arXiv:2604.06200v1 Announce Type: cross
Abstract: Designing project-based learning (PBL) demands managing highly interdependent components, a task that both traditional linear tools and purely conversational AI struggle with. Traditional tools fail to capture the non-linear nature of creative design, while conversational systems lack the persistent, shared context necessary for reflective collaboration. Grounded in theories of distributed cognition, we introduce CoMAP, a system that embodies a graph-based collaboration paradigm. By providing a shared visual workspace with dual-modality AI support, CoMAP transforms the human-AI relationship from a prompt-and-response loop into a transparent and equitable partnership. Our study with 30 educators shows CoMAP significantly improves teachers’ design expression, divergent thinking, and iterative practice compared to a dialogue-only baseline. These findings demonstrate how a nonlinear, artifact-centric approach can foster trust, reduce cognitive load, and textcolorfixsupport educators to take control of their creative process. Our contributions are available at: https://comap2025.github.io/.
Assessing nurses’ attitudes toward artificial intelligence in Kazakhstan: psychometric validation of a nine-item scale
BackgroundArtificial intelligence (AI) is increasingly integrated into healthcare, yet the attitudes and knowledge of nurses, who are the key mediators of AI implementation, remain underexplored.


