1. Becoming a Data Analyst Written by Steve Newton, Rob Horner and Anne W. Todd, University of Oregon Bob Algozzine and Kate Algozzine, University of North Carolina at Charolette & Present by Anne Todd, UO and Rick Kirschmann, East County March 15, 2010 and April 1, 2010
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4. Collect and Use Data Develop Hypothesis Discuss and Select Solutions Develop and Implement Action Plan Evaluate and Revise Action Plan Problem Solving Meeting Foundations Team Initiated Problem Solving (TIPS) Model Identify Problems
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6. Collect and Use Data Develop Hypothesis Discuss and Select Solutions Develop and Implement Action Plan Evaluate and Revise Action Plan Problem Solving Meeting Foundations Team Initiated Problem Solving (TIPS) Model Identify Problems
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9. Problem-Solving Meeting Foundations Structure of meetings lays foundation for efficiency & effectiveness
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13. Organizing for an effective problem solving conversation 03/15/10 Problem Solution Out of Time Use Data A key to collective problem solving is to provide a visual context that allows everyone to follow and contribute
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15. Langley Elementary PBIS Team Meeting Minutes and Problem-Solving Action Plan Form Today’s Meeting: Date, time, location: Facilitator: Minute Taker: Data Analyst: Next Meeting: Date, time, location: Facilitator: Minute Taker: Data Analyst: Team Members (bold are present today) Administrative/General Information and Issues Problem-Solving Action Plan Evaluation of Team Meeting (Mark your ratings with an “X”) Today’s Agenda Items Next Meeting Agenda Items 01. 02. 03. Information for Team, or Issue for Team to Address Discussion/Decision/Task (if applicable) Who? By When? Implementation and Evaluation Precise Problem Statement, based on review of data (What, When, Where, Who, Why) Solution Actions (e.g., Prevent, Teach, Prompt, Reward, Correction, Extinction, Safety) Who? By When? Goal, Timeline, Decision Rule, & Updates Our Rating Yes So-So No 1. Was today’s meeting a good use of our time? 2. In general, did we do a good job of tracking whether we’re completing the tasks we agreed on at previous meetings? 3. In general, have we done a good job of actually completing the tasks we agreed on at previous meetings? 4. In general, are the completed tasks having the desired effects on student behavior?
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22. 03/15/10 Any tasks assigned get copied to the meeting minutes of the next meeting as a follow up item Meeting Agenda Item: Meeting Foundations Tasks: What, by whom, by when
34. ~80% of Students ~15% ~5% 0-1 office discipline referral 6+ office discipline referrals 2-5 office discipline referrals Using office discipline referrals as a metric for universal screening of student social behavior
37. SWIS summary 2008-2009 (Majors Only) 3,410 schools; 1,737,432 students; 1,500,770 ODRs Grade Range Number of Schools Avg. Enrollment per school National Avg. for Major ODRs per 100 students , per school day K-6 2,162 450 .34 = about 1 Major ODR every 3 school days, or about 34 every 100 days 6-9 602 657 .85 = a little less than 1 Major ODR per school day, or about 85 every 100 days 9-12 215 887 1.27 = more than 1 Major ODR per school day, or about 127 every 100 days K- (8-12) 431 408 1.06 = about 1 Major ODR per school day, or about 106 every 100 days
50. Which Statement Is More Precise? 1a. Too many ODRs 1b. Too many instances of disrespect 2a. Too many ODRs between 1:00pm and 1:30pm 2b. Too many ODRs in the afternoon 3a. Too many ODRs occurring outside the classrooms 3b. Too many ODRs on the playground 4a. 25% of students have at least 2 ODRs 4b. Many students are experiencing ODRs 5a. Too many ODRs on the playground 5b. Total of 12 aggression ODRs on playground last month; more than last year & showing increasing trend this year; occurring during first recess; 8 different students involved
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52. Defining the Problem What Problem Behaviors are Occurring? Are there lots of different types of problems or just a few? How do the problem behaviors fit with the SW expectations? What other questions do these data pose?
