Assessing learning session retention utilizing a multi-disciplined learning tool
A method for improving learning comprehension regarding a lesson includes modifying a fundamental illustrative model to illustrate a first set of learning assets of a first learning object using an illustration approach to produce a first learning illustrative model. The lesson includes learning objects which includes the first learning object. The fundamental illustrative model is based on illustrative assets of the lesson. The method further includes obtaining a first comprehension evaluation for the first learning illustrative model and modifying the illustration approach based on the first comprehension evaluation for the first learning illustrative model to produce an updated illustration approach. The method further includes modifying the fundamental illustrative model to illustrate a second set of learning assets of a second learning object using the updated illustration approach to produce a second learning illustrative model.
1. A computer-implemented method of using a computing system, the method comprises:
detecting, by a computing entity of the computing system, an illustrative asset that is common to a first set of assets and a second sets of assets, wherein the first set of assets represents a first learning object that includes a first set of bullet-points for a first piece of information regarding a topic, wherein the second set of assets represents a second learning object that includes a second set of bullet-points for a second piece of information regarding the topic;
rendering, by the computing entity, a three-dimensional (3-D) model of the illustrative asset and a three-dimensional (3-D) model of the first set of assets in accordance with an illustration approach and with regards to the first set of knowledge bullet-points to transform the first set of knowledge bullet-points into 3-D frames of a first descriptive asset using the illustration approach, wherein the first descriptive asset represents the first learning object;
issuing, by the computing entity, the 3-D frames of the first descriptive asset of the first learning object to another computing entity of the computing system in accordance with the illustration approach;
obtaining, by the computing entity, an evaluation of the first descriptive asset associated with the other computing entity;
modifying, by the computing entity, the illustration approach based on the evaluation of the first descriptive asset to produce an updated illustration approach; and
rendering, by the computing entity, the 3-D model of the illustrative asset and a 3-D model of the second set of assets of the second learning object in accordance with the updated illustration approach and with regards to the second set of knowledge bullet-points to transform the second set of knowledge bullet-points into 3-D frames of a second descriptive asset using the updated illustration approach, wherein the second descriptive asset represents the second learning object.
2. The method of claim 1 further comprises:
outputting, by the computing entity, the 3-D frames of the second descriptive asset to the other computing entity.
3. The method of claim 1 , wherein the obtaining the evaluation of the first descriptive asset associated with the other computing entity comprises:
rendering the 3-D model of the illustrative asset and the 3-D model of the first set of assets in accordance with the illustration approach and with regards to the first set of knowledge bullet-points to transform the first set of knowledge bullet-points into the 3-D frames of the first descriptive asset using the illustration approach for subsequent output to the other computing entity, wherein the first set of assets includes a first assessment asset of the first learning object;
obtaining a first assessment response associated with the other computing entity for the 3-D frames of the first descriptive asset; and
generating the evaluation based on the first assessment response and the first assessment asset.
4. The method of claim 1 , wherein the modifying the illustration approach based on the evaluation of the first descriptive asset to produce the updated illustration approach comprises:
when the evaluation indicates that a learner comprehension level is greater than a maximum comprehension threshold, updating the illustration approach to produce the updated illustration approach to include one or more of:
a more challenging viewpoint perspective,
a larger scale of a view,
a larger scope of the view,
a faster speed of delivery,
a higher number of views, and
more highlighting of the view; and
when the evaluation indicates that the learner comprehension level is less than a minimum comprehension threshold, updating the illustration approach to produce the updated illustration approach to include one or more of:
a less challenging viewpoint perspective,
a smaller scale of the view,
a smaller scope of the view,
a slower speed of the delivery,
a lower number of the views, and
less highlighting of the view.
5. A computing device of a computing system comprises:
an interface;
a local memory; and
a processing module operably coupled to the interface and the local memory, wherein the processing module functions to:
detect an illustrative asset that is common to a first set of assets and a second sets of assets, wherein the first set of assets represents a first learning object that includes a first set of bullet-points for a first piece of information regarding a topic, wherein the second set of assets represents a second learning object that includes a second set of bullet-points for a second piece of information regarding the topic;
render a three-dimensional (3-D) model of the illustrative asset and a three-dimensional (3-D) model of the first set of assets in accordance with an illustration approach and with regards to the first set of knowledge bullet-points to transform the first set of knowledge bullet-points into 3-D frames of a first descriptive asset using the illustration approach, wherein the first descriptive asset represents the first learning object;
issue, via the interface, the 3-D frames of the first descriptive asset of the first learning object to another computing entity of the computing system in accordance with the illustration approach;
obtain an evaluation of the first descriptive asset associated with the other computing entity;
modify the illustration approach based on the evaluation of the first descriptive asset to produce an updated illustration approach; and
render the 3-D model of the illustrative asset and a 3-D model of the second set of assets of the second learning object in accordance with the updated illustration approach and with regards to the second set of knowledge bullet-points to transform the second set of knowledge bullet-points into 3-D frames of a second descriptive asset using the updated illustration approach, wherein the second descriptive asset represents the second learning object.
