Menu
Design specifications for dissertation figures such as conceptual frameworks, concept-card/interview process diagrams, AI-agent workflow diagrams, adoption-condition models, and findings maps.
Installer avec Codex ou Claude Copiez ce prompt, collez-le dans Codex, Claude ou un autre assistant, puis laissez-le vérifier la page du skill et l'installer pour vous.
Basé sur la classification professionnelle SOC
| name | dissertation-figure-spec |
| description | Design specifications for dissertation figures such as conceptual frameworks, concept-card/interview process diagrams, AI-agent workflow diagrams, adoption-condition models, and findings maps. |
Use when planning or creating diagrams and figure descriptions for the dissertation.
Before delivering a figure spec, check:
A caption should state:
Avoid captions that simply repeat labels from the figure.
Recommended near-term figures:
Create or update files under figures/, such as:
figures/FIGURE_SPECS.mdfigures/conceptual-framework.mmdfigures/methodology-flow.mmdfigures/utaut-adoption-framework.mmdDo not use participant-identifiable details in figures.
Do not create a polished visual that makes tentative or planned claims look like findings.
Design and review active learning implementation support for university teachers, including classroom activity structures, preparation workflow, student participation, assessment alignment, and AI-agent support points.
Turn dissertation evidence into an AI agent design specification for supporting active learning implementation, including user scenarios, functions, interaction flow, boundaries, failure modes, and design rationale.
Synthesize confirmed co-design, design-elicitation, prototype-feedback, or participant-generated design outputs into requirements, design principles, prototype changes, participant contribution maps, and design decision logs.
Maintain a lightweight dissertation research wiki with project memory, literature notes, methodology decisions, supervisor feedback, design rationale, and open questions.
Audit an AI agent prototype or design concept for usability, pedagogical fit, teacher feedback, active learning support, evidence quality, and next design iterations.
Build and audit a teacher adoption conditions model for an AI agent supporting active learning, distinguishing perceptions, concerns, barriers, enablers, institutional conditions, and design implications.