
NSF Org: |
DRL Division of Research on Learning in Formal and Informal Settings (DRL) |
Recipient: |
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Initial Amendment Date: | January 27, 2021 |
Latest Amendment Date: | July 16, 2024 |
Award Number: | 2045561 |
Award Instrument: | Continuing Grant |
Program Manager: |
Margret Hjalmarson
mhjalmar@nsf.gov (703)292-5186 DRL Division of Research on Learning in Formal and Informal Settings (DRL) EDU Directorate for STEM Education |
Start Date: | May 1, 2021 |
End Date: | April 30, 2026 (Estimated) |
Total Intended Award Amount: | $798,050.00 |
Total Awarded Amount to Date: | $650,600.00 |
Funds Obligated to Date: |
FY 2022 = $122,774.00 FY 2023 = $125,968.00 FY 2024 = $170,260.00 |
History of Investigator: |
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Recipient Sponsored Research Office: |
801 UNIVERSITY BLVD TUSCALOOSA AL US 35401 (205)348-5152 |
Sponsor Congressional District: |
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Primary Place of Performance: |
801 University Blvd Tuscaloosa AL US 35486-0005 |
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): |
CSforAll-Computer Sci for All, ITEST-Inov Tech Exp Stu & Teac |
Primary Program Source: |
04002223DB NSF Education & Human Resource 04002324DB NSF STEM Education 04002425DB NSF STEM Education 04002526DB NSF STEM Education 1300CYXXDB H-1B FUND, EDU, NSF 1300XXXXDB H-1B FUND, EDU, NSF 1300XXXXDB H-1B FUND, EDU, NSF |
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
Next generation physiological computing systems use sensors to measure data like brain activity or heart activity. These emerging systems are at the forefront of human-computer interaction applications involving health technologies, adaptive smart environments, self-regulation, security and authentication. Future STEM professionals are needed to design applications and tools that rely on physiological computing. In addition, physiological sensors are motivating opportunities for students to learn about computer science, data processing, technology, and design. This project will provide rural students and teachers with hands-on learning experiences in physiological computing. The project will investigate how students learn about physiological data processing and computational concepts. Products will include learning modules for high school science and technology courses. Findings from the proposed research will inform future K-12 work at the intersection of human physiology and technology. This project is funded by the CS for All: Research and RPPs program. This project is also 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.
Students are expected to gain physiological data processing and computational skills while engaging with the technology developed in the project. More specifically, physiological sensors engage students in learning about wave properties and other signal processing topics. Physiological computing also requires interdisciplinary learning in data processing, computational thinking, and scientific phenomenon. This project will explore physiological computing in high school classrooms through multiple studies that explore various ways to engage students with physiological computing such as (1) pre-recorded and real-time data (2) integrating physiological data processing and computational concepts, (3) textual and visual programming interfaces, and (4) digital and physical feedback components. The project includes the following research questions. First, how does hands-on experience with pre-recorded and real-time physiological data influence students? ability to gain knowledge of physiological data processing concepts? How do these experiences influence students? interest in STEM? Second, to what extent does integrating computational and data processing concepts build computational thinking and physiological computing skills? When compared to a visual interface, how will a textual interface for physiological data processing influence computational thinking, knowledge of physiological data processing concepts, and interest in STEM? Third, when compared to digital approaches, how will physical physiological-based learning environments influence computational thinking, knowledge of physiological data processing concepts, and interest in STEM? The project will gather evidence from audio and video analysis, screen recordings, student work and other assessments of knowledge and interest.
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.
PUBLICATIONS PRODUCED AS A RESULT OF THIS RESEARCH
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