Read any newspaper and you will discover that finding qualified teachers for subjects such as math, science, and even English language arts can be a challenge in many regions of the United States. That challenge poses a serious problem for many education leaders trying to ensure their students receive an excellent education.
It is imperative to the Missouri Department of Elementary and Secondary Education (MO DESE) to provide excellent, qualified teachers to every student in its system. However, like many states, MO DESE faces teacher shortages. MO DESE recently released the Teacher Shortage Report that notes a need for teachers in numerous areas including elementary grades, early childhood, science, math, and special education. To address this issue, MO DESE partnered with REL Central to develop a tool called the Teacher Predictor Model.
MO DESE began developing the Teacher Predictor Model in collaboration with the Central Comprehensive Center, Center on Great Teachers and Leaders, and REL Central in an effort to better understand when and where schools and districts were succeeding in or experiencing challenges in filling hard-to-staff teaching positions. The expectation was that the Teacher Predictor Model would use statewide data to predict upcoming educator shortages by subject area, grade level, geographic region, and age. MO DESE leaders could then use this information to develop strategies that address those challenges.
To date, REL Central’s role in supporting MO DESE has been to help them better use state data on teacher staffing and associated factors, provide an external review of the model’s validity, develop a training manual, and provide an in-person training to help staff interpret model results.
“We know that not every district has the same ability to fill hard-to-staff positions or even know what possible future shortage areas might be,” said Paul Katnik, assistant commissioner for MO DESE, who has been working closely with REL Central on the project. “Our hope is that we will be able to use this model to help us shape recruitment strategies.”
Katnik envisions that data from the Teacher Predictor Model may ultimately be used to support teacher preparation efforts both at the state and university levels, and the data will inform MO DESE’s strategic plans to ensure every student is receiving an education from an excellent teacher in every subject.
Currently, while continuing to support MO DESE, REL Central is compiling the steps taken by MO DESE to develop and use the teacher predictor model so that other states can benefit from the model. That work will be released as a report, tentatively called “The Teacher Predictor Model: An Approach to Using Teacher and Student Data to Understand and Predict Teacher Shortages” later this year.
