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A presentation by Roger Azevedo, titled "Foundations and Vision for MetaLearn: A Center for Human-Machine Symbiosis in AI in Education."
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Foundations and Vision for MetaLearn: A Center for Human-Machine Symbiosis in AI in Education

115 Erickson Hall 620 Farm Lane, E. Lansing, MI

  Roger Azevedo is a candidate for the Center in Education and Emerging Technologies: Research and Community Engagement (AI and Education) DirectorĀ position. This will be a joint appointment in the Colleges of Education and Natural Science. Azevedo is a Professor in the School of Modeling Simulation and Training at the University of Central Florida. Heā€¦ Read More »

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AI and Education Research Mixer

Wharton Center 750 E. Shaw LN, East Lansing

The Office of Research and Innovation is hosting an upcoming research mixer in collaboration with the College of Education titled ā€œAI and Education Research Mixerā€ on May 7, from 2:00-4:00 p.m. at the Wharton Center. This event will have a series of flash talks that explore the ways AI can enhance learning environments, support theā€¦ Read More »

As part of the Teaching & Learning with Generative AI series, this session will explore "Generative AI and Advanced Science Learning for Real-world Knowledge Application."
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Teaching & Learning with Generative AI Series

Virtual on Zoom

This talk will explore the broader applications of generative AI in education, focusing on how it can create dynamic, personalized and multi-perspectival learning environments that foster deeper understanding and knowledge transfer. It also presents a research study examining how AI-driven, case-based learning, grounded in Cognitive Flexibility Theory (CFT), compares to traditional linear methods in helpingā€¦ Read More »

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CREATE for STEM Presentation – “AI for Smarter Science Assessment”

CREATE for STEM Seminar Space 620 Farm Ln, East Lansing, MI

This presentation demonstrates how AI can revolutionize the scoring and interpretation of student data from science assessments through two studies. Study 1 investigates automated scoring of object-based models depicting particle behaviors and macroscopic properties to assess student understanding of the structure and properties of matter. By extracting key features from the models and correlating themā€¦ Read More »