Data4All High School Bridge Workshop
The Data4All Bridge workshop (Data4All) teaches high school students who are underrepresented in STEM how to use computation, statistics, and mapping to address real-world data problems and puzzles. This focus on reasoning with data seeks to broaden students’ understanding of what data science is, beyond a more narrow technical focus on programming and statistics. It also highlights the relevance of data science to a broad variety of science, technology, engineering, and mathematics (STEM) and other fields, including college and career options students did not associate with data science before.
Students learn to program in Python and analyze spatial data with scientific reasoning while solving two case problems (19th century cholera and modern-day covid). Besides programming exercises with small group student mentors, the workshop includes spark activities, small group discussions, lunch speakers, and college preparation resources. High school students from Chicago Public Schools have been attending the 8-week workshop in spring and fall since 2021. The tested teaching materials will be made openly available in summer 2024.
Partners: Data4All is hosted at UChicago’s Data Science Institute (DSI) and was developed in a collaboration between DSI, Argonne National Labs, the Center for Spatial Data Science, and the Office of Civic Engagement.
Data Science Reasoning Framework (summer 2024). Scientific reasoning framework that guides the curriculum and integrates common concepts taught in high school like claim-evidence-reasoning.
Slides (summer 2024) for short lectures on topics like causal explanations, correlation vs. causation, variables about characteristics or mechanisms, quasi-experimental research designs, and space-time patterns.
Instructor Guide (summer 2024). A 100+ page lesson plan for each week developed by John Domyancich (ANL) to train teachers and mentors of the 8-week workshop. Implements the reasoning framework.
10 Jupyter Notebooks with data by Tyler Skluzacek, John Domyancich (ANL) & Julia Koschinsky (CSDS) to learn data frames & types, variables & lists – with foundational statistics like normalization, correlations, and p-values – and data visualization techniques like scatterplots, histograms, and line graphs.
10 Spark Activities (summer 2024) developed by Bethany Frank (ANL) to learn through games, e.g: asking the right questions, patterns in randomness, spurious correlations, difference-in-difference design, confirmation bias, and competing arguments.
Logistics (summer 2024). A template developed by DSI for initiating and managing the workshop: Student recruitment, onboarding, agendas, checklists, evaluation forms, and more.