Moving Learners from Data Skills to Data Inquiry with Messy Data

This article presents a case study of a data literacy activity in a middle school science classroom, demonstrating how engaging students with “messy” data can develop crucial scientific practices aligned with the NGSS. The activity focuses on students collecting and analyzing local weather data to investigate the relationship between weather and the urban heat island at their school site. Through guided instruction, students learn to clean data by identifying incomplete or inaccurate entries, create visualizations, and interpret patterns. The process emphasizes key data literacy frameworks, including data awareness, access, engagement, management, communication, ethical use, and preservation. The case study illustrates how students use “noticing” statements and “I wonder” questions to critically evaluate data quality, make decisions about data cleaning, and create meaningful visualizations like scatterplots. The activity demonstrates how working with messy data can promote inquiry-based learning and critical thinking while developing essential data literacy skills. Such data-rich pedagogical approaches, when integrated into broader scientific investigations, provide students with authentic opportunities to engage in scientific practices while building transferable skills applicable across multiple disciplines.