AI + Ethics Curricula for Middle School Youth: Lessons Learned from Three Project-Based Curricula
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40593_2022_Article_298.pdf
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2.94 MB
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Adobe PDF
Checksum (MD5)
95b40475372d221f91665f056812c09d
Author(s)
Williams, Randi
Ali, Safinah
Devasia, Nisha
DiPaola, Daniella
Hong, Jenna
Kaputsos, Stephen P.
Jordan, Brian
Breazeal, Cynthia
Date Issued
August 1, 2022
Publisher
Springer New York
Citation
Williams, Randi, Ali, Safinah, Devasia, Nisha, DiPaola, Daniella, Hong, Jenna et al. 2022. "AI + Ethics Curricula for Middle School Youth: Lessons Learned from Three Project-Based Curricula."
Version
Final published version
Abstract
Abstract
Artificial Intelligence (AI) is revolutionizing many industries and becoming increasingly ubiquitous in everyday life. To empower children growing up with AI to navigate society’s evolving sociotechnical context, we developed three middle school AI literacy curricula: Creative AI, Dancing with AI, and How to Train Your Robot. In this paper we discuss how we leveraged three design principles—active learning, embedded ethics, and low barriers to access – to effectively engage students in learning to create and critique AI artifacts. During the summer of 2020, we recruited and trained in-service, middle school teachers from across the United States to co-instruct online workshops with students from their schools. In the workshops, a combination of hands-on unplugged and programming activities facilitated students’ understanding of AI. As students explored technical concepts in tandem with ethical ones, they developed a critical lens to better grasp how AI systems work and how they impact society. We sought to meet the specified needs of students from a range of backgrounds by minimizing the prerequisite knowledge and technology resources students needed to participate. Finally, we conclude with lessons learned and design recommendations for future AI curricula, especially for K-12 in-person and virtual learning.
MIT Department
Massachusetts Institute of Technology. Media Laboratory
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Creative Commons Attribution
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DOI of Published Version
https://doi.org/10.1007/s40593-022-00298-y
