Supporting Upper Elementary Students in Learning AI Concepts with Story-Driven Game-Based Learning - Gupta, Anisha; Lee, Seung; Mott, Bradford; Chakraburty, Srijita; Glazewski, Krista; Ottenbreit-Leftwich, Anne; Scribner, Adam; Hmelo-Silver, Cindy E.; Lester, James (Proceedings of the AAAI Conference on Artificial Intelligence, 2024)
Artificial intelligence (AI) is quickly finding broad application in every sector of society. This rapid expansion of AI has increased the need to cultivate an AI-literate workforce, and it calls for introducing AI education into K-12 classrooms to foster students’ awareness and interest in AI. With rich narratives and opportunities for situated problem solving, story-driven game-based learning offers a promising approach for creating engaging and effective K-12 AI learning experiences. In this paper, we present our ongoing work to iteratively design, develop, and evaluate a story-driven game-based learning environment focused on AI education for upper elementary students (ages 8 to 11). The game features a science inquiry problem centering on an endangered species and incorporates a Use-Modify-Create scaffolding framework to promote student learning. We present findings from an analysis of data collected from 16 students playing the game's quest focused on AI planning. Results suggest that the scaffolding framework provided students with the knowledge they needed to advance through the quest and that overall, students experienced positive learning outcomes.