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Generative AI Prompting Tips for Trainers
Generative AI Prompting Tips for Trainers
Content
In this learning activity, you will explore the journey of Artificial Intelligence — from the early days of logic and theory to the modern era of Generative AI. This activity helps you understand how we got here, how AI thinks, and how to communicate effectively with it using high-quality prompts.
Understanding Artificial Intelligence: From Logic to Generative AI
Artificial Intelligence (AI) is the field of computer science that enables machines to perform tasks that typically require human intelligence — such as reasoning, problem-solving, recognising patterns, and generating ideas.
Historical overview:
- 1950s – The Big Question: Alan Turing’s paper “Computing Machinery and Intelligence” asked, “Can machines think?”, laying the foundation for AI. The term Artificial Intelligence was first introduced at the Dartmouth Workshop in 1956.
- 1970s–1990s – AI Winters: Progress slowed because of limited computing power and funding. Early logic systems, based on the work of George Boole and Gottlob Frege, were accurate but could not handle complexity.
- 1990s–2010s – AI Awakens: With faster processors and more data, AI began learning patterns, predicting trends, and recognising images and text. Landmark moments include IBM’s Deep Blue defeating chess champion Garry Kasparov in 1997.
- 2010s–Present – The Deep Learning Revolution: The combination of big data, powerful GPUs, and neural networks made AI systems capable of human-level image recognition and creative problem-solving.
- 2020s – The Generative AI Boom: Models like GPT, DALL·E, and Midjourney generate text, visuals, and ideas, showing how machines can now collaborate creatively with humans.
How Generative AI Works
Generative AI systems are trained on large datasets and can predict the most likely next word, image, or idea based on what they’ve learned. They don’t think like humans; instead, they recognise and reproduce patterns.
A well-written prompt gives AI a clear understanding of what you want, in what form, and for which audience. The better your prompt, the more accurate, relevant, and creative the AI’s response will be.
Watch:
How to prompt AI
- Start with context – AI needs background information to give meaningful answers.
- Be specific and focused – Ask for one task at a time.
- Use active verbs – “Design,” “Explain,” “Compare,” or “Summarise” work better than vague requests.
- Give examples – Show AI what type of response you expect.
- Set limits – Mention tone, format, or word count.
- Iterate – Refine your prompt gradually; each version improves the output.
- Stay critical – Always check AI results for accuracy and appropriateness before using them.
CRISPY model for prompting
C - Context
R - Role
I - Instruction
S - Specificity/Constraints
P - Personal/Tone
Y - Yield (Output/ form/ Length)
C - Context
Set the scene: Provide background information or situational details that help AI understand the setting, purpose, and audience of your request before generating a response. The more context you give, the more relevant and accurate the answer will be
R - Role
Assign a role: Specify the perspective or identity AI should take. Tell AI who it should be while answering — a youth trainer, project manager, facilitator, researcher, etc. Roles shape the voice and level of expertise in the response.
I - Instruction
State the task clearly: Clearly describe the main task or action you want AI to perform, such as writing, analyzing, summarizing, or creating, to ensure focused and relevant output. Clear instructions lead to useful results.
S - Specificity/Constraints
Add details and limits: Clearly state any restrictions related to the word count, format, style, or focus area of the response, such as avoiding jargon, staying within a word limit, or addressing a specific topic only. Specific constraints help AI stay on track and reduce irrelevant or overly broad answers.
P - Personal/Tone
Guide the voice: Define the desired tone, mood, or communication style of the response, or Say how you want it to sound - formal, playful, inspiring, youth-friendly, academic, etc. Tone makes the output fit your audience and purpose.
Y - Yield (Output/ form/ Length)
Define the final product: Tell AI what you expect, Indicate the preferred final format and scope of the response, such as a bullet list, one-paragraph summary, 10-slide presentation, or 2-minute speech script.
Prompting Practice: From Bad to Brilliant
Weak prompt:
“Write a training agenda on teamwork.”
Improved prompt using CRISPY:
- Context: I’m planning a 90-minute workshop for youth workers on teamwork skills.
- Role: Act as an experienced trainer in youth leadership and non-formal education.
- Instruction: Create a structured session plan with short activities and discussion points.
- Specificity: Focus on cooperation, active listening, and shared responsibility.
- Personal/Tone: Use an encouraging and practical tone.
- Yield: Provide the session plan in bullet points.
Compare the results from both prompts. Notice how the CRISPY version gives the AI enough structure to produce a clear, relevant, and well-organised output.
You will find more exercises for prompting, please download the worksheet from the Resources section.
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This badge recognises the earner’s ability to understand the fundamentals of Artificial Intelligence and to apply the CRISPY framework to create precise, well-structured prompts for Generative AI. The earner demonstrates confidence in using AI as a creative and supportive tool for training and facilitation.
To earn a badge, learners provide a short reflection summarising what they learnt about AI prompting.
Badge issuer: International Youth Work Trainers Guild
Tasks
Task no.1
Evidence verified by: self-approved
Share your learning outcomes from the Prompting Practice section: describe what you discovered about designing effective prompts
Skills
#Artificial Intelligence in Training
Organisers
International Youth Work Trainers Guild
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