Collaborative Research: Empowering Teachers to Integrate Computational Thinking into Middle School Classrooms

Providing students with exposure to high quality CT activities within science classes has the possibility to create transformative educational experiences that will prepare students to harness the power of CT for authentic problems. By building upon foundational research in human-AI partnership for classroom support and effective practices for integrating computational thinking (CT) in science, this collaborative research project will advance understanding of how to empower teachers to lead computationally-enriched science activities with adaptive pedagogical tools. This project will also advance knowledge of how to prepare teachers to engage in AI-augmented teaching and human-AI partnerships for classroom support. The project will involve three yearly cycles of teacher professional development, iterative co-design, development of an AI tool (called TRACES), and classroom implementation of the designed learning activities and AI tool within middle school classrooms. Using state-of-the-art AI methods, real-time classroom data will be used to help teachers modify pacing, help specific students in need, and identify students who can act as peer mentors. The team’s prior research has shown that teachers can be successfully prepared to use and teach with AI in their classrooms, allowing them to notice and respond to these classroom and individual needs. The project will leverage these recent advances to transform the landscape of CT in science education. The project will co-design and test 28 new CT-integrated science activities with teachers and provide learning experiences to 84 science teachers by developing and implementing professional development for CT in science. The project will also iteratively co-design and test the proposed AI-powered support toolset that aids teachers in making data-driven instructional decisions during these activities. The AI-powered toolset co-designed with teachers will provide real-time information to support their ability to notice and respond to student work. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.