ELEMENT #4: SCALED-WORLD SIMULATION
Simulation represents another venue where much integration of data-information- knowledge can be reified, tested, and validated. Scaled worlds are simulations that take primary problems that exist within an environment and bring them more into a lab setting where control and focus can be implemented. The scaled world, in turn, represents an important element of an integrated LLF as it brings dynamics from the real world within the confines of a simulation where in-depth understanding and convergence of concepts can be adapted, adjusted, and refined even more so. A scaled world is much more than a simple lab test as employed in many psychological experiments. The context experienced by user(s) should be present to a threshold level of fidelity in the scaled world. It may not have the full sense surround intact but it should simulate a good portion of it to reflect actual practice. Therein, researchers will need to strategically look across the entire spectrum of how supply chains contribute to natural gas exploitation and exploration, and determine where use is (1) most important for the success in performance, safety and well being, and priority outcomes; (2) is troubled with an array of problems that create bottlenecks, errors, lack of situation awareness, overload, and other issues that demand human-systems integration; and (3) studied in a way to represent a variety of human factors present within the actual environment. Once target areas for simulation are established then the technological infrastructure, control-display surfaces, the data set/database utilized, and software architectures to implement the scaled world can be designed and created.
One way to think about scaled worlds is how they come into existence. This is where the kinetic cycling through different LLF elements results in productive outputs of knowledge. Practice should be evident as individuals and teams perform in the natural; gas supply chain scaled world. As we have seen—practice and use are collected from observations with ethnographic inquiry and knowledge elicitation.
So first and foremost—the scaled world emerges out of the findings obtained from these user-centered elements. Obviously, what novices and experts reveal about problems can come to reality in the scaled world and be presented, attuned, and adapted as needed. It is instructive to think of a scaled world as being able to produce the most difficult problems, situations, constraints, and issues within a controllable simulation to provide in-depth study of it under various conditions (e.g., the use of independent-control-dependent variables).
Second, scaled-world simulations typical commence via scenarios that represent sequences of decisions and actions that are possible when specific events and/or complex situations arise from one state to another. Decisions and actions are coupled to specific problem situations that emerge in time as the simulation plays out in depth and fullness. As the LLF is necessarily problem-centered, one could think of scaled-world simulation as providing ecologically valid situations that contain problem states and a potential number of solution states that come into place with correct elements of decision-action sequences. Simulations may also contain informationseeking elements where participants look-up information to further their awareness and action. In combination with the information architecture underlying the simulation, scenarios offer up the production of built-in affordances that are coupled with effectivities provided by both human team members and the requisite technology that is operable under any given condition. Affordances, decisions, and action are specified by information, which is requisite either within the interface provided or resident within data files that are activated from the information architecture under certain facile conditions. As there are many potential problems—issues that face natural gas exploitation and supply chains—the prioritization of the highest payoffs will need to be ascertained before a significant investment in simulation design is manifest. This creates prioritized plans for simulation that correspond to the challenges, and opportunities to move forward that have been accruing through each of the LLF elements. This last facet points to the last element of the LLF, the technology prototypes that we will get too shortly.
Third, scaled worlds become the vehicles on which specific theoretical hypotheses are tested. This is referred to usually as human-in-the-loop testing, and provides a robust engagement and enriched experience for participants as the simulation, scenarios, and conditions applied are living in that they are highly emulative of real- world problems-issues. Hence, the testable conditions under which a hypothesis is assessed and evaluated are deemed to have a higher ecological validity owing to the feed-forward of other LLF knowledge that has been collected/validated. Another aspect of validity is that novices and experts can be put in the simulator and corrections made accordingly. This improves the overall veridicality and realistic aspects of the experience. Also, placing novices or experts in the simulation and having them perform cognitive walkthroughs (Dix, Finlay, Abowd, & Beale, 2004) is an excellent extended form of knowledge elicitation that pays dividends.