Generative AI is increasingly used in learning environments, but most systems focus on generating responses rather than supporting interaction. This limitation is especially important for blind and visually impaired (BVI) learners, who rely on non-visual ways to navigate and understand programming tasks. We present findings from a co-design study with BVI high school students exploring expectations for AI assistants in expressive computer science learning. Participants described how AI could support accessible interaction, guide learning, and empower learner agency. We derive two design principles for inclusive AI assistants: (1) situated multimodal interaction and (2) scaffolded iterative interaction. These principles shift the focus from adapting outputs (e.g., audio) to designing interactions that support how learners navigate and engage in the CS learning context. Our work highlights the importance of interaction design in accessible AI and the value of involving BVI learners in the design of AI-powered educational technologies.

The rapid growth of generative AI in education has deepened the need for both responsible AI practices and AI literacy. However, these domains are often addressed separately, leaving a gap in guidance for educators, designers, developers, and researchers. This paper presents a conceptual framework that connects responsible AI principles with AI literacy and introduces its application through a practical checklist as a toolkit, with a hypothetical case example, which offers actionable prompts for responsible use of AI in educational and design contexts. Together, the TEACH-RAI framework and toolkit aim to provide both theoretical grounding and accessible resources to foster responsible engagement with AI in the educational context.

Expressive computer science (CS) learning environments teach coding through the creation of an artifact, such as audio or video output.EarSketch is an expressive CS learning environment designed to teach computing through music production, mixing and arranging sounds using code.In this paper, we explore the accessibility challenges of using EarSketch for learners who are Blind and Visually Impaired (BVI).We present key findings from co-design studies with teachers and students at an institution specializing in BVI education, focused on gathering both groups' unique perspectives about EarSketch's ability to support teachers' curricula, students' workflows using the system with accessibility software, and challenges faced by users who are BVI.

This study conducts a novel approach to redesign EarSketch, an expressive computer science (CS) learning environment that integrates music composition into computing education, with a specific focus on inclusivity for blind and visually impaired (BVI) learners. This approach centers on the participation of teachers, students, and the community as co-designers, leveraging their insights and experiences to enhance the program’s accessibility and effectiveness. By actively involving the stakeholders in the development process, the study aims to address the unique educational challenges and needs of learners who are visually impaired more effectively. The participatory design approach is expected to not only maintain the intrinsic appeal of EarSketch but also to expand its accessibility, ensuring that it becomes a more inclusive tool in computer science education. The ultimate goal is to establish a more adaptable and inclusive educational paradigm within STEAM, particularly in computing education and music, that is responsive to the diverse needs of all students, including those with visual impairments. The contributions of this paper are design recommendations based on our data that can be applied to the design of EarSketch and other expressive CS environments for BVI learners.