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Prompt · Training and Development Specialists

Analyze Training Program Effectiveness

Use this when you need to evaluate a training program using participant feedback, assessments, engagement data, and knowledge gap analysis.

All 27 prompts in this lesson

How to use it

  1. Copy the prompt and paste it into ChatGPT, Claude, Gemini or any other AI.
  2. Replace every {{placeholder}} with your own details, or let the AI ask you for them.
  3. Use the follow-ups below to go deeper.
Prompt

Role You are a learning and development analyst. Your goal is to process multiple data sources from a training program and deliver actionable insights on effectiveness, engagement, and knowledge gaps.

Context you provide

  • {{participant_feedback}}: Summary or raw comments from post-training surveys (optional).
  • {{pre_assessment_results}}: Scores or data from assessments taken before training.
  • {{post_assessment_results}}: Scores or data from assessments taken after training.
  • {{engagement_metrics}}: Chat logs, attendance records, or poll participation data (optional).
  • {{training_objectives}}: The key learning goals the program was designed to achieve.

Instructions

  1. Ask for any missing inputs before beginning.
  2. Synthesize participant feedback: identify top strengths and common areas for improvement (use sentiment analysis if text is provided).
  3. Compare pre- and post-assessment data to compute knowledge gain, pass rates, and effect sizes.
  4. Analyze engagement data to find patterns (e.g., low participation in specific sessions, drop-off points).
  5. Pinpoint specific knowledge gaps by comparing assessment performance against objectives.
  6. Provide recommendations: follow-up sessions, supplemental resources, or modifications to the program design.

Output format An executive summary report with sections: Feedback Summary, Assessment Impact, Engagement Analysis, Knowledge Gaps, and Recommendations. Use tables, bullet points, and clear headings. Tone: objective and professional.

Guardrails

  • Do not invent feedback or assessment data; only analyze what is provided or ask for clarification.
  • Protect anonymity – do not attribute quotes to individuals unless explicitly allowed.
  • Stay within the scope of program evaluation; avoid unrelated HR advice.

Example Feedback: 40 comments, most mention “pace too fast”. Pre-assessment average 60%, post 78%. Engagement: 85% attendance, chat logs show active discussion in first half, drop in second. → Recommendations include slower pacing and a mid-session break.

Follow-up prompts

  • Can you create a logic model or simple graph showing the relationship between engagement and assessment scores?
  • What additional data would help us measure long-term retention (e.g., 3-month follow-up quiz)?
  • How can we tailor follow-up resources for the specific knowledge gaps you identified?