Various Forms of Simulations

Simulations are instructional scenarios where the learner is placed in a "universe" defined by the teacher/simulation designer or even the student himself in some cases. They represent a reality within which students interact with the simulated artifacts. Students experience the reality of the new, expected or unpredictable scenarios and gather new meanings from them. A simulation is a form of experiential learning which fits well with the principles of student-centered and constructivist learning and teaching (UNSW, 2018). Instructional simulations also have the potential to engage students in "deep learning" that empowers understanding as opposed to "surface learning" that requires only memorization (Carleton, 2018).

In 2011, when I and my educational initiatives founding team, were planning and preparing to setup a tertiary education institute, we had done detailed simulations using MS-Excel, along with writing Excel Macros (code) for various scenarios, based on our previous experiences and advice of subject matter experts. At that time, without the actual experiential learning for that particular enterprise in a real world setting, which none of the founding team members had, simulations were the only thing we could do. We knew that it was not the perfect solution and we could be off by a margin of 3X or 5X, but at that time, in the absence of too many other viable options, it gave us enough courage to get things started. Also, no amount of theory or textbook could make us feel comfortable enough to start building a University from scratch. Fast forward 2018, once the institute was up and running, and when we repeated the same exercise to project for the next 10-years, we made quite a bit of changes to the original model; however, this time based on our immersive and transformative experiences of the last seven years. This time, we felt a lot more confident in our simulations and they were a lot more detailed and precise, compared to what they were seven years ago. In short, simulations are only as good as the research and more importantly experience of the design team; and improving upon them is a two-way iterative process. Using simulation tools, you make certain decisions and learn new things, and sometimes give new meaning to old ideas, and depending upon how they pan out, you make changes to your simulation model; hence, your real world learning feeds into your simulation models. Of course, this was dependent upon us being able to distill complex decisions into numbers and equations and eventually a comprehensive financial model. It was an invaluable method and guides us to this day.

On the other hand, if it were some sort of negotiation with an adversary and/or multiple parties, a scenario-based mock negotiation simulation would have yielded new learning and enhanced our understanding of the complex bargaining positions of various adversaries. This is also an excellent way of seeing textbook theories being applied in real-world situations. Business schools across the globe have extensively used such simulations, at least for a couple of decades now, to teach Managerial Negotiations, mostly to graduate students. A similar understanding can be derived from mock legal trial simulations, i.e. even in matters of life and death, even if such simulations cannot be reduced to simple numbers, equations, laws of physics, or lines of code.

When it comes to teaching science and/or computing concepts, especially, in a K-16 setting, it would be fair to say, in most scenarios, that there very few substitutes for experiential and/or lab based learning. You have to be able to do it with your own hands to really get it and understand various nuances of the concepts. However, having said that, having access to practically unlimited and expensive lab resources for all students is a luxury and in many ways somewhat idealistic. In a country where I live – Pakistan, even in elite high schools with decent Ivy League placements, the labs are ancient and at best minimal in their capability to host not more than 50-75 different science experiments. In such a scenario, simulation based science learning tools, like the ones from PhET Interactive Simulations, Colorado, are excellent add-ons, essentially, giving students and teachers hundreds of simulations with open source licenses. Besides practicing concept using pre-defined simulation models and/or scenarios, this also means that the ambitious students and/or teachers can tweak/reprogram/customize the simulations and take their understanding / learning truly to the next level.

Also, I would even argue that the range of experiments from Physics - including Nuclear and Quantum Physics, Genetic Engineering, Earth Sciences, Neurosciences, Chemistry that simulations can provide, especially, keeping in view human safety requirements, may not be possible in real labs; therefore, in many scenarios simulations might be the only option. We already know this all too well in the field of Medicine and flight / pilot trainings. In fact, there are now full-fledged graduate degrees in Simulation Sciences, Computational Neurosciences, Computational Biology and others to train individuals who create such simulations for others to use and solve complex problems and gain new knowledge which simply cannot be done through experiments or theory alone.

To summarize, the new learning afforded by simulations are multi-modal, enables active knowledge making, i.e. changes the balance of agency (Cope & Kalantzis, 2018), and in my cases are the only option to proceed to the next steps of learning and understanding for that subject. I believe simulations will continue to be an integral part of the 21st century New Learning Affordance framework, especially, because it pushes the epistemic dimensions of learning (Cope & Kalantzis, Epistemic Dimensions of Learning, 2018) which we need to thrive in the 4th Industrial Revolution.

References –

1. (UNSW, 2018): https://teaching.unsw.edu.au/simulations

2. (Carleton, 2018): https://serc.carleton.edu/sp/library/simulations/why.html

3. (Cope & Kalantzis, 2018): https://www.coursera.org/learn/elearning/lecture/5RHwL/active-knowledge-making-part-2d-changing-the-balance-of-agency

4. (Cope & Kalantzis, Epistemic Dimensions of Learning, 2018): https://www.coursera.org/learn/elearning/supplement/9LEgr/epistemic-dimensions-of-learning