6. The computing device of claim 5 , wherein the processing module further functions to:
output, via the interface, the 3-D frames of the second descriptive asset to the other computing entity.
7. The computing device of claim 5 , wherein the processing module functions to obtain the evaluation of the first descriptive asset associated with the other computing entity by:
rendering the 3-D model of the illustrative asset and the 3-D model of the first set of assets in accordance with the illustration approach and with regards to the first set of knowledge bullet-points to transform the first set of knowledge bullet-points into the 3-D frames of the first descriptive asset using the illustration approach for subsequent output to the other computing entity, wherein the first set of assets includes a first assessment asset of the first learning object;
obtaining a first assessment response associated with the other computing entity for the 3-D frames of the first descriptive asset; and
generating the evaluation based on the first assessment response and the first assessment asset.
8. The computing device of claim 5 , wherein the processing module functions to modify the illustration approach based on the evaluation of the first descriptive asset to produce the updated illustration approach by:
when the evaluation indicates that a learner comprehension level is greater than a maximum comprehension threshold, updating the illustration approach to produce the updated illustration approach to include one or more of:
a more challenging viewpoint perspective,
a larger scale of a view,
a larger scope of the view,
a faster speed of delivery,
a higher number of views, and
more highlighting of the view; and
when the evaluation indicates that the learner comprehension level is less than a minimum comprehension threshold, updating the illustration approach to produce the updated illustration approach to include one or more of:
a less challenging viewpoint perspective,
a smaller scale of the view,
a smaller scope of the view,
a slower speed of the delivery,
a lower number of the views, and
less highlighting of the view.
9. A non-transitory computer readable memory comprises:
a first memory element that stores operational instructions that, when executed by a processing module, causes the processing module to:
detect an illustrative asset that is common to a first set of assets and a second sets of assets, wherein the first set of assets represents a first learning object that includes a first set of bullet-points for a first piece of information regarding a topic, wherein the second set of assets represents a second learning object that includes a second set of bullet-points for a second piece of information regarding the topic;
render a three-dimensional (3-D) model of the illustrative asset and a three-dimensional (3-D) model of the first set of assets in accordance with an illustration approach and with regards to the first set of knowledge bullet-points to transform the first set of knowledge bullet-points into 3-D frames of a first descriptive asset using the illustration approach, wherein the first descriptive asset represents the first learning object;
issue the 3-D frames of the first descriptive asset of the first learning object to a computing entity in accordance with the illustration approach;
a second memory element that stores operational instructions that, when executed by the processing module, causes the processing module to:
obtain an evaluation of the first descriptive asset associated with the other computing entity;
a third memory element that stores operational instructions that, when executed by the processing module, causes the processing module to:
modify the illustration approach based on the evaluation of the first descriptive asset to produce an updated illustration approach; and
a fourth memory element that stores operational instructions that, when executed by the processing module, causes the processing module to:
render the 3-D model of the illustrative asset and a 3-D model of the second set of assets of the second learning object in accordance with the updated illustration approach and with regards to the second set of knowledge bullet-points to transform the second set of knowledge bullet-points into 3-D frames of a second descriptive asset using the updated illustration approach, wherein the second descriptive asset represents the second learning object.
10. The non-transitory computer readable memory of claim 9 further comprises:
a fifth memory element stores operational instructions that, when executed by the processing module, causes the processing module to:
output the 3-D frames of the second descriptive asset to the computing entity.
11. The non-transitory computer readable memory of claim 9 , wherein the processing module functions to execute the operational instructions stored by the second memory element to cause the processing module to obtain the evaluation of the first descriptive asset associated with the other computing entity by:
rendering the 3-D model of the illustrative asset and the 3-D model of the first set of assets in accordance with the illustration approach and with regards to the first set of knowledge bullet-points to transform the first set of knowledge bullet-points into the 3-D frames of the first descriptive asset using the illustration approach for subsequent output to the computing entity, wherein the first set of assets includes a first assessment asset of the first learning object;
obtaining a first assessment response associated with the other computing entity for the 3-D frames of the first descriptive asset; and
generating the evaluation based on the first assessment response and the first assessment asset.
12. The non-transitory computer readable memory of claim 9 , wherein the processing module functions to execute the operational instructions stored by the third memory element to cause the processing module to modify the illustration approach based on the evaluation of the first descriptive asset to produce the updated illustration approach by:
when the evaluation indicates that a learner comprehension level is greater than a maximum comprehension threshold, updating the illustration approach to produce the updated illustration approach to include one or more of:
a more challenging viewpoint perspective,
a larger scale of a view,
a larger scope of the view,
a faster speed of delivery,
a higher number of views, and
more highlighting of the view; and
when the evaluation indicates that the learner comprehension level is less than a minimum comprehension threshold, updating the illustration approach to produce the updated illustration approach to include one or more of:
a less challenging viewpoint perspective,
a smaller scale of the view,
a smaller scope of the view,
a slower speed of the delivery,
a lower number of the views, and
less highlighting of the view.