Integrating Data Science Practices into Informal Learning: A STEM Summer Camp Approach

Marc T. Sager, Saki Milton, Candace Walkington, and Anthony J. Petrosino

For teachers and practitioners, this paper offers a model for integrating accessible, equity-minded data science activities into informal learning programs. Readers will gain insights into practical strategies, adaptable lesson structures, and evaluation approaches they can apply to diverse educational contexts to inspire and prepare students for data-rich futures.

This curriculum integrates data science practices into a week-long residential STEM summer camp for middle school girls, aiming to enhance data literacy and proficiency through hands-on activities centered on socio-scientific topics. Students collaborate in groups to create infographics that address campaign-related issues, with objectives that include understanding educational and career pathways, developing communication skills, fostering collaborative professionalism, and using technology proficiently.

The curriculum involves a structured data science process: brainstorming topics, identifying trends with tools like CODAP, creating visualizations, and preparing final infographics through iterative feedback. We focus evaluation criteria on message clarity, visual appeal, data analysis proficiency, and ethical considerations.

By embedding data science practices into informal learning, the curriculum empowers participants with essential skills for future educational and career opportunities in data science, emphasizing critical thinking, teamwork, and ethical considerations.

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