Engagement & Learning

Engagement & Learning

Psychology and educational research have long created a sharp divide between affect and cognition, the hot and the cold of learning. However, the world is not so easily divided, and the two influence each other in important ways over the pathways a learning might follow. Efficacy and self-efficacy are loosely coupled. Interest and opportunity-to-learn are similarly bi-directionally loosely coupled. Through empirical deep dives into the nature of both motivational constructs and learning processes, we build new accounts of learning towards the STEAM disciplines unfolding over the scale of months to years.

Activation Lab

Activation Lab

The Science Learning Activation Lab is a national research and design effort to learn and demonstrate how to activate children in ways that ignite persistent engagement in science learning and inquiry. Led by LRDC and the Lawrence Hall of Science, the ActLab is conducting research to identify the characteristics of late elementary and middle school aged children that are predictive of successful science learning and future participation in science, as well as to design learning environments that promote such outcomes. Our research uncovers the elements of an activated learner, the trajectory of predicted outcomes, and the learning experiences that support or maintain activation. Current theorizing argues for four dimensions of activation: Fascination in science, Valuing science knowledge and ways of thinking, Competency beliefs for science learning situations, and Scientific sensemaking. But ask us about Identity in science, and how this all changes when you consider STEM.

UBelong Collaborative

Ubelong Collaborative

The Ubelong Collaborative seeks to transform STEM course environments to be equitable and inclusive so that every STEM student feels like they belong. We promote belonging and academic equity in STEM through the development, refinement, and validation of customizable social-belonging interventions. My role within the collaborative is to develop quantitive methods for analyzing institutional data to identify which groups of students are experience large levels of inequity in particular course outcomes. I also lead the effort to study the mechanisms by which a customized mindset belonging interventions changes these outcomes.