Simulation Approach
An instructional simulation, also called an educational simulation, is a simulation of some type of reality (system or environment) but which also includes instructional elements that help a learner explore, navigate or obtain more information about that system or environment that cannot generally be acquired from mere experimentation. Instructional simulations are typically goal oriented and focus learners on specific facts, concepts, or applications of the system or environment.
“Simulations are used in the training of integrated skills that consist of multiple judgments, decisions, and actions that take place in a fluid sequence in response to changing circumstances. What is learned and practiced with the aid of an instructional simulation is the ability to adapt action to a momentary problem-solving need. Simulations provide practice in carrying out complex tasks and also in selecting which tasks to carry out at a given moment. They can be used to teach learning strategies and to help learners to achieve the capacity for self-directed learning. Instructional simulations do this through augmentation within an environment that includes some degree of scaffolding, coaching, feedback, or on-the-spot instruction tailored to the circumstances and requirements of performance.
Because simulations represent an adaptive and potentially costly form in instruction, three general criteria apply to the design of instructional simulations (Atkinson & Wilson, 1969):
The criterion of adaptivity – The ability to modify qualities of the instructional experience based on the actions of the learner
The criterion of generativity - The ability to generate some portion of the instructional artifact at the time of use
The criterion of scalability - The ability to produce instructional experiences in greater quantity without corresponding linear increases in cost
Simulation Architecture
The design architecture of an instructional simulation can be viewed as a composite of many subdesigns, including: (1) a core that computes model state changes; (2) a strategic system of model-experience augmentations; (3) a user control system; (4) a message-generation system; (5) a system for creating surface representation; (6) a system for executing the simulation; and (7) a system for data management. A common approach to simulation design is to center the solution on a software architecture, but doing this indicates an implicit decision that other parts of the design will be forced to fit the software architecture if there is a conflict,” (Gibbons, Mcconkie, Seo, Wiley).
“Simulations are used in the training of integrated skills that consist of multiple judgments, decisions, and actions that take place in a fluid sequence in response to changing circumstances. What is learned and practiced with the aid of an instructional simulation is the ability to adapt action to a momentary problem-solving need. Simulations provide practice in carrying out complex tasks and also in selecting which tasks to carry out at a given moment. They can be used to teach learning strategies and to help learners to achieve the capacity for self-directed learning. Instructional simulations do this through augmentation within an environment that includes some degree of scaffolding, coaching, feedback, or on-the-spot instruction tailored to the circumstances and requirements of performance.
Because simulations represent an adaptive and potentially costly form in instruction, three general criteria apply to the design of instructional simulations (Atkinson & Wilson, 1969):
The criterion of adaptivity – The ability to modify qualities of the instructional experience based on the actions of the learner
The criterion of generativity - The ability to generate some portion of the instructional artifact at the time of use
The criterion of scalability - The ability to produce instructional experiences in greater quantity without corresponding linear increases in cost
Simulation Architecture
The design architecture of an instructional simulation can be viewed as a composite of many subdesigns, including: (1) a core that computes model state changes; (2) a strategic system of model-experience augmentations; (3) a user control system; (4) a message-generation system; (5) a system for creating surface representation; (6) a system for executing the simulation; and (7) a system for data management. A common approach to simulation design is to center the solution on a software architecture, but doing this indicates an implicit decision that other parts of the design will be forced to fit the software architecture if there is a conflict,” (Gibbons, Mcconkie, Seo, Wiley).