CyberTraining: Pilot: Peer-Mentored HPC Bootcamps to Empower Cyberinfrastructure (CI) Users at Primarily Undergraduate Institutions

This project expands participation in cyberinfrastructure by creating a pathway that prepares undergraduate students at Primarily Undergraduate Institutions to become effective users of high performance computing and data intensive research technologies. Although advanced computing now drives discovery across STEM fields, students at smaller institutions often have limited opportunities to gain hands-on experience with these resources. The project addresses this challenge through a student centered training model that combines summer bootcamps, peer mentoring, and authentic STEM research experiences. A distinctive feature of the project is its use of advanced undergraduate peer mentors who guide participants through technical challenges while helping them develop confidence, computational problem solving skills, and a sense of belonging within the cyberinfrastructure community. By broadening access to advanced computing and supporting students from a wide range of STEM disciplines, the project strengthens the national workforce, promotes scientific innovation, and creates a scalable model for cyberinfrastructure training at undergraduate institutions. The project will develop, implement, and evaluate a peer-mentored cyberinfrastructure training program serving undergraduate students from Primarily Undergraduate Institutions. Participants will engage in intensive summer bootcamps followed by academic year mentoring and research activities using the Hellbender high performance computing cluster. Training includes Linux, Python, Jupyter notebooks, job scheduling systems, parallel computing concepts, and reproducible computational workflows. Students will select project pathways aligned with their interests, including independent projects, faculty supervised research, or discipline specific small projects in areas such as computational chemistry, biology, astrophysics, image analysis, and data science. Peer mentors will provide technical guidance, troubleshooting support, and ongoing engagement throughout the project. The project will create and iteratively refine open access instructional materials, assessment tools, and implementation guides that support adoption by other institutions. Evaluation activities will examine student learning, mentoring outcomes, workforce readiness, and barriers to participation, generating evidence-based practices for broadening access to cyberinfrastructure and strengthening undergraduate pathways into research, graduate study, and computationally intensive careers. 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.