Board 165: K-12 STEM Teachers’ Perceptions of Artificial Intelligence: A PRISMA-tic Approach (Work-in-Progress)

Daniel Loke; Jeffrey D Radloff; Ibrahim H. Yeter

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Conference: 2024 ASEE Annual Conference & Exposition
Location: Portland, Oregon
Publication Date: June 23, 2024
Start Date: June 23, 2024
End Date: July 12, 2024
Conference Session: Pre-College Engineering Education Division (PCEE) Poster Session
Tagged Division: Pre-College Engineering Education Division (PCEE)
Permanent URL: https://peer.asee.org/46727

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Paper Authors

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Daniel Loke Nanyang Technological University

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Loke Kwong Yan Daniel is a prospective PhD student majoring in Education at the National Institute of Education (NIE) at Nanyang Technological University (NTU) after completing his Masters in Education (Learning Sciences and Technology). Daniel is an active member of Dr. Yeter's Research Team with a keen interest in STEM education and AI literacy. With over a decade of experience teaching STEM to high school and college students, Daniel is deeply passionate about making STEM and AI education relevant and accessible to learners of all ages.

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Jeffrey D Radloff SUNY, Cortland orcid.org/0000-0003-2625-6963

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Dr. Jeffrey Radloff is an Assistant Professor in the Childhood/Early Childhood Education Department at SUNY Cortland, where he teaches elementary science methods, STEM foundations, and critical media literacy courses. He has a background in biology and pre-college engineering education, and he received his Ph.D. in Curriculum and Instruction from Purdue University. Dr. Radloff’s interests are in understanding how to best support pre- and in-service teachers’ integration of interdisciplinary STEM instruction, as well as exploring related instructional variation across classrooms. His current work focuses on chronicling this variation and fostering the development of teachers’ computational thinking using robotics and applications of artificial intelligence.

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Ibrahim H. Yeter Nanyang Technological University orcid.org/0000-0002-0175-2306

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Ibrahim H. Yeter, Ph.D., is an Assistant Professor at the National Institute of Education (NIE) at Nanyang Technological University (NTU) in Singapore. He is an affiliated faculty member of the NTU Centre for Research and Development in Learning (CRADLE) and the NTU Institute for Science and Technology for Humanity (NISTH). He serves as the Director of the World MOON Project and holds editorial roles as Associate Editor of the IEEE Transactions on Education and Editorial Board Member for the Journal of Research and Practice in Technology Enhanced Learning. He is also the upcoming Program Chair-Elect of the PCEE Division at ASEE. His current research interests include STEM+C education, specifically artificial intelligence literacy, computational thinking, and engineering.

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Abstract

Recent technological advancements have led to the emergence of artificial intelligence (AI) applications like Bard and ChatGPT. Consequently, these applications of AI and others have proliferated aspects of daily life. Notably, there is a growing interest in incorporating AI to enhance K-12 science, technology, engineering, and mathematics (STEM) education and research. To be effectively integrated, however, AI usage needs to align with teachers’ existing STEM curriculum and pedagogy. In essence, the extent to which AI will be deployed in future classrooms will heavily depend on teachers' perceptions of its utility within the STEM education context. STEM teachers’ attitudes, expectations, and perceived challenges regarding AI can significantly influence their willingness to adopt AI-integrated instruction approaches. Identifying and categorizing teachers’ beliefs, motivational factors, and areas of concern will provide practical insights for STEM curriculum designers, professional developers, and policymakers. This study investigates these possible directions through a lens of major established models of integrated STEM education. Although extensive research has been done on integrating AI with STEM, work is lacking that translates this concept into concrete entry points for integration. To address this gap, this research uses a systematic literature review (SLR) approach focusing on preservice teachers’ (PSTs’) perceptions of AI in STEM education. Using the PRISMA model, we gathered related empirical, peer-reviewed articles published from 2020 to 2024. Of the 250 initial studies, 26 met our eventual criteria. Content analyses of these surveys revealed several aspects that may be used to further understand PSTs' perspectives on AI's involvement and potential usage in integrated STEM. Firstly, their competency using AI tools appears to greatly influence their attitude toward AI-integrated STEM pedagogy. Second, their perceptions of AI's effectiveness, utility, and ethics seem to significantly impact their willingness to adopt AI for classroom usage. Lastly, research suggests that PSTs recognize both the benefits, like improving student engagement and personalized learning, and the challenges posed by technical difficulties or the complexity of interspersing these technologies in their STEM classrooms. As such, teacher education related to meaningfully using AI tools is an important focus of integrating AI. Teachers must be skilled and confident in using AI tools in their classrooms, while also able to recognize its limitations and potential pitfalls. PSTs, therefore, need access to targeted AI resources and opportunities for application within their STEM pedagogy courses. Meeting these goals means providing teacher educators and researchers with ongoing support to advance the integration of AI into K-12 STEM education. Keywords: STEM education, artificial intelligence, pre-service teacher, systematic literature review

