Michael Hansen of AEI Education, has penned a new report examining teacher evaluations systems. Hansen believes that, whether or not student test scores continue to be demanded as the gold standard for teacher evaluations, data analysis will be the crucial factor in the future of teacher evaluations.
As more states and districts have moved to teacher evaluation models that include student performance (often called value-added models), there has been just as much pushback against these systems. Their validity is a particular concern to many, with many believing that any model that places standardized tests at the bottom of the pyramid is fundamentally flawed one. Michael Hansen, in the AEI Teacher Quality 2.0 Special Report 4, moves beyond this tension to the recognition that teacher evaluations will need to involve more “process-based evaluations” by state and district leaders. This will mean more time, money, and effort from those in higher positions—none of which are easy to come by. As a result, Hansen speculates, “data-driven” evaluation systems will become increasingly crucial.
From the executive summary to the report:
The growing prominence of value-added models for measuring teacher effectiveness has prompted a recent surge in policies that consider students’ classroom performance part of a teacher’s evaluation. Yet, in light of the criticism and limitations of the current models, whether and how evaluation systems will adapt over time is unclear. This paper considers how teacher evaluations may likely evolve in the near future, which will have implications for state and district policy adoption.
The future shape of evaluation systems will be determined by who bears the cost of controlling the quality of the teacher workforce. Until now, teachers and students have largely born these costs. But if states and districts are serious about improving workforce quality, they must take on a greater share. Consequently, the current orientation of input- and output-based evaluations will be supplemented with more rigorous process-based evaluation. Heightened cost pressures for school leadership will likely lead to more automated, data-driven evaluation systems.
Improvements in four specific areas will particularly influence teacher evaluations moving forward:
- Small-scale measurement;
- Implementation issues;
- Workforce monitoring;
- Paradigm shifts in education research.
Data analysis plays a key role across all four areas, and will be the necessary precursor to improvements in public school teacher evaluation systems.
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