Opportunities and Challenges of Generative AI in STEAM Education: A Thematic Co-occurrence Network Analysis of Primary and Secondary School Leaders’ Perspectives

Abstract Science, technology, engineering, arts, and mathematics (STEAM) education promotes interdisciplinary learning and holistic skill development. Generative artificial intelligence (GAI), with its advanced content generation capabilities, presents both remarkable potential and critical challenges for enhancing STEAM curriculum design and pedagogical practices. Understanding school leaders’ perspectives on GAI in STEAM is essential, as they shape GAI integration policies within schools. This study explored their perceived opportunities and challenges in integrating GAI into STEAM through AI literacy and Unified Theory of Acceptance and Use of Technology (UTAUT) lens. Semi-structured interviews were conducted with 69 school leaders from 36 Hong Kong primary and secondary schools, with data analyzed through a thematic co-occurrence network analysis. We identified nine opportunity themes (expanding STEAM’s scope, supporting teaching content, material preparation, learning activities, assessment, personalized learning, students’ special needs, teacher professional development, and administrative efficiency) and nine challenge themes (academic, accuracy, and ethical concerns, underprepared teachers and students, teacher shortages, unequal GAI access, and concerns of human roles and job displacement). Network analysis revealed strong interconnections between theme pairs, with GAI-assisted learning activities being a dominant opportunity linked to academic concerns, underprepared teachers and students, while underprepared teachers being a key concern linked to expanding STEAM’s scope, GAI-assisted learning activities, and underprepared students. Findings highlight concerns, such as lacked pedagogical integration in teachers’ GAI training, and the importance of improving GAI literacy for STEAM teachers. We recommend clear ethical guidelines and tailored, pedagogy-focused GAI training for schools and policymakers, navigating the GAI-related transformation of STEAM education.

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Publication Details

Journal
Technology Knowledge and Learning
Published
2026-05-16
DOI
https://doi.org/10.1007/s10758-026-09976-5
Primary Topic
Teaching and Learning Programming
Type
article
Field-Weighted Citation Impact
0.00
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article

Opportunities and Challenges of Generative AI in STEAM Education: A Thematic Co-occurrence Network Analysis of Primary and Secondary School Leaders’ Perspectives

Jiaqi Xu, SIYOU WU, Shihui Feng
Technology Knowledge and Learning
Teaching and Learning Programming
article

Opportunities and Challenges of Generative AI in STEAM Education: A Thematic Co-occurrence Network Analysis of Primary and Secondary School Leaders’ Perspectives

Jiaqi Xu, SIYOU WU, Shihui Feng
article en

Abstract

Abstract Science, technology, engineering, arts, and mathematics (STEAM) education promotes interdisciplinary learning and holistic skill development. Generative artificial intelligence (GAI), with its advanced content generation capabilities, presents both remarkable potential and critical challenges for enhancing STEAM curriculum design and pedagogical practices. Understanding school leaders’ perspectives on GAI in STEAM is essential, as they shape GAI integration policies within schools. This study explored their perceived opportunities and challenges in integrating GAI into STEAM through AI literacy and Unified Theory of Acceptance and Use of Technology (UTAUT) lens. Semi-structured interviews were conducted with 69 school leaders from 36 Hong Kong primary and secondary schools, with data analyzed through a thematic co-occurrence network analysis. We identified nine opportunity themes (expanding STEAM’s scope, supporting teaching content, material preparation, learning activities, assessment, personalized learning, students’ special needs, teacher professional development, and administrative efficiency) and nine challenge themes (academic, accuracy, and ethical concerns, underprepared teachers and students, teacher shortages, unequal GAI access, and concerns of human roles and job displacement). Network analysis revealed strong interconnections between theme pairs, with GAI-assisted learning activities being a dominant opportunity linked to academic concerns, underprepared teachers and students, while underprepared teachers being a key concern linked to expanding STEAM’s scope, GAI-assisted learning activities, and underprepared students. Findings highlight concerns, such as lacked pedagogical integration in teachers’ GAI training, and the importance of improving GAI literacy for STEAM teachers. We recommend clear ethical guidelines and tailored, pedagogy-focused GAI training for schools and policymakers, navigating the GAI-related transformation of STEAM education.

Technology Knowledge and Learning
The Ohio State University (US), University of Hong Kong (HK)
Quality Education
Openalex Percentile: Top 2%
Teaching and Learning Programming
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