Neuroscience Applications for Learning (NeurAL) Laboratory is a team of faculty and students who use cognitive and social neuroscience methodologies and technologies to explore how people learn individually and in groups. Our focus is on the learners who exhibit a wide range of attentional and cognitive differences (e.g., inhibitory control, spatial ability, working memory capacity, reading ability etc.) Studies are designed using (or replicating) the authentic learning contexts of the 21st century and produce implications for improving the design and practice of learning and teaching.
Our research has been funded by the National Science Foundation (Science of Learning, Cyberlearning and Future Technologies, GoLife, and Improving Undergraduate STEM Education programs), the National Aeronautics and Space Administration, and the University of Florida (College of Education Research Incentive Fund and UF Research Opportunity Fund). We value collaboration and we would welcome an opportunity to discuss potential projects with you!
We study cognitive dynamics using neurophysiological tools like non-invasive wireless EEG systems with intelligent software as well as a variety of the more traditional indirect methods including think-alouds, secondary task techniques, screen-capture, and server-log data mining techniques.
To gain a deeper understanding of how people learn, we employ a robust eye-tracking platform with custom-built algorithms that allow us to analyze a host of relevant variables – from gaze fixations, to pupil dilations to the temporal distribution of microsaccade production.
We use a variety of paradigms to design and implement measures of learning performance, including summative and formative assessments in traditional formats and using learning analytics tools that collect data on the trends and patterns of learning over time.
Usability is key to the success of any technology. We test usability using both qualitative (e.g., cognitive walk-through) and quantitative methods (e.g., mouse/keyboard interactions, eye tracking, EEG) and offer suggestions for improving information architecture, metaphoric representations and interaction design.