Loading organization details...
Loading organization details...
Source: IRS e-Filed Form 990 (from the IRS e-File system), Tax Year 2024
Total Revenue
▼$725.2K
Program Spending
70%
of total expenses go to program services
Total Contributions
$566.9K
Total Expenses
▼$642.5K
Total Assets
$739.4K
Total Liabilities
▼$513.4K
Net Assets
$226K
Officer Compensation
→N/A
Other Salaries
$432.5K
Investment Income
$0
Fundraising
▼N/A
Source: USAspending.gov · Searched by organization name
Total Federal Funding
$242.8K
Awards Found
2
National Science Foundation
$192.8K
AI AS THE CODING PARTNER: INSTRUCTIONAL PRACTICES FOR ARTIFICIAL INTELLIGENCE PAIR PROGRAMMING IN HIGH SCHOOL COMPUTER SCIENCE COURSES -ADVANCES IN ARTIFICIAL INTELLIGENCE (AI) ARE HAVING PROFOUND IMPACTS IN A RANGE OF AREAS, THEREFORE COMPUTER SCIENCE (CS) EDUCATION MUST PREPARE STUDENTS TO EFFECTIVELY USE AI TOOLS. BECAUSE THESE TOOLS ARE SO NEW, BEST PRACTICES FOR EDUCATIONAL USE OF AI TOOLS ARE NOT WELL UNDERSTOOD; IN FACT, AI TOOLS MAY ACTUALLY INHIBIT STUDENT LEARNING IF NOT USED WELL. ALSO, BECAUSE A MAJORITY OF PROFESSIONAL SOFTWARE DEVELOPERS NOW USE AI TOOLS, IT IS IMPORTANT FOR STUDENTS TO DEVELOP PROFICIENCY IN USING THESE TOOLS - BUT IT IS ALSO IMPORTANT THAT STUDENTS USE THEM IN A WAY THAT ENHANCES THEIR LEARNING INSTEAD OF REPLACING IT. THIS PROJECT CONTRIBUTES TO THE EFFECTIVE INTEGRATION OF AI TOOLS IN CS EDUCATION BY INVESTIGATING PAIR PROGRAMMING WITH AI (AIPP). IN TRADITIONAL PAIR PROGRAMMING, TWO STUDENTS WORK COLLABORATIVELY TO COMPLETE AN ASSIGNMENT. AIPP INVOLVES ONE STUDENT ENGAGING IN PAIR PROGRAMMING WITH AN AI TOOL. THE PROJECT IS DEVELOPING A SET OF CURRICULAR MATERIALS TO SUPPORT STUDENTS TO PRODUCTIVELY USE AI IN THEIR LEARNING TO CODE. THE MATERIALS ARE CURRICULUM-AGNOSTIC--THAT IS, THEY ARE AN OVERLAY TO BE USED ALONG WITH ANY OTHER HIGH SCHOOL CS CURRICULUM. THE MATERIALS DIRECT STUDENTS ON HOW TO COMPLETE CURRICULAR TASKS SO THAT THEIR PROMPTS TO AI AND WHAT THEY DO WITH AI RESPONSES ARE SUPPORTIVE OF THEIR LEARNING. IN THIS WAY, THE PROJECT IS SUPPORTING STUDENTS TO USE AI EFFICIENTLY AS A LEARNING TOOL, WHILE AT THE SAME TIME MIMICKING WAYS THAT THE WORK OF INDUSTRY IN CS IS ADOPTING AI. AS SUCH, THE PROJECT IS EXPLORING WAYS TO PREPARE STUDENTS FOR INTRODUCTION INTO THE WORKFORCE WHILE LEVERAGING AI AS AN EFFICIENT TOOL TO BOLSTER CS EDUCATION GENERALLY. THIS PROJECT IS RESEARCHING THE KNOWLEDGE AND SKILLS STUDENTS NEED IN ORDER TO SUCCESSFULLY ENGAGE IN AIPP. BUILDING ON EARLY RESEARCH OF PROMISING PRACTICES FOR EDUCATIONAL AIPP, THE PROJECT STUDIES THE EFFICACY OF TWO RECOMMENDATIONS: (1) DEVELOPING SKILLS FOR CODE READING AND REVIEW, AND (2) MODULATING TRUST IN AI. THE PROJECT IS PARTICULARLY FOCUSED ON UNCOVERING EVIDENCE OF BEST PRACTICES THAT SUPPORT ALL STUDENTS IN THEIR CS LEARNING, REGARDLESS OF THEIR PRIOR CS EXPERIENCE. THE FIRST