| NSF Org: |
DUE Division Of Undergraduate Education |
| Recipient: |
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| Initial Amendment Date: | August 2, 2019 |
| Latest Amendment Date: | August 2, 2019 |
| Award Number: | 1912159 |
| Award Instrument: | Standard Grant |
| Program Manager: |
Bonnie Green
DUE Division Of Undergraduate Education EDU Directorate for STEM Education |
| Start Date: | October 1, 2019 |
| End Date: | September 30, 2020 (Estimated) |
| Total Intended Award Amount: | $49,796.00 |
| Total Awarded Amount to Date: | $49,796.00 |
| Funds Obligated to Date: |
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| History of Investigator: |
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| Recipient Sponsored Research Office: |
W5510 FRANKS MELVILLE MEMORIAL LIBRARY STONY BROOK NY US 11794-0001 (631)632-9949 |
| Sponsor Congressional District: |
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| Primary Place of Performance: |
1433 Computer Science Stony Brook NY US 11794-0001 |
| 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): | IUSE |
| 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
With support from the NSF Improving Undergraduate STEM Education Program: Education and Human Resources (IUSE: EHR), this project will develop and hold a national workshop entitled "Data Science Across the Undergraduate Curriculum: University-Industry Online Case Studies on Applications of Data Science." The workshop has two major aims: 1) review the national landscape of major online resources for learning and teaching data science across the undergraduate curriculum; and 2) make initial plans for developing frameworks that will guide curricular design, facilitating learning environments, and doing assessments in the context of online case studies on applications of data science.
The growing abundance of data from heterogeneous sources is impacting research, design, manufacturing, marketing, and many workplace practices. Workshop participants will explore how colleges and universities, in partnership with industry, can better prepare undergraduate students from any major to gather, analyze and use data effectively to improve processes. The workshop will engage participants in online resources and learning environments to develop case studies based on examples of data science applications across a wide range of STEM areas. Each case study will address technical and technology dimensions, applications, and societal implications. Participants will also consider ways to help students understand societal impacts of data science. The workshop will generate a report of its findings that will be available online and on relevant STEM education networks. The NSF IUSE:EHR Program supports research and development projects to improve the effectiveness of STEM education for all students.
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.
PROJECT OUTCOMES REPORT
Disclaimer
This Project Outcomes Report for the General Public is displayed verbatim as submitted by the Principal Investigator (PI) for this award. Any opinions, findings, and conclusions or recommendations expressed in this Report are those of the PI and do not necessarily reflect the views of the National Science Foundation; NSF has not approved or endorsed its content.
The explosion of data generated from various sources such as social media, business/industry transactions, and open-source data impacts almost every aspect of our lives. Thus, colleges and universities, working in close collaboration with industries, need to better prepare undergraduate students, regardless of major fields, to gather, analyze and use data effectively to improve processes.
While there have been numerous workshops with specific content in data science held by universities and other institutions, many of them have not yet focused on preparing curriculum for undergraduate students. As a result, the Department of Technology and Society in the College of Engineering and Applied Sciences (CEAS) at Stony Brook University (SBU) hosted a national workshop entitled “Data Science Across the Undergraduate Curriculum: University-Industry Online Case Studies on Applications of Data Science. The workshop has two main aims
● Review the national landscape on major online resources for the learning and teaching of data science across the undergraduate curriculum.
● Lay out initial plans for developing frameworks for doing curricular design, facilitating learning environments, and doing assessments in the context of online case studies on applications of data science.
The workshop was held from Thursday, January 9 through Friday January 10, 2020 at Wang Center, Stony Brook University. The workshop featured 60 participants from 16 institutions.
Intellectual Merit:
-Better knowledge on improving undergraduate education
-Improved knowledge on the role of data science in industry, academia and government.
-More information on career paths for data scientists.
Broader impacts:
-Trained a grad student to help organize and run the conference.
-Collaboration across academia, industry to strengthen data science education. This is especially important because data science is a strategic sector for the economy, security, and healthcare.
-The workshop discussed ways to improve data science across the undergraduate curriculum. We particularly emphasized ways data science can be used in a variety of STEM and non-STEM fields and how students from marginalized communities can best thrive in data science majors and careers.
-We recruited participants from marginalized communities to speak at the workshop and many of our speakers were from underrepresented minority groups.
Last Modified: 12/30/2020
Modified by: Gang He
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