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54. Note that you can request a Table as well as a Graph
55. Are there lots of different types of problems or just a few? How do the problem behaviors fit with the SW expectations? What other questions do these data pose?
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60. Clarifying the Problem Where Are Problem Behaviors Occurring? Many locations or just a few?
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63. Many locations or just a few? What other questions do these data pose?
74. ~80% of Students ~15% ~5% 0-1 office discipline referral 6+ office discipline referrals 2-5 office discipline referrals Using office discipline referrals as a metric for universal screening of student social behavior
It isn’t whether you have a problem, it’s whether you have the same problem again next year.
03/17/10 Newton, J. S., Todd, A. W., Algozzine, K., Horner, R. H., & Algozzine, B. 2008
The full TIPS model. Two parts. Implementation of Problem Solving Meeting Foundations Use of the problem solving process (strategy?)
03/17/10 Newton, J. S., Todd, A. W., Algozzine, K., Horner, R. H., & Algozzine, B. 2008
This slide is animated to teach the different parts of the meeting minute form each click adds the next section Most schools have the title at the top and write/type as the meeting progresses Make a point that we don’t need to document everything that happened (i.e., NM rolled her eyes KJ entered the room, SW continued to repeat the same issue, we took at 5 minute bathroom break)
A completed example… IF a person knows how to use the meeting minute form, the person should be able to pick these minutes up from Jan 7, 2010 and be able to organize previous items to update and facilitate creation of the Feb 3, 2010 agenda
03/17/10 Newton, J. S., Todd, A. W., Algozzine, K., Horner, R. H., & Algozzine, B. 2008
OK…. Building precision problem statements is a skill that is needed for using the data. organizing and interpreting the data requires another set of skills. Slides 25-47 provide a sequence of slides to illustrate different precision statements based on different pictures of the same type of data.
Let’s talk about accuracy of the data again. When you begin to use the data and draw comparisons, the data need to be comparable. Look at the data above. First, as a data analyst, you look and see, ‘wow.. Things are getting better, the graph is going down’…. Then you do what you are supposed to do first, and look at the label on the Y axis. This label says total office discipline referrals. It is great to compare the total ODRs, but now… look at the X-axis. There are a different number of days in each month and the number of schools day in each much has a wide range (Dec may have 10 school days, January may have 19 school days). These months, the way they are arrayed here, are not comparable and this data should not be used! If you aren’t using SWIS, do the math to get average referrals per day per month by using the total referrals and the total days each month. If you are using SWIS, do not fear….. (next slide)
SWIS does that calculation for you. look at the Y-axis label now. Average referrals per day per month allow us to compare months. Now look at the trend….. ‘we are going to have a wild spring term if we don’t do anything differently!). This is the same set of data on the previous slide and look at what the pattern of data does for the problem solving process. Accurate data and data that are formatted for purposes of making decisions is critical. I like to make this a bit dramatic by going back and forth between this slide and previous, telling them they are the team and they are reviewing this data…
Build the routine when reviewing these slides: How many students? How many hundreds? What is the per 100 rate for your school? How are you doing? Is there a trend, are there peaks, patterns?; what can we anticipate?
Build the routine when reviewing these slides: How many students? How many hundreds? What is the per 100 rate for your school? How are you doing? Is there a trend, are there peaks, patterns?; what can we anticipate?
Slides 31-33 work as a set. This slide is a precursor to the next slide to show how to start with ‘this years’ data and then use it to compare to last year (slide 32) Build the routine when reviewing these slides: How many students? How many hundreds? What is the per 100 rate for your school? How are you doing? Is there a trend, are there peaks, patterns?; what can we anticipate?
Build the routine when reviewing these slides: How many students? How many hundreds? What is the per 100 rate for your school? How are you doing? Is there a trend, are there peaks, patterns?; what can we anticipate? What happened last year that we don’t want to repeat?
Final slide of this set Build the routine when reviewing these slides: How many students? How many hundreds? What is the per 100 rate for your school? How are you doing? Is there a trend, are there peaks, patterns?; what can we anticipate? What are we going to do next fall to maintain this success?
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