Multiple-choice questions in courses don’t typically give learners the kind of realistic practice that leads to them discovering possible solutions on their own. An alternative to multiple-choice questions is scenario-based questions, which can be almost as potent as simulations, yet are much less time consuming and less costly to develop. Unfortunately, most scenario writers do not fully reinforce the cognitive pathways learners will need to retrieve the learned information from memory.
By using the research-inspired SEDA (situation, evaluation, decision, action) model, scenario writers can avoid the two biggest shortfalls in scenario-based questions: the closing of the problem space and the lack of processing devoted to examining the answer choices. You will learn how questions using the model prompt learners to look beyond a limited number of answer choices and to think of the situation more like a real-world situation. Participants will also look at how to increase the amount of attentional capacity learners devote to analyzing the answer choices, thus increasing learning outcomes.
In this session, you will learn:
- How you can use the SEDA model to diagnose poor training and simulation design
- The three learning methods that are most effective in minimizing forgetting and supporting long-term remembering
- How to create branching questions that open up the problem space, and hence improve learning results
- How to create branching questions that learners process more fully, and hence improve learning results
Audience:Intermediate and advanced developers and designers who will see how they can use the SEDA model to create more potent scenario-based questions, and senior management, who will learn how the SEDA model can help guide training and eLearning design.
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