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Loke, D., & Radloff, J. D., & Yeter, I. H. (2024, June), Board 165: K-12 STEM Teachers’ Perceptions of Artificial Intelligence: A PRISMA-tic Approach (Work-in-Progress) Paper presented at 2024 ASEE Annual Conference & Exposition, Portland, Oregon. https://peer.asee.org/46727

TY - CPAPER
AB - Recent technological advancements have led to the emergence of artificial intelligence (AI) applications like Bard and ChatGPT. Consequently, these applications of AI and others have proliferated aspects of daily life. Notably, there is a growing interest in incorporating AI to enhance K-12 science, technology, engineering, and mathematics (STEM) education and research. To be effectively integrated, however, AI usage needs to align with teachers’ existing STEM curriculum and pedagogy. In essence, the extent to which AI will be deployed in future classrooms will heavily depend on teachers&#39; perceptions of its utility within the STEM education context. STEM teachers’ attitudes, expectations, and perceived challenges regarding AI can significantly influence their willingness to adopt AI-integrated instruction approaches. Identifying and categorizing teachers’ beliefs, motivational factors, and areas of concern will provide practical insights for STEM curriculum designers, professional developers, and policymakers. This study investigates these possible directions through a lens of major established models of integrated STEM education. Although extensive research has been done on integrating AI with STEM, work is lacking that translates this concept into concrete entry points for integration. To address this gap, this research uses a systematic literature review (SLR) approach focusing on preservice teachers’ (PSTs’) perceptions of AI in STEM education. Using the PRISMA model, we gathered related empirical, peer-reviewed articles published from 2020 to 2024. Of the 250 initial studies, 26 met our eventual criteria. Content analyses of these surveys revealed several aspects that may be used to further understand PSTs&#39; perspectives on AI&#39;s involvement and potential usage in integrated STEM. Firstly, their competency using AI tools appears to greatly influence their attitude toward AI-integrated STEM pedagogy. Second, their perceptions of AI&#39;s effectiveness, utility, and ethics seem to significantly impact their willingness to adopt AI for classroom usage. Lastly, research suggests that PSTs recognize both the benefits, like improving student engagement and personalized learning, and the challenges posed by technical difficulties or the complexity of interspersing these technologies in their STEM classrooms. As such, teacher education related to meaningfully using AI tools is an important focus of integrating AI. Teachers must be skilled and confident in using AI tools in their classrooms, while also able to recognize its limitations and potential pitfalls. PSTs, therefore, need access to targeted AI resources and opportunities for application within their STEM pedagogy courses. Meeting these goals means providing teacher educators and researchers with ongoing support to advance the integration of AI into K-12 STEM education.
Keywords: STEM education, artificial intelligence, pre-service teacher, systematic literature review
AU - Daniel Loke
AU - Jeffrey D Radloff
AU - Ibrahim H. Yeter
CY - Portland, Oregon
DA - 2024/06/23
PB - ASEE Conferences
TI - Board 165: K-12 STEM Teachers’ Perceptions of Artificial Intelligence: A PRISMA-tic Approach (Work-in-Progress)
UR - https://peer.asee.org/46727
ER -