Benefits and application of GMIF in learning design
Specifically, this section presents two concrete scenarios where designers can use GMIF to create optimal learning scenarios.
We have developed the GMIF to support each of these steps.
With the GMIF detailed in this paper, we can develop different functions for authoring tools for learning scenarios.
For the instance shown in Figure 9, where the application employs a five-point scale GMIF, if the instructional designer set the initial stage of a student as s(0,0)--nothing for skill and nothing for knowledge--and the goal stage as s(3,0--associative stage for skill development--the proper levels of difficulty that will favor and maintain the learner's flow are first, level 0: very-easy for the transition s(0,0) [right arrow] s(1,0).
Thus, when an instructional designer selects a transition in the graphical representation of the GMIF, the application automatically show a list of adequate learning objects (shown in Figure 9, left-bottom) that can be selected to maintain the learner's flow during the selected transition.
This new model, called GMIF (Learners Growth Model Improved by Flow Theory) was developed by integrating the LGM (Learner S Growth Model) and Flow Theory.