§ Research
Studying the Role AI in classrooms
Our research braids learning sciences, learning analytics, AI, and human-centered design. We work with teachers and students, audit the systems that mediate them, and build evidence on what helps and what harms.
§ What drives the work
Problem Statement
Artificial intelligence (AI) exacerbates educational inequities by threatening heterogeneity and promoting cultural and linguistic hierarchies. When used in learners’ contexts that differ from the majority, AI tends to perform significantly worse — leading to biased assessments, perpetuated cultural stereotypes, increased hallucinations, and a failure to capture linguistic and cultural nuance.
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What does TRAIL Lab aim to solve through its research?
TRAIL Lab’s research addresses persistent educational inequities that arise when AI is introduced into classrooms. These inequities often affect historically marginalized students and are rooted in how AI systems are designed, evaluated, and used in real-world educational settings.
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How does TRAIL Lab tackle these challenges?
By working at the intersection of learning sciences, learning analytics, AI, and human-centered design, TRAIL Lab develops new methods to identify and mitigate AI biases. We center the lived experiences of historically marginalized students in our design processes to ensure AI systems reflect their realities.
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What role do teachers play in TRAIL Lab’s research?
A key part of our work is enabling K–12 teachers to use AI in ways that recognize and amplify students’ linguistic and cultural assets. Our tools and methods are designed to support educators in creating more inclusive, responsive, and equitable learning environments.
§ Research areas
Active lines of inquiry.
Funded by Spencer Foundation
Funded by Institute for Diversity Science, UW-Madison
Funded by American Family Funding Initiative
Funded by School of Education, UW-Madison