Transforming STEM Education in Under-Resourced Contexts: A Conceptual Framework for AI-Supported OEP/RS and Inquiry-Based Learning

Synthesis: This conceptual paper examines design-based practices for implementing AI-supported open educational resources and practices (OEP/RS) to promote inquiry-led STEM teaching in under-resourced contexts. Anchored in the IBL model and the 5E instructional framework, it presents three adaptable teaching scenarios (natural science, technology, mathematics) showing how generative AI creates curriculum-aligned, multilingual, contextually relevant digital simulations — transforming abstract concepts into interactive experiences and helping overcome infrastructural, linguistic, and contextual constraints in rural classrooms.

Key Findings

1. A conceptual framework bridging generative-AI co-design and open pedagogy. The paper establishes a novel framework for using AI-supported OEP/RS to enable inquiry-led STEM teaching without requiring advanced programming.
2. Three adaptable teaching scenarios. Natural science, technology, and mathematics scenarios demonstrate how generative AI tools create curriculum-aligned, multilingual, contextually relevant digital simulations.
3. Overcoming under-resourced constraints. AI-generated simulations transform abstract concepts into interactive experiences, addressing infrastructural, linguistic, and contextual barriers in rural classrooms.
4. A scalable, cost-effective path to equity. The framework offers a pathway for digital inclusion and equitable STEM education, with actionable guidelines for educators to design localized learning objects.

Implications

This paper connects AI-supported inquiry directly to equity in under-resourced contexts. For rural and under-resourced settings, generative AI can lower the cost and skill barrier to producing localized, multilingual inquiry materials — a practical route to digital inclusion. It complements the wiki's AI-in-IBL evidence by focusing on the context and infrastructure dimension, and links open educational practices to responsible, context-sensitive AI deployment.

Connected Concepts

• Inquiry Based Learning
• Generative AI
• STEM Education
• Equity In AI Education
• K 12
• Multilingual Learning
• Instructional Design
• Critical Thinking

Connected Articles

• Jiang Chatgpt Inquiry Steam Review 2026 — ChatGPT for inquiry-based learning in STEAM
• Dai Chatbots Problem Posing Primary 2026 — GenAI chatbots and problem posing in primary science
• Niri Steam AI Literacy Review 2026 — STEAM education for AI literacy
• Young People Learning Generative AI Rapid Review 2026 — GenAI across learners, contexts, cultures

Citation

Botes, W., Kgosi, A., Neethling, S., Mahlo, L., & Zondi, M. F. (2026). Transforming STEM education in under-resourced contexts: a conceptual framework for AI-supported OEP/RS and inquiry-based learning. International Journal of Educational Qualitative Quantitative Research, 5(1), 1–14.