The Latin of simulation (simulō) means to imitate/pretend, which may have a negative connotation in that simulations might be regarded as false/unreal representations. Plato’s conception of mimesis (μίμησις, Greek term for simulation) had been an imperfect copy or fictitious replica of reality. In contrast, Aristotle notion of mimesis had been a “means to know nature through representations which can be valid and acceptable” (Landriscina, 2012). This, Landriscina points out, is an important shift in emphasis “from imitation to representation” where mental models are key to simulations.
In model-based instruction the underlying model assume a significant function, namely the identification of similarities and differences between the model and the phenomenon it represents. The process results in transforming ideas; confuse and approximate; resulting in more precise and rigorous comprehension. This, Landriscina says, also “happens when a student compares his own mental model of a system with that of a simulation”. He illustrates this with Plato’s example from Politics (Statesman) of cognitive role of the models, or paradeigmata (παραδείγματι):
one of the characters of the dialogue refers to the model of the weaver, where the technique of the politician is compared to that of the weaver who weaves fibers of different nature to create a single fabric
Senge (1990, cited by Landriscina) describes mental models as “deeply ingrained assumptions, generalizations, or even pictures and images that influence how we understand the world and how we take action”. Seel (2003, cited by Landriscina) examined the relation between mental model and education and formulated a teaching and learning theory: Model-Centered Learning and Instruction. Seel differentiated mental-; conceptual-; and design and instructional models:
- Mental model, the internal and subjective model of a system
- Conceptual model, which is objective and shared by a scientific community
- Design and instructional model, used for building the user interface and the learning tasks
To serve as simulation model, the conceptual model must be stated in mathematical terms (rules and equations) in order to be developed as computer programmes. In order to create simulated learning; a mental model of the phenomenon must be formed, studied and use as a basis for prediction, inference, and explanation. Landriscina (2012) cautions by means of Senge’s (1991) words that “simulations with thousands of variables and complex arrays of details can actually distract us [students] from seeing patterns and major interrelationships” and result in misconceptions by students. However, with “black-box simulation models”, for example SimCity® the student interacts with the various scenarios and applications without observing the rules of the game the creators programmed.
Landriscina, F. 2012. Simulation and Learning: The Role of Mental Models. In Seel, N.M. (Ed.) Encyclopedia of the Sciences of Learning. Springer Science + Business Media.