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School-Performance Dashboard Cowen Institute Tulane University Priscilla (Penny) Wohlstetter, Ph.D. Archana Patel Sean Parker Note: This excerpt is my.

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Presentation on theme: "School-Performance Dashboard Cowen Institute Tulane University Priscilla (Penny) Wohlstetter, Ph.D. Archana Patel Sean Parker Note: This excerpt is my."— Presentation transcript:

1 School-Performance Dashboard Cowen Institute Tulane University Priscilla (Penny) Wohlstetter, Ph.D. Archana Patel Sean Parker Note: This excerpt is my contribution to a longer presentation. Please click through it in presentation view to see my step-by- step animations. –Sean

2 Layers of Information Dashboard For Example School

3 Layers of Information Layer Ia: Note the colors. marks the top 20%. marks the bottom 20%. Layer Ib: Note the numbers. The numbers are percentile ranks. A percentile rank of 83 means that this school is performing better than approximately 83% of schools in the sample. Is 83 good? Its all relative. The fastest glacier is still slow. The slowest shooting star is still fast! Dashboard For Example School

4 Layers of Information Digging Deeper What is the schools actual SPS Score? This school is at the top of the pack in SPS, but what does the pack look like? Dashboard For Example School

5 Layers of Information This school has an SPS Score of and 67 mark the bottom 20% and the top 20%, respectively. The bulk of schools fall in this range. Dashboard For Example School

6 Layers of Information This school has an SPS Score of and 67 mark the bottom 20% and the top 20%, respectively. Layer IIa: Note the indicators for the domain. Layer IIb: Note the schools actual values. Digging Deeper What does the 75 for Academic Environment mean? On the face, it means that this school scored higher than about 75% of the schools in the sample. But, there is more to uncover. Layer IIc: Note the placing in each pack. Relatively Low Layer IId (subtle): Note the weighting. (See Appendix) Dashboard For Example School

7 Layers of Information Digging Deeper What is statistical control? What is the difference between Per Pupil Expenditure Controlling for Number of Students and Per Pupil Expenditure (Uncontrolled)? What is the difference between Student-Faculty Ratio and Controlled Student-Faculty Ratio? It is one thing to have a Student-Faculty Ratio of 20 when you have 200 students. It is another thing to have a Student-Faculty Ratio of 20 when you have 800 students. When we statistically control for number of students, we ask of each school, what is your Student-Faculty Ratio over and above (or under and below) what we would predict based your number of students? Dashboard For Example School

8 Layers of Information This school has a Student-Faculty Ratio of 11, which puts it in the middle of the pack. But, the pack is comprised of schools of various sizes. Lets simultaneously consider Student-Faculty Ratio and Number of Students Notice the three schools with about 600 students each. One has an S-F Ratio of about 25, another of about 14, and another of about 8. We see that one school has an S-F Ratio 10 units greater than we would predict based on Number of Students. Another school is 1 unit less than our prediction, and another school is 7 units less than our prediction. Based on a fitted trend line, we predict an S-F Ratio of about 15 for schools with 600 students. Dashboard For Example School

9 Layers of Information Our school has a Student- Faculty Ratio of 11. It has a school size of about 180. Thus, the Student-Faculty Ratio of 11 is 5 units above what we would predict based on number of students. That 5 units is the Controlled Student-Faculty Ratio. Based on a school size of about 180 students, we would predict a Student-Faculty Ratio of about 6. Statistical control is the 3 rd (and most complicated) layer of information. Now, we can put it all together… Dashboard For Example School

10 A Comprehensive View of Performance Dashboard For Example School

11 Appendix: Weighting Digging Deeper Layer IId (subtle): Note the weighting. 2 Dots 3 Dots 4 Dots The percentile rank for the domain is based on a weighted average of the indicators. First, we give the indicators equal weight, as we standardize their various scales to a mean of zero and a standard deviation of one, roughly translating each indicator to a scale from -3 to 3. Then, we give each indicator a deliberate weight (decided by the consortium with a statisticians guidance), and this deliberate weight is denoted by the dots under the value. Thus, we see that the SPS Score is weighted most and that the PPE (Uncontrolled) is weighted least.


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