Building Data Fluency and Generative AI Literacy Through Data Adventures

The growing importance of data, data science and artificial intelligence (AI) in education, work, and personal and civic life has increased the need for all U.S. students to develop data literacy, statistical reasoning, and computational thinking skills. However, most middle school students—especially those with learning disabilities (SLD)—receive limited or no instruction in these areas. Data science and AI instruction is often limited to high school settings, narrowly framed within mathematics or science, and rarely designed with the flexibility to support learner variability. As a result, too many students including those with SLD are less likely to develop foundational data fluency or see themselves as future contributors to data science or AI-related fields, long term consequences for U.S. competitiveness in these fields. It is essential to design inclusive, engaging, and forward-looking instructional experiences that provide all students with meaningful on-ramps to data science and AI fluency. The purpose of this project is to develop and refine Data Adventures, a series of open-access, modular, and instructional experiences units designed to introduce middle school students to data literacy, computational thinking, and digital storytelling, while also promoting critical understanding of AI and its role in education, work technology, and everyday life.

Each Data Adventure will be embedded in a core content area (math, science, English language arts, or technology), incorporate high-interest themes, and culminate in digital data stories. Data Adventures will expose students to foundational AI concepts (e.g., pattern recognition, training data, prompt engineering) and provide optional tools powered by generative AI to support expression, data visualization, and reflection—always paired with evidence based explicit instruction to build critical AI literacy. The team will collaborate with teachers and students using iterative design research methods to co-develop and pilot four Adventures. Over the three-year project, more than 15 teachers and 500 students—including over 50 students with SLD—will participate in co-design, testing, and evaluation. Research will include iterative usability studies and a quasi-experimental pilot study to assess improvements in data literacy, computational thinking, AI fluency, statistical reasoning, and student engagement. Professional development modules and open-source materials will support long-term scalability and integration into multiple content areas.