- In diffuse differentiation all employees receive the same online training content, but have multiple opportunities for training, as they are provided with different sources of stimulation. It is probably the most common approach to differentiated online training, as the use of technology makes the integration of GSBM media and the distribution of online training content very simple.
- Self-directed approach to differentiation.
In the self-directed approach employees receive different online training content, and they are allowed to make their personal choices in working their way through the online content. Examples of self-directed approach is offering either a fixed menu of online training activities and modules from which the employees select the order of completion, or links for online training opportunities and additional information, which employees can choose whether they want to use or not. Self-directed differentiation is also a common approach to differentiated online training.
- Naïve differentiation.
Here, portions of online training content change in a more random way, through a shuffle function for instance, without requiring the participation of employee. An example of naïve differentiation is randomizing the rotation of online training content displays, images and graphics each time viewed. Randomized content view is useful, mainly for revision purposes.
- Boolean differentiation.
In Boolean differentiation, software uses types of Boolean logic to determine how to adjust online training content for different employees. This type of differentiation is more focused on developing problem solving and critical thinking skills. A series of rules determines whether a statement is true or false, and decides if the employee in question is ready for the next step. It is one of the strategies most frequently employed for content adaptation to the particular needs of the learners in adaptive eLearning; depending on the choices learners make, they are presented with a next eLearning activity adjusted to their current state of knowledge.
- Model-based differentiation.
Model-based differentiation combines a variety of approaches for generating ideas that will help the subject matter expert to decide they best way that online training content can be differentiated.
July 2, 2020