Data science and artificial intelligence (AI) are poised to upend the way healthcare is delivered. But what happens when AI is trained on medical data that doesn’t reflect the population? A new semester-long course teaches high school students how embedded bias in machine learning affects healthcare discussions and decisions. The goals of the Data Science, AI, and You in Healthcare project include fostering community connections between educators, researchers, clinicians, and local stakeholders to prepare underrepresented students for STEM jobs—ultimately in fields where their background and

After participating in an afterschool program where they used the Common Online Data Analysis Platform (CODAP) to study time-series data about infectious diseases, four middle school students were interviewed to determine how they understood features of and trends within these graphs. Our focus was on how students compared graphs. Students were readily able to compare cumulative/total infection rates among two countries with differently sized populations. It was more challenging for them to link a graph of yearly cases to the corresponding graph of cumulative cases. Students offered reasonable

The Luquillo Long-Term Ecological Research (LTER) program in Puerto Rico has implemented a Data Jam initiative that fosters student engagement in ecological data science. In December 2023, over 175 middle and high school students presented 51 data-driven projects at a symposium in El Yunque National Rainforest. The initiative, rooted in the LTER’s extensive datasets, allows students to develop research questions, analyze data using the CODAP tool, and present findings. The program includes professional development for teachers, with workshops and Virtual Lab Meetings that equip them to guide

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)

Learning to construct and make sense of time-series graphs is a key practice in middle school science. We describe a new, free educational tool called “Sonify” that enables students to extend their use of the Common Online Data Analysis Platform (CODAP) so that they can listen to graphs of scientific phenomena that change over time while they simultaneously examine these graphs visually. We report on how listening to graphs helps students attend to key elements, including slope, and how listening might help differentiate instruction. Sonify has special appeal to students who value learning

Scientific sensemaking is described in the context of studying a three-week, sixth-grade unit on the ecology and restoration of puffins living off the coast of Maine. Students engaged with a scientific adventure story, observed local bird species, used AI and webcam-facilitated tools, designed puffin burrows, and explored data sets about puffins. Students’ ideas were elicited through discussion of the challenges faced by scientists who restored the puffins; sharing observations of chick-rearing behaviors from a webcam; critiquing and revising classmates’ burrow designs; writing about bird

The study of Atlantic puffins among Maine middle-school science students provides a fascinating subject for integrating ecology, ornithology, and data practices. Atlantic puffins have made a remarkable comeback in Maine over the last 50 years under the leadership of ornithologist Stephen Kress and the National Audubon Society's Seabird Institute (Kress & Jackson, 2020). Studying the extent to which this seabird population has changed, and the reasons for these changes, is the focus of the Puffins curriculum project (Tumblehome, n.d.; NSF DRL-2241777). The curriculum combines a place-based