Why Prompt Engineering Matters to L&D Professionals?


Prompt engineering is revolutionizing eLearning by empowering L&D professionals to streamline workflows, boost creativity, and produce high-quality content efficiently using AI. By mastering precise AI instructions, instructional designers can enhance every phase of the ADDIE model, leading to improved analysis, design, and development of eLearning courses. Real-world examples demonstrate its potential in content summarization, learning objectives generation, and scenario design, while ethical considerations ensure responsible AI use. Embrace AI and prompt engineering to transform your eLearning strategies and achieve exceptional results.

Picture this: You’re an instructional designer, knee-deep in creating a new e-learning course. Your to-do list seems endless: outlining content, crafting learning objectives, designing assessments, and more. Wouldn’t it be nice to have a brilliant assistant who could help you brainstorm ideas, summarize content, and draft scripts for your videos? Enter the world of AI and prompt engineering, your new secret weapon.

But wait, before you run away thinking, “Oh no, not another tech thing I need to learn!,” let me assure you, prompt engineering isn’t just for the tech wizards among us. It’s a skill that every L&D professional can (and should) master to supercharge their workflow and creativity. So, get comfy and let’s explore why prompt engineering matters to you and how it can transform your L&D game.


What on Earth is Prompt Engineering?

First things first, let’s demystify this fancy-sounding term. Prompt engineering is essentially the art of talking to AI in a way that makes it understand exactly what you want. It’s like being a really good communicator, but instead of chatting with your colleagues, you’re chatting with an AI.

Imagine you’re at a coffee shop, trying to order your perfect latte. You could say, “I want coffee,” but that’s not very specific, is it? You might end up with an espresso shot when what you really wanted was a venti, half-caf, sugar-free vanilla latte with almond milk and extra foam. Prompt engineering is about being that specific with AI tools, so you get exactly what you need.


The Four Pillars of Prompt Engineering: Your New Best Friends

Now that we’ve got the basics down, let’s talk about the four pillars of prompt engineering. Think of these as your guiding lights when you’re crafting prompts for AI:

  1. Be specific: Don’t be shy! Tell the AI exactly what you want. The more details, the better.
  2. Be clear: Use language that’s easy for both humans and AI to understand. No need for flowery prose here!
  3. Provide context: Give the AI some background. It’s smart, but it can’t read your mind (yet).
  4. Provide balance: Find the sweet spot between being too vague and too restrictive.

These pillars are your secret sauce for getting the most out of AI tools. Master them, and you’ll be prompt engineering like a pro in no time!


ADDIE and AI: A Perfect Couple

Now, I know what you’re thinking, “This all sounds great, but how does it fit into my actual work?” Well, let me introduce you to the dynamic duo of ADDIE and AI.

The ADDIE (Analysis, Design, Development, Implementation, Evaluation) model is one of the most widely used frameworks in L&D. AI can be your sidekick in each one of the phases, and it particularly shines in the first three:

  •   Analysis. Use AI to help analyze learning needs, gather data, and identify knowledge gaps. With the right prompts, you can get insightful summaries of existing content or generate ideas for needs assessment surveys.
  •   Design. This is where the magic really happens. Use AI to brainstorm learning objectives, outline content structure, generate creative ideas for learning activities, craft assessments or even draft scenarios for role-playing exercises. 
  •   Development. AI can be your tireless assistant in tasks such as creating video scripts or even editing or creating images (this is a fast-evolving area, and a lot can be done even today with the right tools).

The key to making this work? You guessed it, prompt engineering. By crafting clear, specific prompts, you can guide the AI to produce exactly the kind of content you need. 


Real-World Magic: How L&D Pros are Using Prompt Engineering

Now, I know you love a good case study (who doesn’t?), so let’s look at some real-world examples of how L&D professionals are using prompt engineering to work smarter, not harder.

  •   Content summarization: Alison, an instructional designer, used prompt engineering to summarize a 50-page technical manual into a concise 2-page overview for a quick reference guide. Her prompt included specific instructions about the desired length, key points to include, and the target audience’s knowledge level. This is the prompt she used:

“Summarize the key points of the attached 50-page technical manual on network security protocols into a 2-page quick reference guide. Focus on the most critical information that IT professionals with intermediate knowledge would need for day-to-day operations. Use bullet points for easy readability and include any essential technical terms with brief explanations. Ensure the summary covers the main security protocols, their applications, and best practices for implementation.”

  •   Learning objectives creation: Aamir, a curriculum developer, used AI to generate a list of learning objectives for a new leadership course. His carefully crafted prompt specified the course topic, desired Bloom’s Taxonomy levels and the need for measurable outcomes. Take a look at his prompt:

“Create 5 learning objectives for a 2-day introductory leadership course for new managers. Use Bloom’s Taxonomy levels of Apply, Analyze, and Evaluate. Each objective should be specific, measurable, and focused on key leadership skills such as communication, decision-making, team motivation, and conflict resolution. Format the objectives using the ABCD method (Audience, Behavior, Condition, Degree) and ensure they are appropriate for a corporate setting.”

  •   Scenario generation: Zainab, an e-learning designer and developer, used prompt engineering to create realistic customer service scenarios for a retail training program. Her prompt included details about the types of customers, common issues, and the specific skills the scenarios should test. This was her prompt:

“Generate 3 realistic customer service scenarios for a retail clothing store e-learning program. Each scenario should feature a different customer type (e.g., angry customer, indecisive customer, customer with a complex request) and a common issue (e.g., return without receipt, size exchange, product defect). Incorporate opportunities for the learner to demonstrate skills in active listening, problem-solving, and de-escalation. Make the scenarios challenging but solvable and include relevant details about the store’s policies without explicitly stating them. Each scenario should be 100-150 words long.”

