4 items with this tag.
Audio scholarship—podcasts, dialogues, oral histories—deserves recognition as legitimate scholarly work. The format matters less than the quality of thinking.
The peer-reviewed article dominates academia, but essays deserve recognition as scholarship—enabling exploration and synthesis that formal research cannot.
A multidimensional framework for scholarship spanning discovery, integration, application, and teaching.
This essay critically examines the predominant interface paradigm for AI interaction today—text-entry fields, chronological chat histories, and project folders—arguing that these interfaces reinforce outdated container-based knowledge metaphors that fundamentally misalign with how expertise develops in professional domains. Container-based approaches artificially segment knowledge that practitioners must mentally reintegrate, creating particular challenges in health professions education where practice demands integrative thinking across traditionally separated domains. The text-entry field, despite its ubiquity in AI interactions, simply recreates container thinking in conversational form, trapping information in linear streams that require scrolling rather than conceptual navigation. I explore graph-based interfaces as an alternative paradigm that better reflects how knowledge functions in professional contexts, and where AI serves as both conversational partner and network builder. In this environment, conversations occur within a visual landscape, spatially anchored to relevant concepts rather than isolated in chronological chat histories. Multimodal nodes represent knowledge across different modalities, while multi-dimensional navigation allows exploration of concepts beyond simple scrolling. Progressive complexity management addresses potential cognitive overload for novices while maintaining the graph as the fundamental organising metaphor. Implementation opportunities include web-based knowledge graph interfaces supported by current visualisation technologies and graph databases, with mobile extensions enabling contextual learning in practice environments. Current AI capabilities, particularly frontier language models, already demonstrate the pattern recognition needed for suggesting meaningful connections across knowledge domains. The barriers to implementing graph-based interfaces are less technological than conceptual and institutional—our collective attachment to container-based thinking and the organisational structures built around it. This reconceptualisation of learning interfaces around networks rather than containers suggests an alternative that may better develop the integrative capabilities that define professional expertise and reduce the persistent gap between education and practice.