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International Journal of Computing and Artificial Intelligence

Impact Factor (RJIF): 5.57, P-ISSN: 2707-6571, E-ISSN: 2707-658X
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2025, Vol. 6, Issue 2, Part D

Co-Teaching in STEAM education: A theory-driven alignment framework for transdisciplinary learning with responsible AI integration


Author(s): Markasioti Evangelia and Constantina Corazon Argyrakou

Abstract: This article proposes the Co-Teaching and STEAM Alignment Framework (CTSAF), a design framework that aligns established co-teaching models with the transdisciplinary, inquiry-driven, and creative character of STEAM education. The study follows a theoretical design using an integrative synthesis consistent with a hybrid model of concept development to consolidate foundations from constructivist and sociocultural traditions and extend them with insights from distributed cognition. CTSAF specifies when and why particular configurations add pedagogical value in mixed-attainment classrooms and how teachers can orchestrate them across an inquiry cycle. Its architecture comprises four components: principled definitions of quality in STEAM education (inclusivity, collaboration, innovation, and inquiry), a structural layer for roles, task and space-time organisation and formative assessment, a repertoire of conditionally selected adaptations of co-teaching models, and a lightweight evidence strategy with observable indicators of participation equity, collaborative reasoning, creative iteration, and inquiry progress. Enactment is organised as a concise cycle of planning, orchestration, facilitation, reflection, and iteration that keeps workload tractable while supporting disciplined improvement. Within a sociotechnical view of classrooms, Artificial Intelligence is positioned as an educative medium that broadens access, representation, and formative feedback under teacher oversight and transparent quality criteria. The framework provides a practical grammar for curriculum design, classroom practice, and professional learning; it clarifies boundary conditions such as time constraints and resource variability; and it establishes an agenda for empirical studies on implementation fidelity and learner outcomes in STEAM education.

DOI: 10.33545/27076571.2025.v6.i2d.209

Pages: 293-307 | Views: 180 | Downloads: 50

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International Journal of Computing and Artificial Intelligence
How to cite this article:
Markasioti Evangelia, Constantina Corazon Argyrakou. Co-Teaching in STEAM education: A theory-driven alignment framework for transdisciplinary learning with responsible AI integration. Int J Comput Artif Intell 2025;6(2):293-307. DOI: 10.33545/27076571.2025.v6.i2d.209
International Journal of Computing and Artificial Intelligence

International Journal of Computing and Artificial Intelligence

International Journal of Computing and Artificial Intelligence
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