Sushmita Khan
Clemson University, Clemson, South Carolina, United States
With the pervasive and evolving use of tracking and AI to make inferences about online platform users, it has become imperative for adolescents---a key demographic using such platforms---to develop a deep understanding of these practices to protect their privacy. Traditionally, K-12 cybersecurity education has largely been confined to extracurricular activities, limiting underrepresented students' access. To resolve this shortcoming, we partnered with a rural-identifying middle school to deliver AI-related privacy education in classrooms. Using Design-Based Research methodology, we identified students' AI-related privacy learning needs and developed six education modules. This paper focuses on the design, classroom implementation, and evaluation of module \#2, covering the privacy threats of Tracking and Pervasive Personalization (TaPP). Student assessment outcomes show they developed transferable foundational knowledge of the privacy implications of tracking and personalization after participating in the TaPP module. Our findings demonstrate the benefits of integrating AI-related privacy education into existing K-12 curricula.
doi.org/10.1145/3613904.3642460
The ACM CHI Conference on Human Factors in Computing Systems (https://chi2024.acm.org/)