Project Summary The EvolvingSTEM laboratory uses a guided research experience to increase student confidence in their ability to act and think as scientists. Students take part in an authentic bacterial evolution experiment that can be conducted almost anywhere with minimal equipment. High school students learn microbiology, genetics, and biotechnology through the organizing principle of evolution, seeing obvious, heritable changes in bacterial colonies as they adapt to produce biofilm in just a few days. The experiment is biomedically relevant in simulating evolution during infections because related pathogenic bacteria adapt during chronic infections by identical mutations. An accompanying bioinformatics module has been developed that provides students experience in data science when they identify mutations from whole-genome sequencing data generated from prior student research experiments. Students learn to work through productive uncertainty, to engage with the material in ways that traditional life science education cannot, and to build their capacity for critical reasoning. Investigations such as ours allow students from all backgrounds to form a sense of agency to see themselves as scientists and motivate their interest in related careers. This proposal will test the overarching hypothesis that our program can improve topical learning and attraction to STEM in a large school district attended predominantly by underrepresented minority (URM) and economically disadvantaged (DA) students, the urban Pittsburgh Public Schools (PPS) system. Our goals are to (1) improve high school student attitudes towards learning essential life science topics, such as evolution, microbiology, and genetics, (2) improve understanding of how microbes evolve and influence our lives, (3) provide practical skill development in laboratory methods and data science, and (4) motivate their interest in pursuing careers in STEM, partly by helping them to identify as researchers. We seek to assess program impacts on subject learning and STEM attraction in majority URM/DA classes and will test the influence of near-peer mentors and an extended inquiry module on these outcomes (Aim 1). We will also measure the persistence of changes in attitudes towards STEM and students’ own sense of identity as researchers. In addition, we will substantially reinforce the accessibility of our curriculum to students of diverse learning needs and deepen its relevance to medicine, public health, and data science (Aim 2). Notably we will build a cloud-based visual workflow to teach students principles of data science when analyzing genomic data produced by students’ experiments.