The job market of today and tomorrow has almost limitless demand for people with computer and data science expertise. But in many high schools, access to these disciplines remains limited to introductory courses. In Chicago Public Schools, the CS4All initiative seeks to integrate CS education at all levels from kindergarten through high school, but many students seek more advanced training to unleash their potential in this growing field.
The Data4All workshop — a joint project of the Center for Data and Computing, Argonne National Laboratory, and Fermi National Accelerator Laboratory — hopes to fill that need by opening a window to data science for high school students on Chicago’s South Side. In the program’s first-ever workshop, held over spring break, a group of seven high school students learned about the basics of data science, how to think critically about data, and the various career pathways available to them with computational skills.
Funded through the AI + Science program by the University of Chicago’s Joint Task Force Initiative and the UChicago Office of Research and National Laboratories, and supported by the Argonne in Chicago Initiative, the workshop united three scientific regional powerhouses to increase awareness of the data science field within South Side youth communities.
Students from Kenwood Academy, Hyde Park Academy, and the University of Chicago Charter School Woodlawn Campus learned from faculty, students, and researchers at UChicago, Argonne, and Fermilab about the power of data to answer important questions in science and society and bring about positive change. Throughout the week, the students applied their new knowledge in group projects using real COVID-19 data, studying the effects of the pandemic across Chicago neighborhoods and demographic groups.
“The main goal of the Data4All workshop was to get the students hooked on data science, and then show them a plethora of pathways through which they can pursue it further, because there really is no one way to go into data science,” said Katherine Rosengarten, administrative specialist for the Center for Data and Computing and co-organizer of the workshop. “We also want to encourage the students’ own interests and ways of thinking critically about data and data science, because we think that the field of data science needs these voices and new perspectives, especially from folks that are historically underrepresented.”
Students learned how to use Jupyter notebooks, Python programming, Kepler data visualization tools, and other technical skills. But more broadly, they learned how to access and work with large datasets, formulate research questions, and think computationally, skills that are applicable to a wide range of fields from scientific research, technology, and finance to art and video game development.
So much of the computer science that students experience in school lacks authenticity,” said John Domyancich, Learning Center Lead at Argonne. “We really designed the curriculum in a way that the students could investigate a question through a deep dive into data, from many angles, and have autonomy and ownership of their work. The feedback that we got from the students was that they appreciated this approach as it helped them see how these skills could be a stepping stone to other questions they might have.”