Advancing AI and data literacy through student-driven innovation

Artificial Intelligence (AI) and data literacy education are pressing priorities in today’s technology landscape—for example, many schools and universities now teach students how to use tools like ChatGPT responsibly, analyze datasets with Python, and understand how algorithms influence social media feeds and hiring systems. Associate Professor Wei Zakharov co-developed a semester-long, student-driven learning initiative grounded in participatory design pedagogy, with a focus on AI and data education. Beginning in fall 2025, the project was implemented in her two-credit course, “AI for Education” (ENGR 17920–47922), which she teaches each fall and spring semester.

Throughout the semester, students collaboratively develop and refine a Retrieval-Augmented Generation (RAG) system to enhance an AI tutor tailored to their undergraduate programming and data science courses. This hands-on, project-based approach engages students as both developers and users, enabling them to apply AI and data literacy knowledge in real-world contexts while directly benefiting from the tools they help build.

The course currently enrolls 25 undergraduate students majoring in computer engineering, computer science, AI, and data science. The project is designed to strengthen students’ AI and data literacy skills through key competencies, including transformers, LLMs, RAG workflows, pre-training dataset curation, metadata management, and big data lifecycle management.