Plan post-training nudges that make learning stick
A spaced reinforcement sequence of short practice prompts, reminders, and challenges sent in the weeks after a training session.
The prompt
Plan a reinforcement campaign to send learners after a training program.
Program and objectives: [DETAILS]
Key behaviors to apply on the job: [LIST]
Learners and their work rhythm: [e.g. "nurses on rotating shifts", "remote sales reps"]
Channel: [email, Slack/Teams, LMS app, SMS]
Duration: [e.g. "6 weeks after the workshop"]
Manager involvement: [yes / no]
Design rules:
- Use spaced retrieval: ask learners to recall and apply, not just re-read. Space nudges out with longer gaps over time.
- Mix nudge types: scenario question, quick reflection, on-the-job challenge, peer share, success story, myth vs. fact.
- Each nudge takes under 2 minutes and links to one behavior.
- Write like a colleague, not a marketing email. Make opting into replies easy.
- Include at least one nudge that asks what is getting in the way of applying the learning.
Return:
1. A schedule table: Day | Behavior | Nudge type | Message (ready to send) | Response or action requested.
2. Answer and explanation for every question nudge (sent the next day or on reply).
3. A note on how to adjust if engagement drops.
4. What to measure: response rates, answer accuracy over time, self-reported application, and manager observations.
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
- DETAILS
- LIST
- e.g. "nurses on rotating shifts", "remote sales reps"
- email, Slack/Teams, LMS app, SMS
- e.g. "6 weeks after the workshop"
- yes / no
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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