Measuring and Changing STEM Teacher Stress to Promote Effectiveness and Retention

The project aims to serve the national need of preparing and retaining effective mathematics teachers through its focus on understanding and addressing the crisis of STEM teacher stress in high need districts. In an era of elevated levels of clinically significant mental health problems linked to stress, mathematics teachers are tasked with the demands of overcoming learning losses due to the COVID-19 pandemic.

Many teachers report this stressful demand is more than they have been prepared to handle. This stress can cause teachers to be less likely to use the most effective, student engagement teaching practices, and it can cause burnout that leads teachers to leave the profession. Issues related to stress, teacher effectiveness, and burnout may be elevated for pre-service teachers who teach in high-need school districts.

Unfortunately, teacher preparation programs and school and district administrators are underprepared to respond to this crisis. Moreover, there are currently no validated, scalable, actionable measures that can help them to anticipate or respond to teachers’ stress. Therefore, this Noyce research project will first, as a preliminary matter, create a validated, scalable measure of teacher stress.

Using wearable photoplethysmography sensors, data will be collected from 100 pre-service mathematics teachers and 100 in-service mathematics as part of the development of the stress measure. The measure will then be used to test novel hypotheses about ways to promote STEM teacher effectiveness and retention in high-need school districts.

This project at the University of Texas at Austin and Rochester University includes partnerships with the UTeach teacher preparation program and two high-need school districts (Judson ISD and Round Rock ISD). Project goals include: (1) developing and validating a scalable measure of in-service and pre-service mathematics teachers’ levels of threat-type (versus challenge-type) stress, rooted in the biopsychosocial (BPS) model of challenge and threat; (2) testing a path model linking mathematics teachers’ daily threat-type stress responses to teacher effectiveness (implementation of deeper learning practices) and retention; and (3) identifying the administrator-level, classroom-level, and teacher-level factors that are most associated with teachers’ threat-type (vs. challenge-type) stress responses, and that are therefore potential targets for intervention.

The intellectual merit of the project comes from its application of insights from the most recent scientific advances in the affective science of stress to the problem of mathematics teacher stress and coping, and the identification of ambulatory (sensors/monitors) and passive measures of teacher stress responding. Measures of stress developed and validated in the project will map teachers’ stress responses onto classroom teaching and learning processes, and investigate teacher retention and effectiveness.

The broader impacts come from practical insights about how to improve teacher retention and effectiveness in high-need districts by addressing STEM teacher stress, and from the development of measures and scoring algorithms that can be used widely by researchers and practitioners. This Track 4: Noyce Research project is supported through the Robert Noyce Teacher Scholarship Program (Noyce).

The Noyce program supports talented STEM undergraduate majors and professionals to become effective K-12 STEM teachers and experienced, exemplary K-12 teachers to become STEM master teachers in high-need school districts. It also supports research on the effectiveness and retention of K-12 STEM teachers in high-need school districts.

This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.