Foundations of Autonomous Vehicles: A Curriculum Model for Developing Competencies in Artificial Intelligence and the Internet of Things for Grades 7–10

Authors

  • Elham Buxton University of Illinois at Springfield
  • Elahe Javadi Illinois State University
  • Matthew Hagaman Illinois State University

DOI:

https://doi.org/10.1609/aaai.v38i21.30375

Keywords:

Artificial Intelligence, K-12 Education, Robotics, Internet Of Things

Abstract

A few states (e.g., Maryland, Georgia, and Florida) have initiated efforts to incorporate artificial intelligence outcomes in K-12 education but others are still relying on informal spaces for learning and literacy in this area. In this manuscript, we share the curriculum and content of an informal effort focused on students in grades 7-10. We combined artificial intelligence competencies with Internet of Things skills to enable meaningful learning covering all Five Big Ideas in AI. In our one-week summer camp, students experimented with perceptions by working with vision, infrared, and ultrasonic sensors. They learned about representation through work with neural network playgrounds. Students engaged in supervised learning of an image processing model and used the model to control the actions of a robot car. Natural interactions and societal impacts were assessed as students observed the robot car's behavior. Results demonstrate that our curriculum was successful in achieving its objectives. Excluding the robot car kit, the curriculum was created using free platforms and tools. This program could be replicated in informal settings by any educator or collaborator with a computer science background. This paper describes our summer camp curriculum, its components and their implementation, the lessons learned, and potential future enhancements.

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Published

2024-03-24

How to Cite

Buxton, E., Javadi, E., & Hagaman, M. (2024). Foundations of Autonomous Vehicles: A Curriculum Model for Developing Competencies in Artificial Intelligence and the Internet of Things for Grades 7–10. Proceedings of the AAAI Conference on Artificial Intelligence, 38(21), 23276-23284. https://doi.org/10.1609/aaai.v38i21.30375