Increasing Data Literacy in High School Students Through Data Science and Healthcare: Part 1 of 2 Leading to AI Instruction

High school science and biomedical pathway teachers need effective strategies to build student data literacy and prepare them to conduct experiments. This first article of two presents the data collection, visualization, and analysis lessons (Lessons 6–10) from the Data Science, AI and You (DSAIY) in Healthcare curriculum, co-developed and tested by teachers in diverse classroom settings using the Scoutlier online learning platform. The lessons guide students in collecting and visualizing data (Lessons 6–7) and in more advanced data interpretation, analysis, and application (Lessons 8–10). Through a semester-long curriculum and an end-of-year datathon, DSAIY empowers high school students to address ethical challenges in healthcare using data science and machine learning (a subfield of artificial intelligence, AI). DSAIY emphasizes hands-on, culturally responsive, inquiry-based learning aligned with Next Generation Science Standards (NGSS) and Common Core Standards. These approaches are essential for preparing students to conduct experiments and develop machine learning models.