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Self-Reported vs. Verified School Data
Three kinds of misinterpretations can occur when self-reported school outcomes data is used to compare school district results:
(1) Does the data "fit" the same definition from school district to school district?
Example 1: Jones School District reports expenditures per pupil of $6,000 per year per student. Smith School District reports $8,000. Does either figure actually represent the money dedicated to direct classroom instruction (teacher salaries, textbooks, support materials, classroom aides, and others), or does the figure also include the capital outlay of the district (money dedicated to repairs and maintenance of facilities) and expenditures for special needs students (learning disabled, low or high-incidence handicapped, and others)?
Most states have legislated payments to school districts to help them recover some capital expenditures. All states have a shared revenue commitment for educating special needs students. Additionally, the cost of educating a special needs student may be as much as double the cost of the regular education student. Are those costs averaged in?
Example 2: Jones School District reports the pupil/teacher ratio as 16/1. Smith School District 20/1. What positions actually qualify as "teacher" in Jones and Smith Districts?
(2) When can data from school district to school district, regardless of the state or location, be compared?
Data among school districts can be compared when educational consultants have verified that the data fit the same definitions, and when all school districts in the nation abide a federal law that sets the definition for which data will be reported.
(3) Where does a school district "fit" in the national framework?
Self-reported data is frequently discrete numbers, raw data, if you
will. So, if the topic is pupil expenditures, does a dollar in North
Carolina "buy" the same amount of educational services as a dollar
SchoolMatch® relational data are just that - data "handled" in such a
way that every school district across the nation CAN be compared.
Our consultants verify definitions, apply algorithms to raw data,
and query the bases of raw data reports . . . then spread all 16,000
public school districts out over the 99 percentile ranges.
A very good thing happens when the data in one
school district are related to the data in every other K-12 public
school district: a school district can actually take on its own
dynamic and unique identity as outcomes are reported in each of
the 22 data categories - sliding up the scale, if you will, in some
areas, sliding down the scale in others.
Example: a school district can fall in the 5th percentile nationally in size of district (it means they are very small); can fall in the 95th percentile nationally in student performance on college entrance examinations (it means their students are very well prepared to take the exams); and can fall in the 48th percentile in pupil/teacher ratio (it means they are about average nationwide).