Collaborative research: engaging k-8 teachers in integrating computer science, AI, and cybersecurity into standard-based teaching

Federal Grant Award Summary

The Citadel received a $1.87M Project Grant from the National Science Foundation's Division of Research on Learning in Formal and Informal Settings under the STEM Education program (CFDA 47.076), awarded September 15, 2025, with completion targeted for August 31, 2029. This collaborative research initiative focuses on developing and delivering professional development resources to integrate computer science, artificial intelligence (AI), and cybersecurity education into K-8 standard-based curricula. The project will directly engage at least 82 rural teachers from South Carolina through multi-year professional development and coaching activities, with anticipated indirect impact to approximately 8,100 students in their classrooms.

The primary deliverables include curriculum resources, lesson plans, and evidence-based professional development materials addressing the interconnected nature of AI and cybersecurity as complementary systems. All resources developed through the project will be made publicly available as open access through the project website, strategic partnerships, conference presentations, and academic publications. The initiative aims to advance STEM literacy and technical competencies among K-8 students while establishing successful teacher professional development models responsive to the growing demand for preparing informed citizens capable of contributing to an increasingly technology-dependent society.

Abstract

As artificial intelligence (AI) becomes increasingly embedded in the technologies used by both students and teachers, IT is essential for them to understand how to be safe while using AI. Furthermore, AI and cybersecurity technology together are better at detecting malicious activities than conventional security systems. The need to blend the two disciplines into a single, integrated curriculum for k-8 education is highlighted by the interconnectedness of AI and cybersecurity as complementary systems. This project will plant the seeds of these literacies by spiraling content on topics from computer programming, internet fundamentals, and introduction to data and AI along with cybersecurity topics in small doses throughout students' k-8 education. This project will lay the foundation for the students to eventually develop a comprehensive understanding of how different technologies work and interact. This project aims to investigate how teachers from rural schools approach the integration of computer science (CS), and in particular, AI and cybersecurity components, into their existing curricula. This project will directly impact at least 82 rural teachers from south carolina through multi-year participation in professional development and coaching and approximately 8,100 students indirectly in their classrooms. Resources, including lesson plans, developed through the project will be made available as open access on the project website, through partnerships, and via conference presentations and publications. The overarching goal of this project is to improve stem teaching and learning by examining successful teacher professional development (PD) models in response to a need for preparing students with both stem literacy skills and other technical competencies needed to be informed citizens and contributors to society. The project will blend AI and cybersecurity into a unified curricula, supported by the following objectives: (1) analyze how k-8 educators incorporate AI and cybersecurity topics into disciplinary teaching components; (2) explore the learning supports that k-8 educators need to effectively incorporate AI and cybersecurity topics into current curricula to assist students in meeting content-focused learning objectives; and (3) compare the integration opportunities available to k-8 educators in rural areas of south carolina. In the end, hypothesizing that this research can form the basis for the creation of more scalable PD programs for k-8 teachers as well as continuous assistance with CS integration. The research will follow a mixed-methods design, combining survey data, classroom observations, and interviews to examine how educators make sense of and apply these concepts over time. Statistical analyses will identify significant patterns across teacher implementation contexts. Qualitative data – drawn from semi-structured interviews, teaching artifacts, video documentation, and field notes – will be coded to surface pedagogical strategies, challenges, and evolving teacher understandings. In addition, an APP will be created to allow teachers to document real-time classroom integration of AI and cybersecurity, providing a robust, longitudinal dataset. The findings will inform scalable, context-sensitive professional development models and contribute to a broader understanding of how to support interdisciplinary CS learning in k-8 settings. All data collection will be designed to ensure methodological rigor and trustworthiness through triangulation and ongoing member checks with participating educators. This project is CO-funded by NSF's DRK-12 and itest programs. The discovery research prek-12 program (DRK-12) seeks to significantly enhance the learning and teaching of science, technology, engineering, and mathematics (stem) by prek-12 students and teachers, through research and development of innovative resources, models, and tools. Projects in the DRK-12 program build on fundamental research in stem education and prior research and development efforts that provide theoretical and empirical justification for proposed projects. The innovative technology experiences for students and teachers (itest) program supports projects that build understandings of practices, program elements, contexts and processes contributing to increasing students' knowledge and interest in science, technology, engineering, and mathematics (stem) and information and communication technology (ICT) 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.- subawards are not planned for this award.