Friday, April 18, 2014
By Prashant Mittal
(Continued from page 1)
Schools that achieve high reading or math proficiency scores one year are also likely to have high three-year average reading or math scores. Maine’s school ranking formula counts both the one-year and the three-year scores, so schools with high scores get double the credit and schools with low scores get double the penalty.
Graphics by Prashant Mittal
Seven Maine high schools moved up in the state school rankings when the formula was altered to ensure that the schools weren’t penalized twice for the same criteria: once for having low one-year proficiency scores, and again for having low three-year average proficiency scores.
KEY VARIABLES IGNORED
Second, important aspects that might make or break learning outcomes for a school were ignored.
Factors such as student-teacher ratio, teacher qualifications and salary, the socioeconomic status of the town, science proficiency, student demographics, etc., are important predictors of learning environment for a school, which were not considered.
LOCATION, LOCATION, LOCATION
Third, all high schools, no matter where they were located in the state, were compared equally. This had a huge impact on the grading algorithm.
A comparison between a high school in a small town up north with schools in the Portland area will be unfair. A small-town school is more likely to be deficient in resources compared to a school in a larger town or city.
As a consequence, schools that are ranked very low with poor grades really have no silver lining to hope for.
Is there a better solution? This is not all about pinpointing mistakes, but also about offering a better, viable solution.
My recommendation would be to make it a fair, meaningful and numerically correct system.
NCAA SYSTEM: A ROLE MODEL
A sound grading system could learn from the NCAA sports championships, dividing schools into divisions based on similarity of their characteristics.
These divisions could be created based on a single principle: Schools within a division will be similar to each other, and divisions will be dissimilar from each other. A tangible benefit of this kind of divisional clustering is the proportionate and proper allocation of resources.
It will take off the pressure and unintended humiliation that schools may have suffered after the rankings were announced. And it would give them a chance to grow slowly and steadily. That would be a fair way of ranking schools and would give schools the most important ingredient to work harder: hope.
Incidentally, a group of four graduate students has been working on a similar algorithm under my supervision as part of the requirement for a course titled "Probability and Statistics." The state grading system could not have come at a better time, as we are getting ready with a much better, statistically sound and robust algorithm to rank and grade high schools.
Prashant Mittal (email: email@example.com) is a senior statistician at the University of Southern Maine and teaches applied statistics and data analytics courses at the USM School of Business.