MAKASSAR — Two researchers from Universitas Negeri Makassar, Faathir Almur and Munawwarah, have published a study mapping the specific needs of high school chemistry teachers in integrating generative artificial intelligence into classroom instruction. The research, published in 2026, emphasizes that educators lack sufficient institutional support and practical training tailored to the unique pedagogical demands of chemistry education. The findings suggest that professional development must shift toward systematic and collaborative frameworks to effectively close the gap between rapid technological advancement and teacher readiness.
The pedagogical challenge in chemistry stems from its abstract nature, where students must simultaneously comprehend macroscopic, submicroscopic, and symbolic representations, such as molecular interactions and chemical reaction mechanisms. This complexity creates a high cognitive load, often leading to conceptual misconceptions among learners. Generative AI tools such as ChatGPT, Gemini, and Copilot offer significant potential to alleviate this burden by generating interactive visual aids and personalized learning materials, provided teachers know how to integrate them meaningfully.
The study utilized a quantitative research design with a cross-sectional survey to objectively assess the discrepancies between teachers' current proficiency and the perceived importance of AI competencies. An online questionnaire was completed by 43 active high school chemistry teachers from South Sulawesi and West Sulawesi provinces. Data analysis was executed using the Borich Needs Assessment Model to calculate Mean Weighted Discrepancy Scores, allowing the researchers to determine and rank training priorities based on actual field requirements.
The Borich model analysis identified the top ten urgent training priorities for chemistry educators. Establishing an AI learning community ranked first, followed by AI ethics training, chemical reaction simulation techniques, institutional availability of AI training, and general AI usage instruction. Other high-priority items included pedagogical AI integration training, chemistry concept visualization, practical workshops, evaluating AI output accuracy, and developing strategies to supervise and control students' AI usage in the classroom.
Conversely, competencies regarding basic digital technology proficiency, adaptability to new technologies, and a general understanding of AI plagiarism risks recorded the lowest discrepancy scores. This indicates that the surveyed chemistry teachers already possess a solid baseline of digital literacy and ethical awareness, likely enhanced by their experience with online learning platforms during the pandemic. Educators also expressed high confidence in using AI for straightforward tasks, such as generating chemistry test questions, reducing the urgency for introductory-level technical workshops.
The implications of this research are highly relevant for education policymakers and school administrators. Successful AI integration requires shifting from short-term, general tech workshops toward long-term, subject-specific professional development embedded within communities of practice. Furthermore, institutions must address systemic barriers by improving school infrastructure, setting clear technological guidelines, and supporting collaborative teacher networks. Ultimately, while AI serves as a powerful cognitive tool, the teacher's role remains indispensable as a critical validator of AI-generated content to maintain educational quality.
Author Profile:
Faathir Almur is a researcher in Universitas Negeri Makassar.
Munawwarah is a researcher in Universitas Negeri Makassar.
Research Source:
Mapping Teachers Need for Generative AI Integration in Chemistry Education: A Needs Assessment Study, East Asian Journal of Multidisciplinary Research (EAJMR), 2026.
DOI: https://doi.org/10.55927/eajmr.v5i5.92
URL: https://journaleajmr.my.id/index.php/eajmr
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