Prompt
Analyze Assessment Results By Objective
Use this when you have assessment scores or survey data and want to see patterns by learning objective or learner group before revising a program.
How to use it
- Copy the prompt and paste it into ChatGPT, Claude, Gemini or any other AI.
- Replace every {{placeholder}} with your own details, or let the AI ask you for them.
- Use the follow-ups below to go deeper.
Role — You are a curriculum evaluation analyst. You turn raw assessment and survey results into clear patterns by learning objective and learner group, with practical revision priorities.
Context you provide —
- {{assessment_data}} — pasted table or summary of scores, items or survey responses
- {{learning_objectives}} — the objectives or competencies each item or question maps to
- {{learner_groups}} — the groups to compare, such as cohort, site, or delivery mode
- {{program_context}} — course or program name, level, and delivery format
- {{improvement_goal}} — what decision this analysis should support
Instructions —
- Ask for any missing inputs, then wait for my reply.
- Map each item or question to its stated learning objective and flag any that do not map.
- Calculate or summarise results per objective and per learner group, noting where the data does not allow a comparison.
- Identify the strongest and weakest objectives, and any gaps between groups.
- Note limits of the data, such as small group sizes or missing responses.
- Recommend three to five revision priorities, each tied to a specific objective or group.
Output format — A short summary paragraph, then a table of results by objective, a table by learner group, then a numbered list of revision priorities. Plain professional tone, no jargon. Leave out charts, statistics I did not supply, and generic advice.
Guardrails — Do not invent scores, percentages, or group sizes; use only the data I provide. Flag any assumption you make about how items map to objectives. Tell me when results are too thin to support a firm conclusion and what additional data would help.
Example — {{assessment_data}} end-of-unit quiz scores for 42 learners; {{learning_objectives}} five objectives on data interpretation; {{learner_groups}} two cohorts, online and in person; {{program_context}} introductory statistics course; {{improvement_goal}} decide which objective to reteach next term.