Download Presentation

Goals for Session


An Image/Link below is provided (as is) to download presentation

Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author.While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server.


- - - - - - - - - - - - - - - - - - - - - - - - - - E N D - - - - - - - - - - - - - - - - - - - - - - - - - -
    Presentation Transcript
    1. Goals for Session • Define the role of data-based decision-making with the School-wide PBS approach. • Propose features of Office Discipline Referral data that are most useful for decision-making in schools • Provide guidelines for using data for team planning • Provide guidelines for using data for on-going problem solving • Apply guidelines to examples

    2. Improving Decision-Making Solution Problem From Problem Solving Solution Problem To Information

    3. What information do we need to make a good decision?

    4. What information do we need to make a good decision?

    5. What information do we need to make a good decision?

    6. What information do we need to make a good decision?

    7. What information do we need to make a good decision?

    8. Key features of data systems that work. • The data are accurate and valid • The data are very easy to collect (1% of staff time) • Data are presented in picture (graph) format • Data are current (no more than 48 hours old) • 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.

    9. Why Collect Discipline Information? • Decision making • What decisions do you make? • What data do you need to make these decisions? • Professional Accountability • Decisions made with data (information) are more likely to be (a) implemented, and (b) effective

    10. 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

    11. 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 includes needed information • Name, date, time • Staff • Problem Behavior, maintaining function • Location Definitions Compatibility Checklist Referral Form p.10

    12. What data are needed for effective decision making (The Big Five) • How Much: Office discipline referrals (ODR) • ODR per school day • ODR per school day per 100 students • What: ODR by type of problem behavior • Where: ODR by location • When: ODR by time of day • Who: ODR by student • Why: ODR by perceived motivation

    13. Organizing Data for “active decision-making” • Counts are good, but not always useful • To compare across months use “average office discipline referrals per day per month”

    14. January 10

    15. Using Data for On-Going Problem Solving • Start with the decisions not the data • Use data in “decision layers” (Gilbert, 1978) • Is there a problem? (overall rate of ODR) • Localize the problem • (location, problem behavior, students, time of day) • Get specific • Use data to guide asking of “the right questions” • Don’t drown in the data • It’s “OK” to be doing well • Be efficient

    16. Is there a problem? • Office Referrals per Day per Month • Attendance • Faculty Reports

    17. Interpreting Office Referral Data:Is there a problem? • Absolute level (depending on size of school) • Middle, High Schools (> 1 per day per 100) • Elementary Schools (> 1 per day per 250) • Trends • Peaks before breaks? • Gradual increasing trend across year? • Compare levels to last year • Improvement?

    18. Elementary School with 250 students

    19. Middle School with 500 students

    20. Middle School with 500 students

    21. Middle school with 500 students

    22. Middle School with 500 students

    23. Is there a problem? Middle school with 500 students (Dec)

    24. Is there a problem? Middle School with 500 students

    25. Is there a problem? Middle School with 500 students (Dec 04-05)

    26. Is there a problem? Middle School with 500 students (Feb 3, 04-05)

    27. 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?

    28. Middle School

    29. Elementary School

    30. Referrals per Student

    31. Referrals per Student

    32. 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. • An example (hallways)

    33. Summary • Transform data into “information” that is used for decision-making • Present data within a process of problem solving. • Use the trouble-shooting tree logic • Big Five first (how much, who, what, where, when) • Ensure the accuracy and timeliness of data.

    34. Team Reports • ID next team meeting (Date and Time) 1. Team Leaders will notify Manuel raposomt@aol.com 410.545.0930 2. Team leader will arrange meeting and create agenda 3. Team Leader will attend next Baltimore City Team Leader Orientation meeting (Date TBA) • ID topic of next team meeting