Managed Simulations

I have been researching management of simulations and other complex entity based learning implements such as serious games. The challenge here is that the traditional SCORM/AICC paradigm allows limited reporting capabilities. Another challenge is storing state for later resumption (bookmarks) and the third challenge is to be able to set simulation parameters. Another related challenge is to “pool” the simulation experience for a multi-user synchronous or asynchronous simulation/game experience. Yet another challenge is to capture/record simulation experiences for later analysis, grading and feedback.

Clearly, this is an important area of focus. ADL, the keepers of SCORM, have developed an architecture called the High Level Architecture (HLA). Their research:

focuses on developing instructional paradigms, training-specific data structures and communication methods between a simulation, Shareable Content Object Reference Model (SCORM)-based instructional content, and a Learning Management System (LMS), to facilitate using simulation as an environment where an individual or a team can practice a skill (instruction) or demonstrate their level of performing the skill (performance assessment).

Of particular interest is the intersection between S1000D and SCORM. S1000D provides a mechanism to define complex systems having multiple inter-related components, and to define various allied information items thereof (like defining a plane or a ship or even a bicycle).

But of particular interest is the advancement of simulations for learning through research on adaptive simulations, social simulations (utilizing the power of the network – maybe to run alternate reality games) and other ways to raise the bar on what simulations can actually achieve. Let me know your thoughts!

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Learning Styles and Learning

When I was building up the story for LearnOS, in my mind I had a mathematical model for how a complex of factors, assessed through various instruments (psychometric, inventories, observable analytics), could result in heuristics not only for content presentation, but also for collaboration, tools usage and learning process design. A Learning Weights Matrix mapped elements of the learning experience to learner, learning, media and organization indicators to arrive at an indication of design or experience. I tried this with research aimed at evaluating two courses offered by the British Council in New Delhi and got some interesting results.

However, my thinking has changed past that phase, based on a few key considerations.

This is not a machine. There isn’t a definitive set of factors I could use, there is probably not a definitive way of measuring and categorizing profiles and perhaps not a definitive way of mapping enumerated elements of the learning experience to profile information. I am not saying it may not be accurate, or adaptively so, useful, but that it is misdirected. It depends on thinking of students and teachers as finitely defined entities on a production line, programmable and predictable in the face of input.

We are trying to extrapolate from small instances to large scale systems using technology. That is not correct. eLearning as such does not scale well. The quality breaks with scale of any sort. Scale must leverage scale – have a large number of small learning clusters/networks rather than a small number of very large paradigms.

Research, especially around Connectionism (and more specifically Connectivism) indicates that we would be better off looking at focusing on capabilities/literacies rather than on learning styles, on networked behavior rather than individual unrelated atomic conceptions.  Competency frameworks, career progression, and talent management as a whole, need to be re-evaluated in this context

How this emergent ecology will result in competencies bookmarked to real life skills is not altogether unknown. But it still requires structure and method that practitioners, who are currently trying to fit these new ideas inside dominant frames of reference (inside the box), can leverage. It has the promise to scale, much beyond the confines of current eLearning.

These thoughts pretty much redefine the state of art from when I wrote the initial draft for LearnOS and bear on me to remember that technology cannot play God, as someone in a recent conversation, tried to impress upon me.

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