Collaborative Research: Promoting Regional Opportunities for Practical and Engaged Learning in Artificial Intelligence
- Institution
- University of California-Riverside, CA
- Principal investigator
- Evangelos Papalexakis
- Funding
- $400K
- Duration
- 2025–2030
Moonbase score
Still being scored
Abstract
With support from the Improving Undergraduate STEM Education: Hispanic-Serving Institutions (HSI) Program, this ELPSE Level 2 project aims to expand access to artificial intelligence (AI) education through the development of interdisciplinary AI minor and certificate programs, along with community-engaged research opportunities. The project will serve students in the Inland Empire region of Southern California, where there is strong demand for skilled workers in computing and AI-related fields. Building on ongoing collaboration between California State University, San Bernardino, and the University of California, Riverside, the initiative will provide students with flexible entry points into AI careers through curriculum development, industry-informed research experiences, and faculty mentoring. The program will be open to all students across disciplines and institutions. The specific aims of the project are to: (1) build new AI minor and certificate programs that provide students with theoretical and applied skills through career-relevant curriculum design and project-based coursework; (2) establish an AI Help Desk to support community organizations and small businesses by offering AI consultations and student-led solutions to real-world problems; (3) engage students from a range of disciplines, including non-computing majors, through mentoring, faculty-guided research, and community workshops; and (4) sustain pathways into AI by integrating formal instruction with informal learning and collaborative research opportunities. The project will investigate how applied AI learning experiences influence student outcomes and motivation. A mixed-methods research design will be used, combining survey data, academic performance metrics, interviews, and focus groups to assess outcomes. Faculty teams will also evaluate the impact of curriculum design and community-based projects on student engagement and learning. Results will be shared through academic publications, open-source tools, presentations at education and computing conferences, and local institutional partnerships. The long-term goal is to develop a scalable, replicable model for AI education that aligns with regional workforce needs by offering flexible academic programs and practical, hands-on learning experiences to strengthen AI readiness and support sustained growth in the STEM workforce. This project is funded by the HSI Program, which aims to enhance undergraduate STEM education and increase capacity to engage in the development and implementation of innovations to improve STEM teaching and learning at HSIs. 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.
Research team
- Evangelos PapalexakisPI
- Jia Chen
- Yue Dong
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