UPDATES Sign up to receive periodic updates from the Student Experience Research Network.
Sidney D’Mello is a Professor in the Institute of Cognitive Science and the Department of Computer Science at the University of Colorado Boulder. His research lies at the intersection of the cognitive, affective, computing, and learning sciences. Specific interests include affective computing, attentional computing, intelligent learning environments, speech and language processing, human-computer interaction and computational models of cognition.
D’Mello conducts basic research on affective and cognitive states (e.g., confusion, boredom, mind wandering) during complex learning and problem solving, develops real-time computational models of these states, and integrates these models in learning environments that intelligently respond to learners’ mental states. He is interested in studying how beliefs about agency (e.g., self-efficacy and mindset) and behavioral dispositions (e.g., self-control, diligence) influence how students regulate emotions and behavior during learning. He develops web-based performance tasks that enable researchers to measure non-cognitive competencies quickly, reliably, inexpensively, and at scale.
D’Mello holds a doctorate in computer science and master’s degree in mathematical sciences from University of Memphis, and a bachelor’s degree in electrical engineering from Christian Brothers University.
Visit our library to view Sidney D’Mello's papers related to learning mindsets.
- Analytic and computational approaches to uncover teacher practices that foster positive identity and equity in engagement and learning for middle school mathematics students
- How does high school extracurricular participation predict bachelor’s degree attainment? It is complicated
- Language as thought: Using natural language processing to model noncognitive traits that predict college success
- Language as thought: Using natural language processing to investigate mindsets, learning environments, and college success
- A brief behavioral measure of frustration tolerance predicts academic achievement immediately and two years later
- A big biodata approach to mindsets, learning environments, and college success
- Advanced, analytic, automated (AAA): Measurement of engagement during learning
- Student Experience Research Network’s portfolio of research on mindsets and the learning environment
- When students zone out, zero in on their desire to “matter” in life
- How do Learning Environments Shape Student Mindsets?
- Lessons from the first round of the Mindsets & the Learning Environment Initiative