Scenario-Based Learning Acronyms: From MCQ to AI

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Image depicting various learning tools and technologies for scenario-based learning.

Scenarios-based learning comprises several conceptual dimensions: whether they’re simulation-driven, branching, or even just better-written multiple-choice questions (MCQ). Another factor is how they’re implemented. This is particularly true for interactive scenarios. There are important variations in the tools and the associated design choices that accompany those approaches. Knowing them increases the likelihood that a particular approach is appropriately implemented and therefore justified.

Standard Authoring Tools

The first thing to know is that mini-scenarios are just better-written MCQs. Thus, you can use your regular authoring tools (which all have MCQ abilities), with the caveat that they must support different responses for all choices. You can use media, such as images, comics, or even video to support your contextualization, as well as audio and/or text. There are, of course, the usual challenges associated with each, for instance with video the details required in scripting and filming, as well as the costs for revising, can be a barrier.

Moreover, most authoring tools also make it easy to develop branching scenarios. They may need support in terms of keeping track of the branches, but they will provide support. This is good news because branching scenarios are a great solution to create contextualized learning. They similarly can use the various media, though developing branching video can get problematic.

In both cases, then, you don’t have to invest in new software to get effective learning experiences. You may have to invest to find out how to develop these structures in the tool, but they are doable. Some even have the ability to carry variables forward, so you can do sophisticated examples.

Branching Media

Beyond general-purpose tools, there are tools dedicated to creating branching experiences. This holds true across media. Industrial strength tools make sense when you anticipate creating scenarios at scale.

Video is a powerful medium for creating context, and thus is a potent tool for creating scenarios. While the issues above in cost are true, there are dedicated tools to make it easier. There are tools for all types of branching scenarios and ones dedicated to video.

Of course, you can use more powerful general-purpose tools, with tradeoffs. For instance, you can use game engines to build branching scenarios, as these can handle rendering visuals quite powerfully. While AR and VR tools are still largely in the ‘build for this platform only’ stage, if you do know and can dictate one platform, they will work for branching scenarios.


As long as you’re using such powerful tools, you can think further, and start thinking of going beyond branching, and actually creating the underlying simulation that can drive experience. There are tradeoffs to this that are worth considering.

The major concern is the effort to develop, and tune, a simulation model, even before designing a learning scenario for it. Choosing the variables, and programming the transitions is hard enough, tuning the variables to give a plausible experience is additional work. While we don’t need to tune to the level of “pay $80 for this”, we do need to create appropriate timings and probabilities.

On the plus side, such an investment gives a lot of benefit. For one, you can provide enough randomness to support almost infinite replay. You can also provide an adjustable difficulty to support the development of a high level of ability. Simulation games, whether rendered on-screen or in an immersive environment, are powerful learning tools.

Coming Soon to a Theater Near You

One area that briefly surfaced, for a while, and should be a really effective learning tool, are Alternate Reality Games (ARGs). Here, your tasks are situated in the real world, using your existing email, phone, etc. It’s just that the design and the reactions are all handled by a script, not the real world. Imagine, for instance, practicing a sales process with virtual clients but they call you and send you email, and respond to yours! The benefits are using the tools you’ll actually use to perform. ARGs have kind of fallen away for now, but the potential remains there as a training tool.

Then, it’s interesting to explore what might be next. There have been efforts to try to get artificial intelligence (AI) agents to create games, but to date, they’ve lagged. In general, it’s hard to get AI to understand emotion, so creating and tuning experiences could be difficult. That said, an AI might be a good thinking partner, providing ideas for settings and random events, as long as the results are supervised.

While AI-generated scenarios are likely in the distant future, the tools are here now to allow us to create powerful experiences. It’s up to us to design them, but, on the whole, that’s probably a good choice.

In conclusion, scenario-based learning is a versatile and dynamic approach to education, offering a spectrum of possibilities from well-structured multiple-choice questions to immersive simulations. As technology continues to advance, the toolkit for implementing these scenarios also grows, enabling us to create engaging and effective learning experiences. To delve deeper into the world of scenario-based learning and harness its full potential, we invite you to read our eBook, “Scenario-Based Learning: The Ultimate Asset In Your L&D Toolkit.” Don’t miss out on the opportunity to unlock the power of scenario-based learning. Get your copy today!

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