PHASE OF THE PROJECT IS DEVELOPING AIPP RESOURCES WITH CS EDUCATORS IN REGION 8 OF THE STEM COLLECTIVE FOR INNOVATIVE LOUISIANA STAKEHOLDERS. FOLLOWING THIS, CS EDUCATORS IMPLEMENT AIPP IN THEIR CLASSROOMS. REPEATED MEASURES DESIGNS TEST THE EFFICACY AMONG STUDENTS OF AIPP (AND THE TWO SUPPORTIVE PRACTICES) RELATIVE TO TRADITIONAL PAIR PROGRAMMING. THE PROJECT IS ITERATIVELY REVISING AND UPDATING THE CURRICULAR MATERIALS AFTER THE FIRST ROUND OF IMPLEMENTATION AND THEN PREPARING ADDITIONAL TEACHERS TO IMPLEMENT AIPP FOR FURTHER TESTING IN TWO MORE YEARS. BOTH THE RESEARCH FINDINGS AND THE CURRICULAR MATERIALS WILL BE DISSEMINATED TO VARIOUS APPROPRIATE AUDIENCES, SUCH AS OTHER RESEARCHERS, TEACHERS AND CURRICULUM DESIGNERS. THIS PROJECT IS FUNDED BY THE CS FOR ALL: RESEARCH AND RPPS 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.- SUBAWARDS ARE NOT PLANNED FOR THIS AWARD.
National Science Foundation
$50K
CONFERENCE: DEVELOPING GUIDANCE FOR THE USE OF ARTIFICIAL INTELLIGENCE IN STEM EDUCATION RESEARCH -ARTIFICIAL INTELLIGENCE (AI) TOOLS ARE BEING ADOPTED AT AN UNPRECEDENTED RATE, OFFERING POWERFUL NEW CAPABILITIES FOR RESEARCHERS IN SCIENCE, TECHNOLOGY, ENGINEERING, AND MATHEMATICS (STEM) EDUCATION. WHILE THESE TOOLS CAN ACCELERATE DISCOVERY, THEY ALSO PRESENT SIGNIFICANT CHALLENGES SUCH AS PROVIDING INACCURATE OR LIMITED INFORMATION. THIS PROJECT AIMS TO DEVELOP GUIDELINES FOR STEM EDUCATION RESEARCHERS SO THAT THEY CAN USE THESE NOVEL TOOLS EFFECTIVELY AND RESPONSIBLY. THIS PROJECT ADDRESSES A CRITICAL GAP BY BRINGING TOGETHER EXPERTS FROM A VARIETY OF FIELDS AT A CONFERENCE TO DEVELOP FOUNDATIONAL GUIDANCE FOR THE RESPONSIBLE USE OF AI IN STEM EDUCATION AND RESEARCH. THIS WORK SERVES THE NATIONAL INTEREST BY LESSENING THE RISK OF USING AI IN STEM EDUCATION. THE RAPID PROLIFERATION OF LARGE LANGUAGE MODELS (LLMS) AND OTHER AI TOOLS IN THE RESEARCH WORKFLOW HAS OUTPACED THE DEVELOPMENT OF PROFESSIONAL STANDARDS FOR THEIR USE. THUS, THIS PROJECT CONVENES A CONFERENCE OF EXPERTS TO CREATE GUIDANCE FOR THE RESPONSIBLE USE OF AI WITHIN THE CONTEXT OF STEM EDUCATION RESEARCH. THE PROJECT CENTERS ON EXPANDING THE UNDERSTANDING THAT STEM EDUCATION RESEARCHERS HAVE OF THE COMPLEX ISSUES INVOLVED WITH THE USE OF AI AND SEEKS TO ESTABLISH A FRAMEWORK FOR DECISION-MAKING. THE CONFERENCE AND SUBSEQUENT ACTIVITIES ADDRESS TWO CENTRAL RESEARCH QUESTIONS: (1) WHAT ARE THE OPPORTUNITIES, CHALLENGES, AND RISKS PERTAINING TO THE USE OF AI TOOLS IN STEM EDUCATION RESEARCH? AND (2) WHAT ETHICAL ISSUES, INCLUDING AUTHORSHIP AND DATA PRIVACY, SHOULD STEM EDUCATION RESEARCHERS CONSIDER WHEN USING AI TOOLS IN THEIR RESEARCH? THE PROJECT CONTRIBUTES TO THE DEVELOPMENT AND DISSEMINATION OF AI GUIDELINES THAT WILL INFORM AND ENHANCE STEM EDUCATION RESEARCH. 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.- SUBAWARDS ARE NOT PLANNED FOR THIS AWARD.
