Cybertraining: pilot: building cross-disciplinary AI literacy and skill-set

The National Science Foundation Office of Advanced Cyberinfrastructure awarded Purdue University $299,897 on December 1, 2026, under the Computer and Information Science and Engineering program (CFDA 47.070) to develop, implement, and evaluate interdisciplinary educational modules integrating artificial intelligence literacy, applied machine learning skills, and responsible use of generative AI tools for undergraduate students.

The project pairs computer science and social science students in data-intensive research tasks including qualitative data coding, thematic analysis, and large-scale information processing. Deliverables include modular instruction, hands-on practicum activities, collaborative research experiences, evidence-based instructional practices, curriculum resources, and a replicable educational model. Assessment activities will examine how students develop technical competencies, evaluate AI tools, and integrate domain knowledge with computational methods.

Performance occurs in West Lafayette, Indiana, with a period of performance from December 1, 2026, through November 30, 2028. The assistance type is Project Grant. The project addresses the need for early-career researchers and students to learn how to use advanced AI technologies effectively, responsibly, and critically within their own disciplinary fields, with outcomes designed for scalability across institutions.

Abstract

Artificial intelligence is rapidly changing how scientific research, education, and the workforce operate. However, many students and early-career researchers lack opportunities to learn how to use these technologies effectively, responsibly, and critically within their own fields. This project addresses that challenge by creating educational experiences that prepare undergraduate students to work with advanced artificial intelligence tools in research settings. By bringing together students from computing and social science disciplines, the project will help develop a workforce that can apply emerging technologies to real-world scientific and societal problems while understanding their limitations and risks. The project supports the national interest by strengthening the future research workforce, expanding access to advanced technological capabilities, promoting interdisciplinary collaboration, and improving the ability of researchers to use artificial intelligence in ways that are trustworthy, ethical, and beneficial to society. This project will develop, implement, and evaluate a scalable set of interdisciplinary educational modules that integrate artificial intelligence literacy, applied machine learning skills, and responsible use of generative artificial intelligence tools. The project will provide modular instruction, hands-on practicum activities, and collaborative research experiences that pair computer science and social science students in data-intensive research tasks such as qualitative data coding, thematic analysis, and large-scale information processing. Assessment activities will examine how students develop technical competencies, evaluate artificial intelligence tools, and integrate domain knowledge with computational methods. Project outcomes will include the creation and delivery of evidence-based instructional practices, curriculum resources, and a replicable model for interdisciplinary artificial intelligence workforce development that can be adapted across multiple scientific disciplines and engineering fields. 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.