  •   Assessment design: Arman, a learning experience designer, used AI to draft multiple-choice questions for a compliance course. His prompt specified the topic, the number of questions needed, and instructions to include both correct answers and plausible distractors. Here is what he used as a prompt:

“Create 10 multiple-choice questions for a data privacy compliance course, aligned with the following learning objectives: 1) Identify key principles of GDPR, 2) Explain data subject rights under current privacy regulations, 3) Describe the proper procedures for data breach notification, 4) Apply best practices for data protection in a corporate setting. Ensure that the questions are distributed evenly across these learning objectives. Each question should have one correct answer and three plausible distractors. The questions should assess different levels of cognitive skills (knowledge, comprehension, application) and be relevant to a corporate environment. For each question, indicate which learning objective it addresses. Include a brief explanation for the correct answer after each question. Format the output as follows:

Q1: [Question]

Learning Objective: [Number of the related learning objective]

  1. A) [Option]
  2. B) [Option]
  3. C) [Option]
  4. D) [Option]

Correct Answer: [Letter]

Explanation: [Brief explanation]

Ensure that the distractors are plausible but clearly incorrect to someone who has mastered the learning objective. Use realistic scenarios or examples where appropriate to test the application of knowledge.”

These examples show just a glimpse of what’s possible when you combine L&D expertise with the power of AI and skillful prompt engineering.


Ethical Considerations: Keeping it Real and Responsible

Now, before we get carried away with all this AI excitement, let’s take a moment to talk about ethics. As L&D professionals, we have a responsibility to use AI tools in a way that’s ethical, fair, and beneficial to our learners.

Here are some key ethical considerations to keep in mind:

  1. Bias check: AI can inadvertently perpetuate biases present in its training data. Therefore, always review AI-generated content for potential biases and make necessary adjustments in your prompts to avoid those results. This is an essential aspect when crafting your prompts. In the first example, Alison carefully reviewed the 2-page overview AI created to balance the pronouns used. Since the source document used masculine pronouns, AI used the same in its summary. Alison brought human awareness to this and fixed the bias.
  2. Privacy first: Be mindful of data privacy when using AI tools. Avoid inputting sensitive or confidential information, and always check the privacy settings of the AI platforms you’re using. Define specific measures and guidelines for you and your team about how to properly and securely use all AI systems. Before Aamir used Copilot (with company-level privacy measures built-in) to generate learning objectives for his course, he double-checked using the tool with the client regardless.
  3. Human touch: While AI can be a fantastic assistant, it shouldn’t replace human creativity and expertise. Use AI-generated content as a starting point, then add your unique insights and personal touch. Remember that you are the brain behind the tool. Zainab tweaked her scenarios with the additional context she gathered from discovery interviews with the subject matter experts, so the scenarios now truly represent the learner’s world and its challenges.
  4. Fact-checking: AI can sometimes generate inaccurate information (a phenomenon called “hallucinations”). As such, always verify the accuracy of AI-generated content, especially for critical information. Arman found that some questions AI generated had incorrect information about GDPR. He conducted a quick fact-check and his content was validated as good to go! 
  5. Transparency: If you’re using AI-generated content in your learning materials, consider being transparent about it. This can help build trust with your learners and stakeholders. As we mentioned before, we always confirm with our clients when using AI to support the design processes. When building AI-enabled activities that learners interact with, we also suggest adding disclaimers that inform learners that they are interacting with an AI as it serves to build trust and add value to each experience.

By keeping these ethical considerations in mind, we can harness the power of AI while maintaining the integrity and high quality of our learning solutions.


Embracing AI Prompting

At this point, you might be feeling a mixture of excitement and perhaps a bit of apprehension. But remember, as with every other skill, the key is to start small, experiment, and keep learning.

Here are some steps you can take to begin your prompt engineering journey:

  1. Start experimenting: Pick an AI tool (ChatGPT, Claude, or Copilot are great starting points) and begin playing around with prompts. Try using it for a small task in your next project.
  2. Practice the four pillars: With each prompt you craft, consciously apply the four pillars of prompt engineering. Be specific, clear, provide context, and find the right balance.
  3. Join the community: Connect with other L&D professionals who are exploring AI and prompt engineering. Share experiences, learn from each other, and stay updated on the latest trends.
  4. Keep learning: The field of AI is evolving rapidly. Make it a habit to stay informed about new developments and best practices in prompt engineering.
  5. Reflect and iterate: After each AI interaction, reflect on what worked well and what could be improved. Prompt engineering is as much an art as it is a science so you’ll get better with practice!

Remember that prompt engineering isn’t about replacing your skills as an L&D professional. It’s about augmenting your capabilities, freeing up your time for more creative and strategic work, and ultimately creating better learning experiences for your audience.

With the rapid growth of AI tools, the future for L&D looks promising and requires us to keep up with this evolution and its challenges to make the most of it. So, are you ready to sharpen your prompt engineering skills? Who knows, your next brilliant instructional design idea might just be one well-crafted prompt away!

If you’re hungry for more information on how to leverage AI and prompt engineering in your L&D work, connect with us at Artha Learning Inc. We’re here to help you navigate this brave new world and make the most of AI tools in your learning design journey.

This article was written by Gilda Martinez, Senior Instructional Designer at Artha Learning Inc.

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