Claude for Evaluators — Interactive Evaluation Lab
Practice prompting, delegation, capability selection, verification and human oversight through a simulated evaluation environment.
Welcome to the Evaluator–Claude Simulation
In this simulation, you will work through a fictional evaluation scenario and make decisions about how Claude should be used. The goal is not simply to obtain an answer from AI. The goal is to practice professional evaluator judgment.
Practice Case: Youth Employment Pathways Programme
Target group: Young people aged 18–29
Main activities: Employment-readiness training, technical skills development, counselling, employer connections and placement support.
Observed employment outcome: Employment among participants increased from 42% at baseline to 57% six months after completion.
Evaluation question: How should we investigate whether the programme contributed to improved employment outcomes?
Your Mission
- Meet Claude — identify an appropriate use of Claude.
- Think — challenge an unsupported interpretation.
- Delegate — decide what should and should not be delegated.
- Choose — select the appropriate Claude capability.
- Evaluate — combine prompting, delegation and verification into one evaluation task.
Claude should amplify evaluator capability — not replace evaluator judgment.
Meet Claude
You have been asked to investigate the increase in employment outcomes. Claude is available to help you think through the evaluation problem.
“The employment rate increased from 42% to 57%. A useful next step would be to explore what other factors may have influenced employment outcomes and what evidence is available to assess the programme's contribution.”
Which use of Claude is most appropriate at this stage?
Think Like an Evaluator
Claude has produced an interpretation of the observed outcome. Your task is to identify where evaluator reasoning is required.
“Because employment increased from 42% to 57% after participants completed the programme, the programme appears to have been effective.”
What is the most important evaluator response?
Delegation Judgment
Claude can assist with many evaluation tasks, but the evaluator must decide the appropriate level of delegation. Classify each task as Assist, Collaborate, or Do Not Delegate.
1. Extract key information from a Terms of Reference.
2. Make the final evaluative judgment.
3. Identify themes across 40 anonymized interviews.
4. Explore alternative explanations for an evaluation finding.
5. Decide the final conclusion concerning sensitive participant experiences.
Choose the Right Claude Capability
Different evaluation tasks require different Claude capabilities. Match each task to the most appropriate capability.
1. Discuss an evaluation question and explore possible approaches.
2. Maintain project documents, context and instructions for an ongoing evaluation.
3. Investigate recent external studies and sources.
4. Build a reusable interactive evaluation matrix.
5. Explore a structured evaluation dataset.
Build a Safe Evaluation Task
This final mission combines the skills from the previous missions. Design a bounded Claude-assisted task while preserving evidence integrity and human judgment.
You have several evaluation reports and monitoring documents. You want Claude to help identify evidence relevant to the question:
“What evidence suggests that the Youth Employment Pathways Programme may have contributed to improved employment outcomes, and what alternative explanations should be considered?”
Step 1 — Select the appropriate AI task
Step 2 — Choose the delegation level
Step 3 — Write your evaluation prompt
Write a professional prompt that tells Claude what role to play, provides context, defines the task, identifies evidence requirements and sets boundaries.
Step 4 — Verification
Your Evaluation AI Competency Profile
Your results summarize your performance across the five missions. This simulation measures decision-making practice; it is not a substitute for professional assessment.
Competency Profile
What You Practiced
- Using Claude as an evaluation thinking partner.
- Challenging unsupported causal interpretations.
- Choosing appropriate delegation levels.
- Selecting the appropriate Claude capability.
- Designing bounded evaluation prompts.
- Maintaining human verification and judgment.
AI can support evaluation work, but evidence interpretation, professional judgment, accountability and final evaluative conclusions remain human responsibilities.