With experts across the country debating what it takes to create a successful teacher evaluation system, teachers are making their voices heard about the process. According to the Network for Public Education, teachers consider test-based teacher evaluations particularly unhelpful.
Those were among the responses to a recent survey released by the Network for Public Education, which polled nearly 3,000 teachers and administrators.
Many of the teachers surveyed said test-based evaluations have a negative effect on those who are educating the most reliant students. They also stated that these systems have harmed the relationships developed between teachers and their students, and other educators.
For years, policy makers have been in conflict with education organizations such as the American Statistical Association, which has discouraged the use of these value-added measurements. Proponents of these measures said they are designed to form an accurate assessment of a teacher’s effectiveness by using formulas combining standardized test score with the “value” added by the teachers. Yet, critics say the results are far from reliable. The American Statistical Association, for example, stated that value-added models (VAMs) typically measure correlation, not causation: Effects — positive or negative — attributed to a teacher may actually be caused by other factors that are not captured in the model.
The Network for Public Education’s survey results do not serve as a statistical representation of the country, but they do show the common issues teachers have with current and proposed teacher evaluation systems. They also align with the results of many other polls and surveys with teachers’ views that they are the victims of their occupation being focused on by school reformers, putting them under notable amounts of stress.
Many educational experts say it will take more time and research to develop effective teacher evaluation systems. And they say it’s crucial to take teachers’ thoughts and opinions into consideration as well when deciding on the system best fit to evaluate their performances.