High School Summer Camps Help Democratize Coding, Data Science, and Deep Learning

TL;DR

The paper investigates on-campus, week-long high school camps that teach coding, data science, and deep learning, aiming to democratize access to computational education and reduce STEM disparities. It uses a three-level curriculum, on-campus immersion, and a mentorship network spanning undergraduates, graduates, and faculty, complemented by post-camp interviews and surveys. Findings indicate significant gains in coding confidence and a strong interest in AI and data science careers (68.6%), with nuanced preferences for topics like machine learning, data science applications, and ethics. The study demonstrates that structured, mentored, collaborative camp environments can broaden participation in computational fields and offers practical guidelines for designing scalable equity-focused STEM programs.

Abstract

This study documents the impact of a summer camp series that introduces high school students to coding, data science, and deep learning. Hosted on-campus, the camps provide an immersive university experience, fostering technical skills, collaboration, and inspiration through interactions with mentors and faculty. Campers' experiences are documented through interviews and pre- and post-camp surveys. Key lessons include the importance of personalized feedback, diverse mentorship, and structured collaboration. Survey data reveals increased confidence in coding, with 68.6\% expressing interest in AI and data science careers. The camps also play a crucial role in addressing disparities in STEM education for underrepresented minorities. These findings underscore the value of such initiatives in shaping future technology education and promoting diversity in STEM fields.

Figures (2)

• Figure 1: Progression through the levels of the program
• Figure 2: Mentorship Structure in the Camp Program