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AI is beginning to transform every aspect of society. With the dramatic increases in AI, K-12 students need to be prepared to understand AI. To succeed as the workers, creators, and innovators of the future, students must be introduced to core concepts of AI as early as elementary school. However, building a curriculum that introduces AI content to K-12 students present significant challenges, such as connecting to prior knowledge, and developing curricula that are meaningful for students and possible for teachers to teach. To lay the groundwork for elementary AI education, we conducted a qualitative study into the design of AI curricular approaches with elementary teachers and students. Interviews with elementary teachers and students suggests four design principles for creating an effective elementary AI curriculum to promote uptake by teachers. This example will present the co-designed curriculum with teachers (PRIMARYAI) and describe how these four elements were incorporated into real-world problem-based learning scenarios.
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Design Considerations for Evaluating Middle School AI Knowledge
K-12 students need to understand technical and ethical knowledge about Artificial Intelligence to utilize ubiquitous AI-powered technologies responsibly. Recent studies have explored ways to teach AI to K-12 students effectively, but little is known about ways to assess their learning. In this study, we describe how five computer science teachers from urban and rural Georgia school districts designed, adapted, and implemented assessments in their classrooms while teaching a middle school elective course aligned with the Five Big Ideas of AI. Analyzing artifacts from 201 students, we explore the efficacy of different assessment instruments co-designed with teachers, measuring students’ understanding of sensors and the societal impacts of autonomous vehicles. We suggest design considerations for AI knowledge assessments to meet the needs and challenges in diverse classroom contexts.
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- Award ID(s):
- 2049029
- PAR ID:
- 10684773
- Editor(s):
- Rajala, Antti; Cortez, Arturo; Hofmann, Riika; Jornet, Alfredo; Lotz-Sisitka, Heila; Markauskaite, Lina
- Publisher / Repository:
- Repository of the International Society of Learning Sciences
- Date Published:
- Page Range / eLocation ID:
- 1978 to 1982
- Subject(s) / Keyword(s):
- Artificial Intelligence K-12 education middle school curriculum design
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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- Free Publicly Accessible Full Text
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Accepted Manuscript
- Conference Paper:
- https://doi.org/10.22318/icls2025.318374
