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Opportunities and Tradeoffs  \nJANUARY 2025  \nAcknowledgments  \nThis brief is a product of the Community for Advancing Discovery Research in Education (CADRE) Committee on AI in STEM Education and Education Research. CADRE connects STEM education researchers funded by the National Science Foundation’s Discovery Research PreK-12 (DRK-12) program to share their methods, findings, results, and products with the research and development community and the greater public, to better inform and impact policy, research and education.  \nSteering Committee:  \nChristopher J. Harris,  \nWestEd  \nEric Wiebe,  \nNorth Carolina State University  \nShuchi Grover,  \nLooking Glass Ventures  \nReviewer:  \nEbony Terrell Shockley,  \nUniversity of Maryland College Park  \nAuthors:  \nJeremy Forest Price,  \nIndiana University Indianapolis  \nShuchi Grover,  \nLooking Glass Ventures  \nSuggested Citation:  \nPrice, J.F., & Grover, S. (2025) . Generative AI in STEM teaching: Opportunities and tradeoffs. Community for Advancing Discovery Research in Education (CADRE) . Education Development Center, Inc.  \nCopyright 2025 by the Community for Advancing Discovery Research in Education (CADRE). This publication is available from CADRE at Education Development Center, Inc, 300 5thAve Waltham MA 02451. [https://cadrek12.org/](https://cadrek12.org/)  \nThe activity was funded by the National Science Foundation, Grant \\# 2100823. Any opinions, findings, and conclusions or recommendations expressed in these materials are those of the author(s) and do not necessarily reflect the views of the National Science Foundation.  \nGenerative AI was not used to create [this brief. Photos from Pexels.com. Credits: Pavel Danilyuk](this brief. Photos from Pexels.com. Credits: Pavel Danilyuk), Vlada Karpovich, Charlotte May, and Max Fischer.  \n2 | Generative AI in STEM Teaching: Opportunities and Tradeoffs  \nTable of Contents  \nForeword..........................................................................................................4  \nIntroduction and Motivation.......................................................................6  \nThe Pre-Generative Roots of AI in STEM Teaching...............................9  \nNew Directions in AI for STEM Teaching.................................................12  \nJustice, Equity, and Inclusion....................................................................13  \nCurricular Decision Making and Lesson Planning.............................15  \nPedagogical Practices and Instruction...................................................17  \nFormative and Summative Assessments..............................................19  \nInservice and Preservice Teacher Learning and Leadership..........21  \nThe Way Forward for AI in STEM Teaching: A Complex Interplay of Opportunities and Risks..........................................................................23  \nOpportunities: Promising Research Trajectories.................................23  \nRisks: A Critical Appraisal of Generative AI’s Promise..................... 27  \nConclusion......................................................................................................30  \nReferences   32  \n3 | Generative AI in STEM Teaching: Opportunities and Tradeoffs  \nForeword  \nBy Christopher J. Harris and Eric Wiebe  \nResearch and development work in artificial intelligence in education (AIED) is wide ranging and rapidly growing in support of all areas of science, technology, engineering, and mathematics (STEM) teaching and learning. With its broad applicability and transformative potential, AIED represents what could arguably be the most fundamentally game-changing technology for education to emerge since the Internet. Building from prior decades of work on artificial intelligence (AI) and AI-based learning and teaching technologies, the recent advances in AIED—especially the leaps in generative AI—are pushing us to reimagine what is possible for STEM teaching a","cbCait8IwN7F9AWR","https://ap.wps.com/l/cbCait8IwN7F9AWR","pdf",552399,45,"English","# Foreword\n# Introduction and Motivation\n# The Pre-Generative Roots of AI in STEM Teaching\n# New Directions in AI for STEM Teaching\n# Justice, Equity, and Inclusion\n# Curricular Decision Making and Lesson Planning\n# Pedagogical Practices and Instruction\n# Formative and Summative Assessments\n# Inservice and Preservice Teacher Learning and Leadership\n# The Way Forward for AI in STEM Teaching: A Complex Interplay of Opportunities and Risks\n# Opportunities: Promising Research Trajectories\n# Risks: A Critical Appraisal of Generative AI’s Promise\n# Conclusion\n# References","[{\"question\":\"What is the main focus of the brief on generative AI in STEM teaching?\",\"answer\":\"The brief examines opportunities and tradeoffs of generative AI and broader AIED advances for STEM teaching and learning, including both transformative potential and concerns about bias and everyday practice.\"},{\"question\":\"How does the brief address justice, equity, and inclusion?\",\"answer\":\"It highlights how AI breakthroughs may perpetuate long-standing biases, placing justice, equity, and inclusion among the core considerations for using AI in K–12 STEM education.\"},{\"question\":\"What areas does the brief cover for classroom and educator practice?\",\"answer\":\"It covers curricular decision-making and lesson planning, pedagogical practices and instruction, formative and summative assessments, and inservice and preservice teacher learning and leadership.\"}]","Generative AI in STEM Teaching: Opportunities and Tradeoffs - January 2025 | PDF",1792049660,113]