Welcome to Part Four of our Illuminating Insights blog series, where we explore Richard Mayer’s cognitive theory of multimedia learning and how it applies to eLearning design. In previous posts, we’ve discussed how good eLearning design reduces extraneous processing, manages essential processing, and fosters generative processing.

In today’s post, we’re focusing on how to encourage generative processing—the type of learning that helps learners understand the material deeply and apply it on the job.

What is generative processing?

Let’s say you’re designing a multimedia eLearning course about recognizing phishing email scams. The goal is for learners to identify and report phishing scams at work. To reduce extraneous processing, you’ve made sure to focus on key points and cut out unnecessary details. To manage essential processing, you’ve broken it down into manageable chunks and provided pre-training on important concepts like the definition of “phishing.”

Now, the question is: how can you make sure that learners will be able to apply what they’ve learned? This is where generative processing comes in. Generative processing is the cognitive effort that helps learners make sense of the material. When they can connect new concepts to each other and to what they already know, they develop a deeper understanding, which is more likely to help them apply their knowledge in real situations. Generative processing is key to impactful training.

How do we encourage generative processing?

Generative processing happens when learners are motivated to think deeply about the material. Motivation is often social, and learners tend to work harder when they feel connected to others. In a classroom, learners might feel motivated by their relationship with the instructor or classmates. In eLearning, learners typically participate alone. Still, research shows there are ways to make learners feel more socially connected, even when they’re learning on their own. Let’s discuss four of Mayer’s recommendations.

Strategies for Fostering Generative Processing

Mayer recommends several strategies, including the following:

1. Using a conversational style.
2. Using an appealing, human-like narrator.
3. Using natural movement and human-like gestures for on-screen instructors, characters, and animations.
4. Including activities that encourage deep thinking.

Use a conversational style

To help learners feel more connected to the material, use a friendly, conversational tone. This helps build a sense of “social presence” and creates an “implied conversation” between the learner and the eLearning, which motivates learners to engage more deeply (Mayer, 2020, p. 306). Here’s how to do it:

• Use “you” and “I/we” instead of third-person language. For example: “You can help us by reporting phishing emails” instead of “Employees should report phishing emails to the company.”
• Give warm, personalized feedback. For example: “That’s not quite right. Let’s try again” instead of “Incorrect. Click the button to re-take the quiz.”
• Avoid filler words or confusing expressions, and stick to clear, simple language.

Use a human-like narrator

Mayer’s research shows that using a human-like voice helps learners feel more connected to the instructor, which encourages deeper learning. A warm, professional voice—either a human narrator or a high-quality AI voice—helps learners feel like they’re connecting to a real person. Avoid robotic or overly formal voices, as they can feel impersonal.

Use natural gestures and movement

Incorporating natural gestures and movement can help create a sense of connection even in a solo learning experience. Mayer refers to this as “embodiment,” and it encourages social presence and increases the learner’s motivation. Here are some ways to incorporate embodiment:

• Gestures: If you’re using an instructor or onscreen character, they should use hand movements and body language while explaining concepts.
• Drawing: Use animations that show concepts being drawn on screen (like a whiteboard-style animation). Time the appearance of onscreen items with the narration to give a natural feel.
• Eye Contact: If you’re using an instructor or onscreen character, they should look directly at the camera, as if making eye contact with the learner.
• Perspective: In demonstrations, use a first-person perspective to make the learner feel more involved.

Include activities that encourage deep thinking

Learners retain more when they actively engage with multimedia. Instead of passively watching or reading, encourage learners to summarize, map, self-test, or reflect on the content. Some examples of activities include:

• Summarizing: Have learners explain a concept in their own words. For example, “Explain one danger of phishing scams.”
• Mapping: Let learners organize information into diagrams, like flowcharts or hierarchies. For example, learners might drag and drop the steps for reporting phishing in the correct order.
• Self-testing: Include low-stakes quizzes that help reinforce key concepts. For example, show a sample email and ask learners to identify whether it is a phishing attempt.
• Self-explaining: Encourage learners to reflect on their decisions and explain why they chose a particular answer. For example, ask, “Which part of the email made you suspicious?” and provide tailored feedback.

Conclusion

By applying these strategies, you can help learners process information more deeply, making the training more effective and ensuring they can apply what they’ve learned to real-world situations. Creating eLearning experiences that foster generative processing is key to improving learning outcomes and making your training truly impactful.

Reference

Mayer, R.E. (2020). Multimedia Learning (3rd ed.). Cambridge University Press. https://doi.org/10.1017/9781316941355