Peer-led coding camps boost children’s interest in AI and programming

A Penn State-led study reveals that children are more engaged in coding and AI when lessons are led by peers close to their age, highlighting the potential of youth-led informal learning in fostering interest and confidence in STEM subjects.

A Penn State-led study suggests that children may be more willing to explore coding and artificial intelligence when the lessons come from someone only a few years older than they are. The work centres on Khushi Kharuna, a high school student outside Philadelphia who built and ran summer camps for younger pupils, and Priya Kumar, a professor in Penn State’s College of Information Sciences and Technology, who studies how young people learn and move through digital spaces.

The researchers looked at two community-based camps Kharuna hosted in summer 2025 at local libraries for children aged 11 to 15. One focused on Python, while the other introduced basic artificial intelligence and machine learning. Among 35 participants, surveys, comments and researcher observations pointed to strong engagement, with campers describing the sessions as enjoyable and more appealing than typical school coding lessons. After the camps, the children also reported greater interest in programming and AI.

Kumar said the findings support a growing body of research showing that informal STEM settings can do more than supplement school lessons. Previous studies have found that out-of-school programmes can strengthen STEM identity, confidence and career interest, particularly when young people have hands-on activities, mentoring and space to take ownership of their learning. Research on informal STEM education has also highlighted the value of “grounded fun”, agency and authentic experiences for pupils who are often under-represented in science and technology.

The broader lesson, according to the Penn State team, is that youth-led learning may help children imagine themselves in computing by making the classroom feel less hierarchical. In this model, younger learners are not just being taught; they are seeing someone close to their own age succeed, explain difficult ideas and adapt activities in real time. That, Kumar said, can make abstract subjects feel more accessible and personally relevant.

Kharuna’s path into teaching began after a STEM conference she attended in eighth grade, where she saw older girls building robots and apps with confidence. She started by teaching herself to code, then launched an eight-week camp in her basement before local libraries opened their doors to her programme. Since then, she has turned what began as a local effort into a research collaboration, giving talks in Philadelphia and preparing to join a Penn State forum on youth and AI. The work now points to a practical message for schools and community groups: if adults create the space, young people can help lead the learning.