
Chris Dede
Harvard University
Chris Dede is a Senior Research Fellow at the Harvard Graduate School of Education and was for 22 years its Timothy E. Wirth Professor in Learning Technologies. His fields of scholarship include emerging technologies, policy, and leadership. From 2001-2004, he was Chair of the HGSE department of Teaching and Learning. In 2007, he was honored by Harvard University as an outstanding teacher, and in 2011 he was named a Fellow of the American Educational Research Association. In 2023 he was named a Fellow of the Online Learning Consortium and in 2024 he was named a Scholar of the Immersive Learning Research Network.
Chris is a Co-Principal Investigator and Associate Director for Research of the NSF-funded National Artificial Intelligence Institute in Adult Learning and Online Education. In 2020 Chris co-founded the Silver Lining for Learning initiative (https://silverliningforlearning.org). His most recent co-edited books include: Teacher Learning in the Digital Age: Online Professional Development in STEM Education; Virtual, Augmented, and Mixed Realities in Education; Learning engineering for online education: Theoretical contexts and design-based examples; and The 60-Year Curriculum: New Models for Lifelong Learning in the Digital Economy.
报告主题
Complementing Human Minds with Digital Brains: GenAI and Higher Order Thinking Development
内容简介
While many forecasts chart an evolution of artificial intelligence (AI) in taking human jobs, more likely is a future where AI changes the division of labor in most work-roles, driving a need for workforce development to shift towards uniquely human skills. The global economy is moving into an era of Intelligence Augmentation, where the judgement and decision-making skills of humans are enhanced by the reckoning skills (e.g. calculations, analysis of multidimensional information, predictions) of computers or machine intelligence. Persons and machines work synergistically together to be better than their individual abilities. This framework implies that learning knowledge, skills, and dispositions for work should increasingly prioritize capability building of higher order thinking, creativity, and applied wisdom about contexts and cultures—at the expense of developing some reckoning skills that AI will assume.
In particular, creativity is defined as the ability to transcend conventional ideas to create novel and valuable outputs. Creative thinking drives innovation and addresses global challenges, advances industries, and is essential for overall societal progress. Human creativity can be amplified through collaboration with AI systems, but such collaboration must be designed thoughtfully to avoid unethical or plagiaristic outcomes.
To aid the development of higher order thinking, machine learning (ML) could be used to help “engineer” learning, by applying evidence-based strategies to the continual re-design of performance-based simulation experiences to optimize their effectiveness and efficiency. This will enable developing diagnostic/formative longitudinal assessments of judgement that complement our current high-stakes tests centered on reckoning.
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