Design Thinking in Admissions: A Qualitative Playbook

Evidano is an AI-powered qualitative data analysis platform that converts design-thinking workshop artifacts into auditable, reproducible thematic syntheses to inform admissions pilots and policy.

Design thinking workshops can rapidly surface many actionable ideas, and an AI-enabled synthesis turns those artifacts into defensible evidence for decision-makers.

• A Jan 2025 UNC DT session (n=15) produced ~76 brainstormed ideas, 43 ideas prioritized across 3 themes, and 4 prototypes, demonstrating high generative yield.
• The UNC study used inductive thematic coding with 90.5% inter-coder agreement and a 94% post-workshop survey response rate, useful benchmarks for synthesis quality.
• Teams can ingest photos, facilitator notes, and vote tallies to produce cross-segment comparisons and audit trails before piloting changes.

The study ran a structured design-thinking (DT) session with purposively sampled admissions stakeholders to reframe problems, generate divergent solutions, and draft low-fidelity prototypes.

The study collected physical artifacts (chart paper, worksheets), facilitator notes, and a brief post-workshop survey that achieved a 94% response rate.

Analysis in the study used inductive thematic coding with 90.5% inter-coder agreement, while quantitative responses were reported descriptively (for example, creative problem solving M=4.7 ±0.5).

• Primary focal areas were interview restructuring, GenAI integration/compliance, and broadening admissions criteria.
• Examples of ideated tactics included task-based live writing stations to preclude GenAI, technology-mediated monitoring, GenAI-assisted rubric generation, and adding timed writing to candidate days.
• The study was generative and exploratory, single-site with a small purposive sample, appropriate for ideation rather than outcome claims.

This checklist provides a seven-step runbook to convert a DT session into decision-ready insight.

• 1) Collect artifacts: photos, worksheets, facilitator notes, and vote tallies, then export them into one folder.
• 2) Ingest files into Evidano and run auto-transcription with an optional custom dictionary for domain terms.
• 3) Auto-suggest initial codes and import your manual codebook; run AI-assisted coding to tag quotes and artifacts.
• 4) Compute code frequencies, cross-segment comparisons (role, vote count), and co-occurrence networks.
• 5) Validate top themes with member-checking by generating a one-page summary and running a short AI-facilitated follow-up with selected stakeholders.
• 6) Prototype remotely by using AI avatars to simulate candidate tasks (for example, critique a GenAI essay) and collect structured responses.
• 7) Produce an exportable synthesis (slides plus an appendix of raw quotes and an audit trail) for the admissions committee.

Design thinking produces rich, stakeholder-driven ideas quickly, and the UNC workshop published June 23, 2026, shows how a small, well-structured session can yield dozens of actionable leads (n=15, ~76 ideas).

• Run a DT session, ingest artifacts into Evidano, and produce an auditable thematic synthesis plus cross-segment comparisons.
• Pilot one low-cost prototype (for example, a timed writing MMI station) and measure candidate experience and equity outcomes before scaling.
• If you want to try this pipeline, Try Evidano for free or learn more at Evidano and import your first workshop to generate a shareable synthesis in hours, not weeks.