Sequencing eLearning for better outcomes is a crucial task for all instructional designers. After considering all learner discovery analysis an ID must choose the correct sequencing paths to get the learner to the desired goal. In this article, we will go over three sequencing paths for learning.
1. Traditional Directive Linear
Linear directive-based training is great for including gamification into training for learners who need to learn a task with limited options to choose that have close-ended results for a task with one action. These typically follow a “rule-example-practice-feedback” (Clark, 2013)model. In the past, traditional directive learning has worked great for introducing learners to a new subject and then providing an exercise to practice what they recently learned and provide immediate feedback for their choices.
2. Linear Scenario-Based
Linear Scenario-Based learning works for more complex learning. It gives learners a chance to make decisions, get feedback, then continue on a learning path towards additional situations. This style represents real-world situations closer. The linear scenario-based method works better for learners that already have experience. It allows the learner to be more engaged and active in problem solving and providing feedback and consequences for the choices they make.
3. Problem Solving Branching Scenarios
These are the most complex of scenarios to create. Each decision leads a learner into another unique path. That means the learners can have individual paths that are made because of their decisions. This style gives the realest-world situation the learner will be exposed to. This is the most complex option for scenarios and is the most difficult and time costly to build.
References:
Clark, R. (2013). Scenario-Based e-Learning. John Wiley & Sons
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