Can More Data Help Improve Teacher Preparation?
The U.S. Department of Education’s new regulations for teacher preparation programs ask states and organizations that prepare teachers to provide much more data about graduates’ competence, their persistence in the teacher workforce, and their impact on student learning. In the works since 2012, these new regulations differ from what states must report under the current regulations in Title II of the Higher Education Act.
The big shift is that starting in the next school year, states must collect outcome data from teacher preparation programs that goes beyond the current data—such as the number of teacher candidates; their race, ethnicity, and gender; and the percentage who pass state certification exams. U.S. Department of Education Secretary John King called the information collected until now “surface level” data and said that the information required under the new regulations would give a much deeper look at how well teacher preparation programs prepare effective teachers.
For the most part, the new data requirements focus on such outcome-driven questions as:
- Are employers satisfied with their new teachers’ abilities?
- Do new teachers stay in the profession?
- Can new teachers raise student achievement?
- Do new teachers themselves believe they were well-prepared to teach?
No doubt answers to these questions can provide teacher educators, school districts, and principals with more data about teacher preparation programs and their graduates already in the field. But earlier indicators could signal problems long before candidates graduate.
Research shows that an effective teacher can raise student achievement above the norm. Plus, brand-new teachers often end up teaching students in the most disadvantaged schools and communities. So their ability to teach well on day one is essential to the students who most need excellent teaching.
And states are very aware of that need. Forty-five states’ current equity plans cite improving educator preparation and certification as a strategy for ensuring equitable access to excellent educators. Analysis of the new data should inform and incite a productive policy dialogue.
As for what we can expect under the new regulations, states will now have to collect data on teacher-preparation programs, use it to evaluate each program’s effectiveness, and rate each program. Programs rated as less than effective for two out of three years will no longer be able to offer federal Teacher Education Assistance for College and Higher Education (TEACH) grants, which award up to $4,000 per year to teacher candidates preparing to work in high-needs schools and subjects. Withdrawal of TEACH grants from less than effective programs will take effect in the 2021-22 school year.
Analysis of the new data can point to weak teacher programs—after the fact. What’s missing is a measure of weakness before a program falters, before its candidates graduate and start teaching. To ensure that all students have access to effective teachers, teacher educators should assess their candidates long before they are placed in classrooms. That would let teacher educators get individual candidates back on track—or adjust their programs to better prepare candidates.
Some programs are trying a “rounds” model, similar to those used in medical training. Teacher candidates visit multiple classrooms to watch different teachers use specific teaching practices. Others give candidates more carefully structured feedback on their student teaching.
On the technology front, a new simulator lets candidates practice in a virtual, no-stakes environment—like rookie pilots do when learning to fly airplanes. Would-be teachers master such instructional moves as asking open-ended questions or responding to student misunderstanding, long before they try them out with children.
It may ask a lot of federal policy to inspire deep transformations that could improve what teacher educators do to prepare teacher candidates to become skilled and ready to support student learning. But perhaps as this new, wider data collection becomes routine, as the ratings are published, and as aspiring teachers choose to attend the best-rated programs, the field may be inspired to design and test new ways to prepare teachers and assess their effectiveness before they finish their program, before they enter the field, and before their teacher preparation program is held accountable for their performance.
Jenny DeMonte specializes in teacher preparation and licensure. She has worked on research and policy issues related to teacher quality and school improvement for more than two decades—first as a journalist and now as an AIR researcher.