An XAI Social Media Platform for Teaching K-12 Students AI-Driven Profiling, Clustering, and Engagement-Based Recommending

Early AI literacy builds critical thinking about social media: The tool teaches grades 4-9 students fundamental concepts about how social media platforms work—data collection, user profiling, engagement metrics, and recommendation algorithms—helping them understand that their online experiences are algorithmically shaped rather than random.

Transparency tools can make complex AI systems understandable to children: By combining an Instagram-like interface with real-time visualizations and explanations of data-driven processes, the researchers demonstrated that young learners can grasp how their actions influence both their own feeds and other users' experiences, making "black box" algorithms more transparent.

Understanding AI systems enhances "data agency" in young people: The paper emphasizes that hands-on experimentation with how platforms collect and use data can increase students' awareness of their own digital footprint and decision-making power, potentially helping them make more informed choices about their online behavior.

AI ethics education should start early: By exposing K-12 students to how engagement metrics drive recommendation systems, the tool cultivates sensitivity to AI ethics issues—such as how platforms may prioritize engagement over user wellbeing—at a formative age when digital habits are developing.

Practical classroom interventions can scale AI awareness: Testing with 209 children across 12 sessions provides evidence that explainable AI educational tools are feasible and can be deployed in real K-12 settings to improve students' understanding of the AI systems they use daily.