Harnessing the power of data in design to optimize learning outcomes

“I know the answer!” is not something we want to hear from learners at the outset of an immersive learning experience. We know we’ve created a transformative experience when we see teams of learners discussing, debating, and teasing out the best possible path through a simulation. Our team-based, immersive learning experiences have three primary features that maximize engagement, application, retention, and measurable behavior change:

  1. Place learning in context
  2. Invite learners to navigate ambiguity by playing in the gray
  3. Create opportunities to fail forward in a safe and fun environment

Getting it right is both an art and a science. Tim Burkowske recently wrote an excellent article exploring the role of art in learning, so I’ll focus on the science behind good learning design—specifically, how we use data to optimize answer choices in scenario simulations

What do answer choices have to do with optimizing learning outcomes?

Effective learning experiences require attention to every last detail—especially the options presented at decision points in the scenario simulation. Well-written answer choices have the power to achieve the following:

  • Improve critical thinking and decision-making skills: By presenting realistic and thought-provoking options, scenario simulations encourage learners to evaluate the consequences of their choices, consider different perspectives, explore best practices, and develop effective decision-making skills that can be applied in real-life situations.
  • Identification of failure points: Failing forward helps learners understand the consequences of poor decision-making and encourages them to reflect on their choices, consider alternative paths, and learn from mistakes in a safe and controlled environment.
  • Engagement and motivation: Answer choices that are well-balanced, challenging, and aligned with learners’ skill levels create a sense of engagement and motivation. When learners are presented with options that require careful consideration and critical thinking, they are more likely to feel invested in the learning experience. Engaging simulations are captivating, making the training more enjoyable, memorable, and ultimately more effective.
  • In-context learning and application: By carefully crafting options that reflect on-the-job challenges, simulations create a bridge between theoretical knowledge and practical application. The connection enhances learners’ ability to transfer their skills and knowledge to real-life situations, improving their overall application and performance.

In a scenario simulation, decision points are the catalyst for learning; the answer choices presented have the power to make or break the entire experience. Why? There are a couple of reasons.

First, for many populations of learners, the bar for learning experiences is low. People are accustomed to jamming the Next button to get to the end of dry compliance training (for a laugh, check out @albita8687’s TikTok video) or being forced to sit through a talking-head presentation by someone who has no idea what actually happens during a real workday. These types of experiences are known for including ridiculously straightforward answer choices that purport to be knowledge checks—is the sky blue, purple, or sparkly? Should frustrated employee Jack unload his rage in a verbal tirade or speak to his HR rep about the situation?

Good learning design is a pop of color in an otherwise bland sea of training modules. We’ve seen firsthand how provocative answer choices within scenario simulations enhance learning outcomes. Choosing the best path forward provides a safe way for learners to practice responding to real-life challenges—those challenges rarely offer straightforward solutions, which means that an authentic simulation must be equally inscrutable. Most importantly of all, engaged learners who have the opportunity to fail forward and synthesize new ideas in context walk away from a learning experience equipped to drive real change in the organization. In order to achieve that level of engagement, the interactive components must seize the learner’s attention by provoking critical thought.

How we use data to optimize answer choices in scenario simulations

A scenario simulation strikes a delicate balance between difficulty and engagement: choices must be challenging enough to provoke critical thinking and decision-making, while also being realistic and aligned with the learning objectives. We use data-driven insights and pilot programs to ensure that the choices presented to learners invite critical thinking, exploration of best practices, and recognition of potential failure points. 

Pilots and iterative design

During the pilot phase, we examine the data collected from participants to refine and improve the answer choices within our scenario simulations. By analyzing the distribution of choices made by participants, designers can identify any biases or inconsistencies and make necessary modifications to enhance the learning experience. This iterative process allows the team to make adjustments based on user feedback and ensures that the simulations are both engaging and effective.

In some cases, when the material is extremely complex, we may even recommend a second pilot to increase the accuracy of our analysis and recommendations. Examining data from different pilot groups allows us to identify any variations in the distribution of choices and determine whether these variances are significant or due to random chance. This multi-pilot approach enhances the reliability of the data analysis and can lead to even more robust and refined answer choices.

Using psychometrics to reflect on best practices and failure points

Our commitment to data-driven optimization doesn’t stop at the pilot phase. The use of psychometrics adds another layer of insight to the process of optimizing answer choices. Our designers reflect on previous examples to understand what led to a well-balanced distribution of choices and what did not. When clients give us permission to analyze ongoing data about user interactions and choices it makes it possible for our team to identify learner behavior and decision-making patterns and assess whether the answer choices align with the intended learning objectives. Ongoing analysis enables us to identify areas for improvement, adapt to changing learner needs, and refine our approach over time. 

Optimized design = optimal outcomes and return on learning investment 

The goal of any learning initiative is to change behavior to drive business transformation (and deliver a good return on learning investment in the process). Scenario simulations provide a contextualized, collaborative, and thought-provoking learning experience; one that offers opportunities to explore best practices and failure points to enhance critical thinking, decision-making skills, and engagement among learners. The data we capture and analyze throughout our align, design, and deliver process ensures that our scenario simulations remain relevant and effective at driving meaningful learning outcomes. Get in touch with our team when it’s time for a change in your organization.

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