Flu Finders: Data Literacy through Wastewater Monitoring

To prepare for challenges in the biomedical field, students must be data-literate. American students’ underperformance in STEM fields, and the limiting effect that has on the STEM workforce including roles in biomedical science, is an ongoing concern (Sass, 2015; Rosenzweig et al., 2021). Problem-based learning, which emphasizes authentic problem-solving, is one flexible instructional method that has been effective at building data literacy skills and improving students’ science achievement, but is also time-consuming and challenging to implement (Friedrich et al., 2024; Merritt et al., 2017). Building tools that help students develop the skills to navigate a data-centric world and see the value of science in their lives, while enabling educators to respond to their students’ needs, would help address this critical issue. This SBIR Phase I & II award will enable Killer Snails LLC to develop a multimodal learning experience, Flu Finders, that uses a Problem-based learning framework to deliver Next Generation Science Standards-aligned content to students in grades 7-10. Killer Snails will collaborate with virologist Dr. John Dennehy to create 5 class period-length challenges about monitoring the spread of flu in a community by interpreting data from sources including wastewater and clinical outcomes. Dr. Dennehy is an expert and innovator in the field of using RNA sequencing on samples of wastewater to monitor viral diseases, an impactful, surprising, and data-driven field that forms the basis of the Flu Finders narrative. Flu Finders will leverage the features of an interactive, personalized website to support a Problem-based learning curriculum, allowing students to build data literacy, digital fluency, and problem-solving skills that are critical throughout STEM subject areas. Flu Finders will also address the need for individualized feedback with a real-time educator dashboard that summarizes student actions and highlights actionable steps to support building new skills. This approach will address issues of scalability that make Problem-based learning less likely to be implemented in classrooms. Flu Finders has three innovative features: (1) Interactive Data Visualization Builder to enable students to explore the data collected in the virtual environment and power their inferences and decision-making (2) Collaborative Interface to enable students to collaborate on a final presentation, using a proprietary design structured to support sharing their recommendations and evidence-based reasoning. (3) Real-Time Educator Dashboard Optimized for Problem-Based Learning to highlight progress and diagnostic recommendations for tailored, timely, contextual educator feedback. The dashboard will display actionable learning analytics of individual student work and the collaborative interactions between students. The dashboard will highlight evidence of data literacy skills, or the need for support from the educator. Our innovative features will be iteratively tested to examine how they contribute to students' learning. Our evaluators, Marcy Peak LLC, will conduct a randomized control trial investigating the extent to which Flu Finders influenced students’ content knowledge, data literacy, digital fluency, and problem-solving skills, and subjective value of science, as well as educators’ ability to monitor and support students during problem-based learning activities. Flu Finders’ integrated narrative, curriculum, and digital platform will meet the data-centric needs of science learners and educators.