Field Learning Studio

Context

MEL, evaluation, donor reporting and programme learning teams work with interviews, observations and field notes that rarely arrive in a consistent structure.

Problem

A polished summary can conceal weak evidence, missing provenance or an unreviewed inference. The difficult work is retaining the relationship between source material, analytical claims and the decisions that follow.

Design Principle

Keep the human analyst responsible for qualification and judgment. Make evidence relationships and readiness checks inspectable rather than treating a fluent draft as proof.

System

A human-led, browser-local field learning synthesis app. Local studies connect questions, scope and framework with imported field material and reviewed analytical outputs.

Workflow

1. 01Raw field evidence↓
2. 02Source inventory↓
3. 03Evidence matrix↓
4. 04Findings↓
5. 05Lessons learned↓
6. 06Good practices↓
7. 07Recommendations↓
8. 08QA review↓
9. 09Donor-ready learning brief

Current State

• Local study creation or cloning of read-only showcase cases; questions, scope and framework.
• DOCX, CSV/TSV and structured-note intake with human qualification of observations.
• Findings with supporting, challenging and qualifying evidence relationships.
• Lessons, practices and recommendations developed from reviewed findings.
• Professional Draft assembly, Final Review and controlled working/professional export.
• Browser-local IndexedDB persistence, structured backup and file-inclusive recovery archives.

Interface

Boundaries

Access