AI literacy initiatives in K-12 education frequently emphasize the importance of AI ethics. However, many existing AI ethics curricula offer limited opportunities for students to examine ethical dilemmas or practice ethical decision-making with real-world scenarios. Prior work suggests that games can support ethics education by providing low-stakes, playful environments for exploration and reflection. In this paper, we present Orbiting the VirtueVerse, a scenario-based ethics game designed to introduce middle-school students to virtue ethics in the context of artificial intelligence. We report findings from a research workshop with 22 students aged 13–14. Participants learned about virtue ethics, played the game, and co-designed new scenarios for a future iteration of the game. Our findings suggest that game-based ethical scenarios are a promising approach for supporting students’ ethical understanding of AI. We conclude by offering design guidelines for effectively integrating ethical scenarios into educational games for AI literacy.

Artificial intelligence (AI) is increasingly present in children’s lives, yet few tools support developmentally appropriate AI literacy for grades K-3. This work examines the role of narrative in early AI literacy by directly comparing two versions of interactive game-based digital storybooks for children ages 6-9. The “Book+” condition combined an overarching story and characters with mini-games and scaffolded AI interactions, designed to be enjoyable, provide narrative context, and to give hands-on AI experience. We compared this with a “Game” condition that included the same learning goals, mini-games, and AI interactions but replaced the narrative with primarily instructional text. Across 57 participants, both conditions elicited high engagement, but “Book+” participants showed significantly greater learning gains and higher perceived knowledge. Qualitative findings revealed that while both groups enjoyed the creative AI mini-games, “Book+” participants more frequently used AI vocabulary in responses, connected concepts to the learning context, and expressed stronger emotional connection.

Children regularly negotiate questions of authority and control in home and school life, but little is known about how they believe robots should fit into these dynamics. We conducted a 75-minute design session with 17 children (ages 6-9) to examine when robots should take, share, or defer control, and how expectations shift when robots are framed as teachers, classmates, or mentees. Children resisted robot control, particularly in adult-regulated domains and areas tied to personal skill or self-expression. They were more open to robot control in domains where they felt less competent, or where robots, perceived as less legitimate authorities than humans, could substitute for adult control. Role framing further shaped expectations: teacher robots were granted autonomy, classmate robots were expected to act as peers, and mentee robots were expected to defer. These findings show that children apply context- and role-sensitive rules when negotiating control with robots. We conclude with design considerations for robots in children's everyday lives that respect children's agency, calibrate autonomy by domain, and align behavior with children's context-sensitive expectations.

As generative AI (GenAI) emerges as a transformative force, clear understanding of high school students' perspectives is essential for GenAI's meaningful integration in high school environments. In this work, we draw insights from a participatory design workshop where we engaged 17 high school students -- a group rarely involved in prior research in this area -- through the design of novel GenAI tools and school policies addressing their key concerns. Students identified challenges and developed solutions outlining their ideal features in GenAI tools, appropriate school use, and regulations. These centered around the problem spaces of combating bias & misinformation, tackling crime & plagiarism, preventing over-reliance on AI, and handling false accusations of academic dishonesty. Building on our participants' underrepresented perspectives, we propose new guidelines targeted at educational technology designers for development of GenAI technologies in high schools. We also argue for further incorporation of student voices in development of AI policies in their schools.

Artistic creation is often seen as a uniquely human endeavor, yet robots bring distinct advantages to music-making, such as precise tempo control, unpredictable rhythmic complexities, and the ability to coordinate intricate human and robot performances. While many robotic music systems aim to mimic human musicianship, our work emphasizes the unique strengths of robots, resulting in a novel multi-robot performance instrument called the Beatbots, capable of producing music that is challenging for humans to replicate using current methods. The Beatbots were designed using an “informed prototyping“ process, incorporating feedback from three musicians throughout development. We evaluated the Beatbots through a live public performance, surveying participants$(N=28)$to understand how they perceived and interacted with the robotic performance. Results show that participants valued the playfulness of the experience, the aesthetics of the robot system, and the unconventional robot-generated music. Expert musicians and non-expert roboticists demonstrated especially positive mindset shifts during the performance, although participants across all demographics had favorable responses. We propose design principles to guide the development of future robotic music systems and identify key robotic music affordances that our musician consultants considered particularly important for robotic music performance.

Social-emotional learning (SEL) skills are essential for children to develop to provide a foundation for future relational and academic success. Using art as a medium for creation or as a topic to provoke conversation is a well-known method of SEL learning. Similarly, social robots have been used to teach SEL competencies like empathy, but the combination of art and social robotics has been minimally explored. In this paper, we present a novel child-robot interaction designed to foster empathy and promote SEL competencies via a conversation about art scaffolded by a social robot. Participants (N=11, age range: 7-11) conversed with a social robot about emotional and neutral art. Analysis of video and speech data demonstrated that this interaction design successfully engaged children in the practice of SEL skills, like emotion recognition and self-awareness, and greater rates of empathetic reasoning were observed when children engaged with the robot about emotional art. This study demonstrated that art-based reflection with a social robot, particularly on emotional art, can foster empathy in children, and interactions with a social robot help alleviate discomfort when sharing deep or vulnerable emotions.