AUTHOR=Leon Cristo , Lipuma James , Oviedo-Torres Xavier 

TITLE=Artificial intelligence in STEM education: a transdisciplinary framework for engagement and innovation

JOURNAL=Frontiers in Education

VOLUME=Volume 10 - 2025

YEAR=2025

URL=https://www.frontiersin.org/journals/education/articles/10.3389/feduc.2025.1619888

DOI=10.3389/feduc.2025.1619888

ISSN=2504-284X

ABSTRACT=IntroductionArtificial intelligence (AI) has reshaped STEM education by influencing instructional design, learner agency, and ethical frameworks. However, the integration of AI into educational ecosystems raises critical questions regarding pedagogical coherence, assessment reform, and algorithmic ethics.MethodsThis study conducted a systematic review of 41 peer-reviewed publications to examine how AI has been integrated into STEM educational ecosystems. The review focused on peer-reviewed studies published between 2020 and 2025 that addressed AI applications in STEM education, transdisciplinary approaches to AI integration, and the ethical challenges inherent in AI-driven learning environments. A transdisciplinary communication (TDC) framework guided the synthesis of findings. The review followed PRISMA protocols for transparency and utilized Nvivo, Excel and VOSviewer to support thematic coding and bibliometric mapping.ResultsThe analysis identified three emergent themes: (1) the evolving role of student agency in AI-enhanced learning, (2) shifts in assessment paradigms toward adaptive, AI mediated models, and (3) ethical tensions surrounding algorithmic transparency, equity, and automation in pedagogical design. Divergent disciplinary perspectives were noted, with some emphasizing efficiency and other prioritizing inclusive access and epistemic reflexivity.DiscussionDrawing on the Universal Design for Learning (UDL) framework and trustworthy AI principles, this review offers a critical lens on inclusivity and design ethics in AI-mediated learning environments. The results offer a conceptual foundation and a set of actionable strategies for institutions, educators, and policymakers seeking to implement AI technologies in ways that are ethically sound, inclusive, and informed by epistemic plurality in STEM education.