Dyanmic Variables: The Basics
For an overview of Variables, click here.
Deep Learning on Variables is found in Motive Academy. Click here to see the course this lesson is in.
Dynamic Variables change based on Conditions set dynamically throughout the Scenario. These Conditions may be triggered based on an action the learner has taken or on the current state of another object in the environment.
The Dynamic Variable editing screen can be found by clicking on the atom icon in the top right corner of the editor.
In the Dynamic Editor, you can create branches and nodes that dictate the conditions under which specific Variable values will be set. When the Scenario reaches a Frame with a dynamic tree, the system will run through the branches and nodes in the tree and change the Variables in the Frame based on true Conditions at run time.
When the processor hits a Frame that has a Dynamic Variable tree in it, it processes the tree as follows:
All nodes (represented by black bars) are processed. You would use two nodes in one tree if you have two different things you want to check for in one Frame. For example, in this Frame, I will use the first node to determine if the Scenario is in teach mode or not to decide if I want to show object prompts, and in the next node, I am going to check which Scenario step I am on to decide which completion Event to fire.
The branches beneath a node are run through until the processor finds a Condition that is true. It will stop there and set the Variable. If nested branches are below the parent branch that are true, it will also run through those to set any further Variables. It will not check additional branches below the first one it finds that fulfills the criteria set:
Branches in the Dynamic Editor are processed in three different ways:
In Order: By default, the branches are processed in order. The Condition on each branch is evaluated, and the first branch with a true Condition dictates the value of the Variables set in that branch. You can change the order of branches and nodes by dragging them.
Priority: The branches are checked in order of priority; this allows preferred outcomes to have the highest likelihood of getting chosen.
Weight: The branch processed is chosen based on the probability you assign in the “weight” field. You can use the “weight” method of selecting nodes to randomize Scenario outcomes.
To learn more about Dynamic Variables, please complete the Author Certification course in Motive Academy.
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