Award Abstract # 2343693
RAPID: DRL AI: Non-digital Hands-on AI Learning Resources for Middle-School Students

NSF Org: DRL
Division of Research on Learning in Formal and Informal Settings (DRL)
Recipient: NORTHWESTERN UNIVERSITY
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: FY 2024 = $156,000.00
History of Investigator:
  • Duri Long (Principal Investigator)
    duri@northwestern.edu
Recipient Sponsored Research Office: Northwestern University
633 CLARK ST
EVANSTON
IL  US  60208-0001
(312)503-7955
Sponsor Congressional District: 09
Primary Place of Performance: Northwestern University
2240 Campus Dr
EVANSTON
IL  US  60201-2952
Primary Place of Performance
Congressional District:
09
Unique Entity Identifier (UEI): EXZVPWZBLUE8
Parent UEI:
NSF Program(s): ITEST-Inov Tech Exp Stu & Teac
Primary Program Source: 1300PYXXDB H-1B FUND, EDU, NSF
Program Reference Code(s): 7914, 093Z
Program Element Code(s): 722700
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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