Improving Student Learning While Decreasing Bias in Teaching Through Simulation

This project aims to contribute to a more just and equitable society in the future by encouraging teachers to identify, reflect on, and correct revealed biases. This three-year project will implement a scalable model for developing equitable, culturally responsive teaching practices through a simulated teaching environment. The project will identify best practices to help teachers recognize and mitigate implicit biases that often impact student success. Bias reduction in teaching practices is crucial for enabling future leaders to achieve their highest innate and positively nurtured potential. The COVID-19 pandemic has highlighted disparities in learning and emphasized the importance of socio-emotional stability for the long-term well-being of students and teachers.

The project team will iteratively develop and test a Teaching without Bias curriculum and add an AI-driven set of bias reduction tools to existing simulation instruction modules. The project will use data-driven decisions to confirm the feasibility of a three-phase approach to reducing bias in teaching. Through a randomized-assignment experimental design, the project will also confirm whether any of the three phases alone, in sequence, or in combination, is most effective. Through a simulated teaching environment, the project outcomes will lead to a model for developing equitable, culturally responsive teaching practices. The project will use the simulated teaching environment to develop and refine computational models that lead to improved teaching practices and contribute to the learning sciences.

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.