Founder and CEO of Active Learning Sciences, Inc. / Professor Emeritus, Harvard University
Dr. Kosslyn is the founder of Active Learning Sciences, Inc., and is Lindsley Professor Emeritus at Harvard University. He previously was the founder and President of Foundry College, after having served as the Founding Dean and Chief Academic Officer of Minerva University. Before that, he was the director of the Center for Advanced Study in the Behavioral Sciences and Professor of Psychology at Stanford University. Prior to that, he was chair of the Department of Psychology, Dean of Social Science, and John Lindsley Professor of Psychology at Harvard University. Kosslyn's research has focused on the science of learning, the nature of visual cognition, and visual communication; he has published 14 books and over 350 papers on these topics. He has received numerous honors, including the National Academy of Sciences Initiatives in Research Award, a Guggenheim Fellowship, three honorary Doctorates and election to the American Academy of Arts and Sciences.
Workshop
[Closing Fireside Chat]
Quality, Scale, and Cost: The Potential for Individualized Instruction in an AI-enabled World
Presentation
[Featured Presentation]
Dynamic Personalized Learning: Using AI to Leverage the Science of Learning
We have used Generative Artificial Intelligence (AI) to provide dynamic, personalized learning. This educational method is "dynamic" not only because the AI provides feedback in real time, but also because it quickly adjusts the level, pace, and content as appropriate. This education is "personalized" because the AI adapts the content to fit each individual learner's needs, interests, preferences, and background. For instance, analogies and examples are tailored to be relevant for each learner's hobbies and interests. And such education focuses on "learning" by drawing on the science of learning to organize the material, present it effectively, and provide active learning exercises. Dynamic Personalized Learning rests on a two-phase approach: First, the AI uses uploaded learning objectives and rubrics to conduct a diagnostic interview with the individual learner, which then allows it to provide a personalized tutorial to help each individual acquire the appropriate knowledge. Second, the AI then provides an active learning exercise, which leads the learner to apply the material in a specific way. During both phases, the AI monitors the learner’s performance and adjusts instruction accordingly. Dynamic Personalized Learning can be used in a hybrid context, where learners work with the AI individually, but meet regularly as a group to use their new knowledge and skills in group projects, which encourages deeper learning, promotes bonding, and enhances retention.