Perceptual and Embodied Learning in the Context of Educational Technologies
My research intersects core areas of the learning sciences (i.e., cognitive and educational psychology, mixed methods) to study student reasoning and learning in mathematics in the context of educational technologies. I also study the meta-science behind this process!
Informed by theories of perceptual learning and embodied cognition, I investigate how even the smallest details of students' learning environments can shape performance and learning in mathematics, ultimately aiming to provide recommendations to improve open-access digital materials and educational technologies.
In my second line of research, I enjoy collaborating with data scientists to explore the meta-science behind conducting research in the context of educational technologies. For instance, how can and should methods across the learning sciences (e.g., machine learning, multi-level modeling) be used in different contexts? And when and how do we need to account for the nested structure of data in online education research?
Have you thought about how the non-mathematical ways that problems are presented influences the ways that students process information and make calculations? Subtle changes such as the spacing between symbols, the use of parentheses to group terms, and symbol font color (coming soon) all impact how students attend to and act on math expressions! Check out our friendly rapid community report for a quick introduction.