About the MiL·Lab

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The Motivation, Identity, and Learning Lab (MiL·Lab), directed by Tony Perez, Ph.D., researches how students’ expectancies for academic success, perceived values, and perceived costs shape their feelings of motivation, belonging, and persistence. Our goal is practical: translate motivation science into course designs and supports that help diverse students thrive throughout their academic journey.

What We Study

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Our research is guided by Situated Expectancy-Value Theory (SEVT), a motivational framework that emphasizes the role of context in shaping students’ confidence in their abilities and the value they assign to academic tasks. We also examine how identity-relevant barriers and supports shape student motivation across learning environments. Broadly, our work seeks to better conceptualize how motivation and identity development intersect, and how they can promote academic engagement, achievement, and persistence – particularly among students from historically underrepresented groups in STEM disciplines. We build on conceptual and theoretical foundations and apply these insights toward the design of learning environments that foster equity, inclusivity and belonging – where all students can see themselves as capable, valued members of their fields.

What We Build

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MilLab partners with instructors and programs across the country to design and test course-embedded supports and interventions that:

• Increase the perceived value of coursework and connect it to students’ identities and goals
• Lower avoidable costs (e.g., ineffective teaching practices, inflexible expectations and course structure)
• Increase student feelings of self-efficacy, belongingness, and institutional trust and effectiveness
• Improve self-regulated learning skills
• Create identity-safe, feedback-rich classrooms that reduce stereotype-threat cues and increase students’ ability to persist in the face of challenges

Drawing on our profile work, we focus on introductory gateway courses where small changes can shift trajectories.

How We Work

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We have historically used a wide range of methods and samples in our studies. These include large-enrollment course surveys, longitudinal designs, and advanced statistical modeling (e.g., profile and growth analyses), paired with instructor interviews, student focus groups, and ongoing intervention to evaluate what improves engagement, achievement, and persistence.