As artificial intelligence (AI) becomes increasingly central to healthcare and biomedical research, there is a growing need for learning experiences that help students understand AI concepts while envisioning future career pathways. This paper presents a theory-informed narrative-centered model designed to foster AI literacy and support emerging interest in biomedical careers among early adolescents aged 11-14. Grounded in narrative-centered learning and social cognitive theory, the model articulates how narrative structure, role-based engagement, and consequential decision making can support self-efficacy development, conceptual understanding, and interest in AI-enabled biomedical work. Building on this framework, we describe the design of a narrative-centered educational game in which learners assume the role of a medical intern and investigate patient cases using AI diagnostic tools. We then report findings from a pilot study with 25 students who played the game and participated in focus groups, drawing on gameplay trace data, in-game reflections, and qualitative feedback. Findings suggest high engagement, productive use of AI tools, and evidence of increased awareness of biomedical applications of AI, along with indications of perceived understanding of AI concepts. Together, the theoretical model, game design, and pilot findings illustrate how narrative-centered educational games can serve as research platforms while providing insight into how youth reason about AI in career-connected learning contexts.

As AI becomes increasingly central to healthcare and biomedical research, there is a growing need for tools that introduce students to AI in engaging, authentic contexts. This paper presents AI4Health, a narrative-centered educational game that places middle school students in the role of a medical intern investigating real-world health mysteries. In the game's first episode, players gather evidence, interview characters, and use machine learning models with different training data and performance characteristics. Through branching dialogue and contextual problem-solving, players explore the impact of training data on model reliability and consider the ethical implications of AI-assisted diagnosis. This paper showcases the core mechanics, dialogue system, and interactive narrative structure that support AI literacy and health career exploration, and highlights plans to extend the game through additional biomedical scenarios and classroom integration.

As artificial intelligence (AI) continues to transform industries across society, it is having a profound impact on healthcare and biomedical research. To prepare students for this evolving landscape, there is a growing need for learning experiences that build foundational AI literacy and connect to real-world career pathways. However, most middle school students lack access to engaging and personally meaningful opportunities in AI education and career exploration. NarrativeCentered Learning (NCL) offers powerful affordances for contextualizing AI literacy through engaging storylines and role-based problem-solving. In parallel, Social Cognitive Career Theory (SCCT) emphasizes how students' beliefs about their abilities, expectations about outcomes, and personal goals influence the development of their academic and career trajectories. This paper introduces a design framework that integrates NCL and SCCT to foster both AI literacy and health-related career interest. We apply this framework to the design of a narrative game in which students take on the role of a medical intern investigating virtual patient cases using AI tools. We report findings from a usability study with 25 middle school students who played the game's first episode and participated in structured focus groups. Student feedback suggests that the game supported engagement, sparked curiosity, and encouraged emerging career interest. These findings offer preliminary support for the framework and inform the design of career-connected AI learning.