Award Abstract # 2118272
Collaborative Research: CyberTraining: Pilot: A Cybertraining Program to Advance Knowledge and Equity in the Geosciences

NSF Org: OAC
Office of Advanced Cyberinfrastructure (OAC)
Recipient: THE ADMINISTRATORS OF TULANE EDUCATIONAL FUND
Initial Amendment Date: September 9, 2021
Latest Amendment Date: January 8, 2024
Award Number: 2118272
Award Instrument: Standard Grant
Program Manager: Sharmistha Bagchi-Sen
shabagch@nsf.gov
 (703)292-8104
OAC
 Office of Advanced Cyberinfrastructure (OAC)
CSE
 Directorate for Computer and Information Science and Engineering
Start Date: October 1, 2021
End Date: September 30, 2024 (Estimated)
Total Intended Award Amount: $173,323.00
Total Awarded Amount to Date: $173,323.00
Funds Obligated to Date: FY 2021 = $173,323.00
History of Investigator:
  • Kyle Straub (Principal Investigator)
    kmstraub@tulane.edu
  • Nicole Gasparini (Former Principal Investigator)
Recipient Sponsored Research Office: Tulane University
6823 SAINT CHARLES AVE
NEW ORLEANS
LA  US  70118-5665
(504)865-4000
Sponsor Congressional District: 01
Primary Place of Performance: Tulane University
6823 St. Charles Avenue
New Orleans
LA  US  70118-5698
Primary Place of Performance
Congressional District:
01
Unique Entity Identifier (UEI): XNY5ULPU8EN6
Parent UEI: XNY5ULPU8EN6
NSF Program(s): CyberTraining - Training-based
Primary Program Source: 01002122DB NSF RESEARCH & RELATED ACTIVIT
Program Reference Code(s): 7231, 7301, 9102, 9150
Program Element Code(s): 044Y00
Award Agency Code: 4900
Fund Agency Code: 4900
Assistance Listing Number(s): 47.070

ABSTRACT

This project will build and evaluate sustainable pathways for participation in cybertraining within the Earth science fields. The project will enhance inclusivity by focusing on underrepresented geoscience students for training in cyberinfrastructure (CI), including computer programming, data analysis, and modeling, which are not typically parts of the geoscience curriculum. The project will enhance programming education for geoscience students and increase access and mentoring relationships in STEM fields, thus building sustainable CI for geoscience programing. Consequently, this project will lower barriers to entry for STEM students while developing networks and mentoring relationships in the geosciences.

This project will provide geoscience graduate students with skills training that promote knowledge proliferation in software development and science communication. Students will learn to automate workflows, test code, manage code repositories, visualize data, and communicate research effectively, which will accelerate their research foundation and provide future professional opportunities. Given the size of the Spanish-speaking STEM student population in the United States, the current effort will focus on bi-lingual cybertraining. This CI project will provide opportunities to enhance coding skills and communication abilities, while expanding students? professional network and establishing mentors at multiple career stages. Cybertraining will occur in a series of virtual and in-person terms, where students will learn Python coding and data analysis, and will be exposed to a Hackathon to provide practical application of these skills. Course materials will be open source, which will create a sustainable cybertraining program.

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.

This project trains early career geoscientists in basic programming and science communication skills. Although programming and science communication are not typically included in a geoscience graduate curriculum, these skills are used almost daily in the modern research process. This project fills a gap in training students for a career in the geosciences, whether in research, business, or industry.

The novel aspects of this project are the integration of science communication—for example, can you explain to a friend how you solved a wicked programming problem, or can you explain to the public how your research might benefit them?—and the side-by-side bilingual (Spanish and English) approach to teaching programming, with instructors and course developers who are also early career bilingual geoscientists. This approach is especially useful for students who know one language and are trying to learn the other. Students demonstrate their competency in programming by completing a team project at the end of the training program. Students also give an oral presentation on their team project and receive feedback from instructors and other participants. The side-by-side bilingual course material developed for this project, though written for geoscientists, is general enough to be used by other disciplines. Because the course material is licensed as open source, anyone can reuse and remix it for their needs. The course material is freely and publicly available online.

Evaluation of participant outcomes indicates increases in programming and communication skills as well as heightened sense of belonging. Through this project, we provided the opportunity for bilingual geoscience graduate students to teach programming and science communication skills to other early career geoscientists. The students and instructors working together through the training program form a cohort that expands their peer and professional network. Further, the leadership skills developed by the instructors and course developers set a foundation for their future careers to help them navigate collaborations, mentorship, and career development.

 


Last Modified: 02/12/2025
Modified by: Kyle Straub

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