| name | teacher-adoption-modeling |
| description | 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. |
Teacher Adoption Modeling
Use when the user asks to analyze teacher perceptions, concerns, adoption conditions, barriers, enablers, readiness, or implementation conditions.
Core Distinctions
Keep these categories separate:
- perceptions: how teachers understand or value the AI agent
- concerns: worries, risks, doubts, or objections
- barriers: practical or structural obstacles
- enablers: factors that make adoption easier
- conditions for adoption: requirements that must be met for acceptable use
- design implications: how the agent should change in response
- institutional implications: policy, training, workload, support, governance
Workflow
- Read relevant findings, codebooks, or theme tables.
- Extract adoption-related evidence.
- Group evidence by category.
- Identify relationships:
- concern -> condition
- barrier -> support mechanism
- perceived benefit -> design priority
- institutional constraint -> governance implication
- Draft a model that can be represented as:
- table
- matrix
- conceptual diagram
- chapter subsection
- Flag unsupported or overgeneralized adoption claims.
Output
Create or update:
models/TEACHER_ADOPTION_MODEL.md
models/ADOPTION_CONDITIONS_MATRIX.md
figures/adoption-conditions-model.mmd
Guardrails
Do not flatten teacher concerns into generic "resistance".
Do not imply causal relationships unless the study design supports them.