This presentation describes prerequisites to produce an Engine for virtual learning which main objectives is create new learning approach according to Predictable and Unpredictable Events. What tools will learners use? What standards will apply? What new learning approaches may result as a function of the proposed engine?
These are the scope of our proposal.
To understand the wide scope where the proposed engine applies we describe three scenarios:
1. Virtual Tutor where Simulation is used to trigger iterative interactions and create required environment for virtual learning. 2. Scenario for Robot handling where number and types of semantic rules are defined according to cumulated knowledge acquired by performing more serious games. 3. Scenario to predict how the particle is produced and how it decays within the Standard Model[1]. The proposed scenario is composed of a set of predefined messages exchanged between LHC and control stations which pilot its mission in measurement of Proton-proton collisions according to predictable events like how the particle is made in the LHC and how it disintegrates into other, more familiar particles as soon as it is created.
We propose a new standard to produce a universal engine: SPDF (Standard Process Description Format) which consists of two parts: a. message structured-data part (including semantics) and,
b. process description part (with higher level of semantics).
URL address of the full text and previous contributions:
http://www.mlfcham.com/index.php?option=com_content&view=category&id=334&Itemid=1447
