Learning in vivo

Role of mental models in simulations

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.

Simulation-based learning defined

Learning through simulation may occur in one of two or both ways, namely (a) observation—the simulation serves as illustration of the content to be learned or understood; and (b) direct interaction— learning induced through experience.

Simulation-based learning comprises two parts, namely learning and simulation—the term suggests learning through the use of simulation/s.

• With a simulation one process is imitated by another process (Hartmann, 1996).
• Simulations often focus on the structural aspects of a model rather than the dynamic characteristics, making them relatively static (Hughes, 1999; Grüne-Yanoff & Weirich 2010)
• A simulation is a manifestation of a model, providing a description through a set of intertwined elements (Grüne-Yanoff & Weirich 2010)
• Frasson and Blanchard (2012) concludes after citing the above that simulations entail the action of imitating a model’s dynamics and/or structure with its resulting element; including either static and/or dynamic features.

Frasson and Blanchard (2012) report several features discussed in literature about simulation-based learning opportunities and their classification:

• Realisation—three main groupings of models are differentiated, namely those (a) involving humans; (b) mechanical; and (c) computer enabled.
• Fidelity—the extent to which the model correctly represents—on a continuum from low to high. High fidelity represents more coherently, but do not always provide the best pedagogical opportunities. Low fidelity focus mainly on pedagogically relevant aspects (with fantasy elements possibly added) and as result sometimes more adequate.
• Interactivity—refers to the degree of passive observation versus acting and influence the evolution.
• Immersiveness—is the degree of enabling fidelity and interactivity resulting in accurate real-situational feelings.
• Intelligence—intelligent components often enhances user interaction and allow for various constructive alternatives.

Frasson, C. & Blanchard, E.G. 2012. Simulation-Based Learning. In Seel, N.M. (Ed.) Encyclopedia of the Sciences of Learning. Springer Science+Business Media.

Work-integrated learning assessment methods and practices

Appropriate work-integrated learning assessment methods are a challenge. Apart from maintaining academic standards; relevance and consistency of assessment; deciding what should be assessed; who is responsible, where and when; and how assessment is supported and managed; are among the challenging issues.

A range of potential methods include reflective journals, portfolios, ePortfolios, workplace mentor/supervisors reports and workplace projects. Assessment should not only address skill acquisition and workplace competencies, but also the acquisition of 'soft skills' related to practical application of theory learned. Additionally graduate attributes; what learned about workplace culture and standards of the community of practice. The workplace mentor or employer’s supervisor should authenticate the evidence. Dunn, Schier and Fonseca (2012) identified the following key elements of an ePortfolio:

Dunn, L.; Schier, M. & Fonseca, L. 2012. An innovative multidisciplinary model for work placement assessment. Asia-Pacific Journal of Cooperative Education, 2012(3), 135-145.

Restorative Formative Normative Custodian

In an article titled ‘But I thought you were doing that’ Rowe, Mackaway and Winchester-Seeto (2012) attempt to clarify the role of the host mentor/supervisor in the experience-based learning setting. They present the following model:

The model identifies four key roles: Restorative (supporting the student); Formative (fulfilling an educatinal role); Normative (administrative functions); and Custodian (guardian role within the community of practice). 

The article elaborates on the aspects that make up the four roles.

Rowe, T.; Mackaway, J. & Winchester-Seeto, T. 2012. ‘But I thought you were doing that’ – Clarifying the role of the host supervisor in experience-based learning. Asia-Pacific Journal of Cooperative Education, 2012(2), 115-134.