About

The K-12 engineering and technology education sector faces rapid curricular shifts due to the acceleration of artificial intelligence, forcing districts to update instructional strategies. Deploying new technologies into classrooms can incur high implementation costs and strain institutional capacity when teachers are required to integrate complex tools without targeted pedagogical frameworks, risking instructional fragmentation and teacher burnout. The major challenge of the research group is to systematically analyze how K-12 technology educators can utilize advanced computational tools to streamline curriculum development and optimize classroom management. Having a structured framework for teacher-AI collaboration will increase the quality of project-based STEM instruction, reduce teacher administrative burdens, and minimize inequitable implementation across diverse school environments. The stakeholders are K-12 school districts, represented by superintendents, building principals, engineering and technology classroom teachers, university researchers, and the primary and secondary students within STEM pipelines. To the research team, the context is to evaluate pedagogical interventions that position intelligent systems as co-designers and instructional partners, reducing the operational strain on educators by balancing human-centric pedagogy with autonomous technical workflows.