Write measurable IEP goals from a student's present levels
Turns present levels of performance into measurable annual IEP goals, short-term objectives, and progress-monitoring plans.
The prompt
Help me write measurable IEP goals for a student.
Grade and disability category: [e.g. "4th grade, specific learning disability in reading"]
Present levels (PLAAFP): [CURRENT DATA - e.g. "reads 52 words correct per minute on grade 2 passages, 88% accuracy"]
How the need affects access to the general curriculum: [DETAILS]
Areas to target: [e.g. reading fluency, written expression, self-regulation]
Grade-level standards involved: [STANDARDS or "suggest"]
Services and setting: [e.g. "30 min/day resource room plus push-in"]
For each area:
1. Write one annual goal with all four parts: condition (given what), behavior (observable verb), criterion (how well, how often), and timeframe.
2. Check the baseline-to-target jump is ambitious but realistic for one year; flag any goal with no baseline in my present levels.
3. Add 2-3 short-term objectives or benchmarks.
4. Name the progress-monitoring tool, how often data is collected, and who collects it.
Rules:
- No vague verbs ("will understand", "will improve"); every goal must be countable or scorable.
- Do not invent assessment scores. Use [ADD BASELINE] where data is missing.
- Keep wording family-friendly; define any jargon in parentheses.
Return a table (Area | Baseline | Annual goal | Objectives | Measurement and frequency), then a short list of present-levels data I should gather before the meeting. Final goals must be decided by the IEP team and meet your state's requirements.
Highlighted [brackets] are blanks to replace with your own details.
Fill in the blanks and use this promptMore Learning & Teaching prompts
What to fill in
- e.g. "4th grade, specific learning disability in reading"
- DETAILS
- e.g. reading fluency, written expression, self-regulation
- STANDARDS or "suggest"
- e.g. "30 min/day resource room plus push-in"
- ADD BASELINE
How this prompt is built
This prompt follows the Few-Shot structure (Few-shot prompting). A few-shot prompt includes one or more worked examples of the input and the output you want, so the model can copy the pattern instead of guessing it.
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