A Michigan State University researcher is developing a web application that will help educators make their teaching practices more unbiased using data from their own classrooms.
Niral Shah, assistant professor of teacher education, said the innovative tool, called Equity Quantified In Participation, or EQUIP, can be used to code classroom interactions between teachers and students and provide analytic feedback of individual student, demographic and overall classroom patterns.
Because people have a tendency to favor those that look and act like them, teachers may marginalize those that are different, particularly students of color and girls. The app would help them understand, and ultimately address, this issue.
“Teachers don’t currently have a way of getting concrete data on how implicit bias might be affecting their practice,” Shah said.
“We hope to explore how quantitative analytics generated by EQUIP—alongside data on students’ subjective experiences of equity and bias—can support teachers in making their teaching practice more equitable over time."
Shah will work with educators using this tool through research funded by a new fellowship. Recently, he was chosen as a 2017 National Academy of Education/Spencer Postdoctoral Fellow, which will provide $70,000 for up to two years of research to enhance the future of education.
His project, “Reducing the Impact of Implicit Racial and Gender Bias on Mathematics Classroom Discourse,” delves into the biases educators may have.
Once completed, Shah hopes the app can be incorporated into teacher preparation programs and that school districts will adopt the tool during professional development opportunities.
The project is an extension of Shah’s research focus on equity and implicit bias in science, technology, engineering and mathematics, or STEM, education.
