AI Instructional Framework:

This article presents an innovative AI Instructional Framework that comprehensively explores the diverse interactions between human and artificial intelligence (AI) agents in educational settings. As AI technologies continue to evolve rapidly, their integration into education offers unprecedented opportunities to enhance teaching and learning experiences. Through a systematic examination of various learning scenarios, this framework provides a nuanced understanding of how AI can be leveraged to support and transform educational practices.Our research employs a scoping review methodology to map the current landscape of AI applications in education. The framework categorizes educational interactions into four main types: Traditional Teaching & Learning, Adaptive Instruction, Advanced Simulations, and Pedagogical Collaboration. Within each category, we explore multiple subtypes of interactions, ranging from human-to-human to fully simulated AI-to-AI scenarios.Key findings highlight the potential of AI to enhance educational experiences through personalized learning, real-time feedback, and adaptive instruction. The framework demonstrates how AI can support pedagogical research by enabling the creation of controlled, simulated environments for testing innovative teaching methodologies. Furthermore, it illustrates the role of AI in facilitating teacher development through virtual training environments and collaborative instructional tools.Importantly, this study emphasizes the critical balance between human and AI interactions in learning environments. While acknowledging the transformative potential of AI, we argue for its role as a complement to, rather than a replacement for, human instruction. The framework showcases the value of simulations and exploratory learning for both students and educators, highlighting how these tools can foster skill development, critical thinking, and innovative pedagogical approaches.The AI Instructional Framework presented in this article offers a roadmap for understanding and leveraging AI in education while also identifying crucial areas for future research and development. As AI continues to reshape the educational landscape, this framework provides a foundation for thoughtful implementation and ongoing evaluation of AI technologies in learning environments.