Do teachers improve every year as measured by student achievement, and, if not, should it impact compensation?
Can we measure teacher performance?
Bill Sanders, currently a professor at University of North Carolina, has been developing a highly sophisticated statistical system called “value-added modeling.” While there has been criticism of Sander’s methodology we are clearly on the path to be able to extract the amount of “value” teachers add to students.
The DOE is using the Sanders modeling methods in the Teacher Data Initiative (TDI), an early experiment in informing teachers of their “effectiveness” compared with other teachers teaching similar students.
Salary schedules, for eons, have been seniority based, called “steps.” In recent years the “steps” have been steeper at the lower end of the scale. In NYC teachers receive two step increases a year for the first eight years, then, raises after 10, 13, 15, 18, 20 and reach maximum at 22 years. The theory is simple, create a salary structure that encourages teachers to remain in the system.
If it is possible to measure teacher performance, how should it impact salary compensation schedules? Should we continue with a seniority based system or factor “value-added” into compensation plans?
The evolution of supercomputing has enabled researchers to analyze limitless bits of data, and apply statistical tools,
A regression is a statistical procedure that takes raw historical data and estimates how various causal factors influence a single variable of interest.
a mathematical ‘neural network’ is a series of interconnected switches, like neurons, receive, evaluate and transmit information…. At the end of the network is a final switch that collects information from previous neural switches and produces from its output the neural network’s prediction …
At the end of the process the researcher looks at the data and decides whether the results are “significant.” Aaron Pallas, at Gotham Schools is instructing us, a sort of Statistics 101.
As the evidence mounts we can conclude, not surprisingly, that “all teachers are not created equal.”
Is using student/teacher achievement data to impact compensation schedules the correct route? Will it result in more effective schools, or simply reward some teachers, and antagonize others?
Should we reward individual teachers, schools (i. e., the current NYC Bonus Plan), or, teams of teachers, such as grade teams or small learning communities in secondary schools?
Do senior teachers become too “comfortable,” and fail to continue to upgrade their skills?
Should “rewards” solely be in increased compensation, or should the increased dollars be totally flexible and be used to buy equipment, fund school trips, etc.
Or, should this datum become the core of a peer review teacher evaluation system?
The American Federation of Teachers has just announced an Innovation Fund, hopefully the fund will encourage a wide range of school-based plans that inform future policy determinations.