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In the next 50 years, the rise of computing and artificial intelligence (AI) will transform our society and it is clear that students will be forced to engage with AI in their careers. Currently, the United States does not have the infrastructure or capacity in place to support the teaching of AI in the K-12 curriculum. To deal with the above challenges, we introduce the use of visual media as a key bridge technology to engage students in grades 6-8 with AI topics, through a recently NSF funded ITEST program, labeled ImageSTEAM. Specifically, we focus on the idea of a computational camera, which rethinks the sensing interface between the physical world and intelligent machines, and enables students to ponder how sensors and perception fundamentally will augment science and technology in the future. Our 1st set of workshops (summer 2021) with teachers and students were conducted virtually due to recent pandemic, and the results and experiences will be shared and discussed in the conference. 

As part of a professional development experience, inservice teachers were provided with lessons and activities emphasizing computer vision. Lessons focused on image processing, machine learning for visual data, and applications in robotics and visual media. Personal Construct Theory (Kelly, 1955) was used to answer the following research question: After middle school teachers engaged in professional development emphasizing computer vision, what changes in thinking occurred in relation to computer vision? Results showed changes in thinking in the form of a more refined understanding of computer vision and its role in STEM education.