Source: Federal Audit Clearinghouse (fac.gov)
No federal single audit records found for this organization.
Single audits are required for entities expending $750,000+ in federal awards annually.
Tax Year 2024 · Source: IRS e-Filed Form 990
Individuals serving as officers, directors, or trustees of the organization.
| Name | Title | Hrs/Wk | Compensation | Related Orgs | Other |
|---|
Source: IRS Publication 78, Auto-Revocation List & e-Postcard Data
Tax-deductible contributions: Yes
Deductibility code: PC
Sources: IRS e-Filed Form 990 (XML) & ProPublica Nonprofit Explorer
Scroll →
| Year | Revenue | Contributions | Expenses | Assets | Net Assets |
|---|---|---|---|---|---|
| 2024IRS e-File | $725.2K | $566.9K | $642.5K | $739.4K | $226K |
| 2023 | $564K | $449.9K | $567K | $250.1K | $143.3K |
| 2022 | $594.1K | $479.7K | $469.4K | $200.9K | $146.3K |
| 2021 | $223.6K | $174.9K |
Sources: ProPublica Nonprofit Explorer & IRS e-File Index
Financial data: IRS e-Filed Form 990 (Tax Year 2024)
Leadership & compensation: IRS e-Filed Form 990, Part VII (Tax Year 2024)
Federal grants: USAspending.gov (live)
Organization info: IRS Business Master File
Tax-deductibility: IRS Publication 78
| Total |
|---|
| Monica Mcgill | President | 50 | $110.1K | $0 | $0 | $110.1K |
| Abi Olukeye | Chair | 1 | $0 | $0 | $0 | $0 |
| Karen A Peterson | Treasurer | 1 | $0 | $0 | $0 | $0 |
| Chris Stephenson | Vice Chair | 1 | $0 | $0 | $0 | $0 |
Monica Mcgill
President
$110.1K
Hrs/Wk
50
Compensation
$110.1K
Related Orgs
$0
Other
$0
Abi Olukeye
Chair
$0
Hrs/Wk
1
Compensation
$0
Related Orgs
$0
Other
$0
Karen A Peterson
Treasurer
$0
Hrs/Wk
1
Compensation
$0
Related Orgs
$0
Other
$0
Chris Stephenson
Vice Chair
$0
Hrs/Wk
1
Compensation
$0
Related Orgs
$0
Other
$0
Members of the governing board. Board members often serve without compensation.
| Name | Title | Hrs/Wk | Compensation | Related Orgs | Other | Total |
|---|---|---|---|---|---|---|
| Callista Chen | Member | 1 | $0 | $0 | $0 | $0 |
| Carlos Zavala | Member | 1 | $0 | $0 | $0 | $0 |
| Olivia Lu | Member | 1 | $0 | $0 | $0 | $0 |
| Tamara Pearson | Member | 1 | $0 | $0 | $0 | $0 |
Callista Chen
Member
$0
Hrs/Wk
1
Compensation
$0
Related Orgs
$0
Other
$0
Carlos Zavala
Member
$0
Hrs/Wk
1
Compensation
$0
Related Orgs
$0
Other
$0
Olivia Lu
Member
$0
Hrs/Wk
1
Compensation
$0
Related Orgs
$0
Other
$0
| $260.6K |
| $49.8K |
| $21.6K |
| 2020 | $166.4K | — | $100.7K | $81.2K | — |
| 2021 | 990 | Data |
| 2020 | 990-EZ | Data | PDF not yet published by IRS |
Tamara Pearson
Member
$0
Hrs/Wk
1
Compensation
$0
Related Orgs
$0
Other
$0