
NSF Org: |
DRL Division of Research on Learning in Formal and Informal Settings (DRL) |
Recipient: |
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Initial Amendment Date: | December 4, 2023 |
Latest Amendment Date: | December 4, 2023 |
Award Number: | 2343693 |
Award Instrument: | Standard Grant |
Program Manager: |
Chia Shen
cshen@nsf.gov (703)292-8447 DRL Division of Research on Learning in Formal and Informal Settings (DRL) EDU Directorate for STEM Education |
Start Date: | December 15, 2023 |
End Date: | November 30, 2025 (Estimated) |
Total Intended Award Amount: | $156,000.00 |
Total Awarded Amount to Date: | $156,000.00 |
Funds Obligated to Date: |
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Recipient Sponsored Research Office: |
633 CLARK ST EVANSTON IL US 60208-0001 (312)503-7955 |
Sponsor Congressional District: |
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Primary Place of Performance: |
2240 Campus Dr EVANSTON IL US 60201-2952 |
Primary Place of
Performance Congressional District: |
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Unique Entity Identifier (UEI): |
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Parent UEI: |
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NSF Program(s): | ITEST-Inov Tech Exp Stu & Teac |
Primary Program Source: |
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Program Reference Code(s): |
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Program Element Code(s): |
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Award Agency Code: | 4900 |
Fund Agency Code: | 4900 |
Assistance Listing Number(s): | 47.076 |
ABSTRACT
Young learners need opportunities to build critical awareness surrounding AI. To rapidly expand inclusive access to AI education, K-12 educators need activities that (a) are low-cost, (b) do not require specialized technology, (c) can be led with little prior knowledge of AI and used in settings with time constraints and competing curricular needs, and (d) have clear learning objectives and tie-ins across disciplines. ?Unplugged? activities that are playful, hands-on learning experiences that foster learning about AI without programming can address these constraints. This project will create a public repository of unplugged activities for fostering middle school aged youth?s age-appropriate understanding of AI. The aim is to broaden access to AI education, especially for learners underrepresented in STEM. This proposal was received in response to the Dear Colleague Letter (DCL): Rapidly Accelerating Research on Arti?cial Intelligence in K-12 Education in Formal and Informal Settings (NSF 23-097) and funded by the Innovative Technology Experiences for Students and Teachers (ITEST) program, which supports projects that build understandings of practices, program elements, contexts and processes contributing to increasing students' knowledge and interest in science, technology, engineering, and mathematics (STEM) and information and communication technology (ICT) careers.
The project team will explore three key research questions: 1) how can we design a set of unplugged activities that empower young adolescent learners to learn about AI through the lens of their own bodies and identities?; 2) How do adolescents and educators perceive unplugged AI literacy activities?; and 3) Are unplugged activities e?ective at fostering middle-school learners? AI literacy, especially as it relates to AI?s impact on their lives? Researchers will engage in iterative design-based research to develop up to 15 unplugged activities that span a variety of AI literacy learning objectives and relevant cross-disciplinary connections. Research design includes interviews with 20 to 30 adults including teachers, parents, and after-school group leaders as well as 20-30 teens who will engage with the activities and o?er feedback. Teens will additionally complete a retrospective post-test to assess learning. This project will contribute an open-source repository of AI literacy activities that will be widely disseminated amongst parents and educators. In addition, this project will contribute an evidence-based understanding of whether and how unplugged resources can support young adolescents? learning about AI, including design recommendations that can be used to guide future interventions. This work will result in new theories about the ways in which adolescents learn about AI through their bodies and the lens of their personal identities.
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.
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