Educating Citizens versus Sheep, Part 6: Scenario-Based Learning

“Scenario-based learning (SBL) is an immersive training environment where learners meet realistic work challenges and get realistic feedback as they progress, since everything that happens reflects the learner’s choices.

Unlike many e-courses, where learners passively absorb information by reading a text and taking a test afterward, in scenario-based training, they actively participate in the process from the very beginning to the end of the lesson.” Helga Kolinski and James Gilchrest

Kolinski’s and Gilchrest’s comment in the opening quote is spot on. However, it fails to include the integrated nature of SBL and serious games. SBL without a serious game driving it is not effective. Serious games without scenarios are like a car without a driver.

The SBL is not a game engine. Organizations can employ SBL without a single computer. A case study, for example, can be a form of SBL, depending on its structure. Serious games significantly extend SBL’s capabilities, especially if married to a Learning Enablement System (LES) and data management/analytics capability.

A sound LES helps assess student capabilities, progress, and game effectiveness. A LES more than a traditional Learning Management System (LMS). The lES helps the student to interact with the learning system and games. It can determine the student’s capabilities and capacity to understand new information and to generate knowledge.

The LES should track and assess student cognitive capabilities and to tweak scenarios by ramping up exogenous cognitive loads that make it more challenging for students to sort through distractions to get to the key information and events in the scenario. This is different than the branches shown in the figure above. The core scenario is the same, it just more difficult and can lead to different branches. It also allows students to play the same scenario multiple times and see different outcomes depending on complexity.

The other thing both serious games and SBL need is a data management/analytics capability. Most game engines will have data management capabilities. However, we want the data management capabilities to have analytical capabilities, to interact with the SBL and a LES to manage the scenarios and the triggers for branches and to track student and team performance. Ideally, there is a single data management/analytics for a school or even a district to provide a student passport that tracks the student through graduation.

If the scenarios are well-designed, they can also help students uncover their cognitive biases and develop skills to understand and manage them. Branches can help them to see the impacts of these biases.

The central wheel in the figure above provides the key components of SBL

• Select Learning Objectives and Interfaces. Ideally, designers develop and maintain learning objectives separately so that educators and game designers can use them in multiple scenarios. The interface between learning objectives and the scenario should specify the learning interfaces the scenario will use.
• Develop Events & Actions. Marsh (2010, p.219) provides key concepts into how objectives should drive a story and its events. The actions and events provide the means to engage the learning objectives and interfaces and to evaluate them. The execution creates data that then flows into data analytics.
• Build a narrative. The narrative is a storyline with characters, challenges, and problems. Players engage the characters and negotiate the challenges and problems that are based on the events and actions. The narrative needs to be informative and engaging to encourage learning. Designers should tailor it to the cognitive capabilities and capacity of the learning audience. Scenarios with low cognitively developed learners should be straightforward, with little or no exogenous cognitive load and lower lever cognitive learning objectives. As the learning audience’s cognitive development increases, the scenarios may have larger exogenous cognitive loads to help make the challenges and problems more difficult. Learning objectives may also increase up the cognitive chain.
• Develop Branches. Branches allow the learner to move to different learning objectives within a game. They are like an exist ramp on a highway, activated by the trigger shown in the figure above. Data analytics should establish trigger points for a branch activation. In a digital component, the workflow could tell the game engine to start the branch and the associated information and actions. In an analog component, the workflow could alert the teacher and/or mentors to start the branch and provide players with new information required to them to explore the branch.
• Execute & Conduct Data Analytics. Serrano-Laguna et al. (2016, p5) provide a structure for event and action data to flow into data analytics. Designers must instrument the events and actions to capture the data needed for assessment. The assessments help to determine scenario branches to engage and evaluate performance and progress. If the game moves into AI/ML capabilities, data analytics will become more important, and the analytical sophistication will need to grow.

Follow on posts will go into additional details.

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