The word ‘simulation’ has multiple perspectives and one such definition as stated in the Cambridge dictionary is “a model of a real activity, created for training purposes or to solve a problem”. A simulation is an imitation of real-life scenarios, in a controlled environment, so that the participants get to learn from their mistakes, without causing any real damage.
According to Fatimah Lateef, simulation learning is a perfect tool for practice learning and has applications across different disciplines. Furthermore, while simulation learning is a revolutionary concept, however, it is important to acknowledge the fact that it is a technique (and not technology) to provide learners with an immersive experience. Traditionally simulation-based learning has been widely applied in fields such as the armed forces, medical, and aviation.
Applying simulation learning
Simulation learning as a technique is not a new concept, however, its prevalence was seen only in the areas like medical sciences, military training, space flight training, and to some extent in academic institutions’ laboratories and workshops. Now, with the ‘new normal’ kicking in due to the advent of Covid 19, it has become a necessity to expand the horizons of simulation learning.
The ever-evolving IT industry is not far behind in incorporating simulation learning. In this section, the author highlights the application of simulation learning to various facets of the IT industry.
According to Guzman (2015) and Jenkins (2002) programming has been perceived as a very difficult subject to teach, and hence teaching methodology for programming has prompted a rethink. Magana & Silva Coutinho (2017) have elaborated the benefits of using simulation for the purpose of engineering academics, especially, computing. Their thoughts have been further corroborated by Kelly et al (2014), by stating that simulation can help in linking the learning environment to how the professional, as well as the academic future, might be. Meanwhile, Rochester et al (2012), go a step further by suggesting that some academic programs have adopted simulated learning as an alternative to industry placement. Because of these advantages, there is an extensive application of simulated learning in business and education disciplines.
A very important aspect to think about from the perspective of simulated learning, is the cultural differences, as far as approach to learning and academics is concerned. These differences have created a ‘poles apart’ situation in the context of simulated learning. As a result, though the construct and application of simulation might be totally diverse, the enhancement and engagement in learning have been a great success.
In the following sections, the author will talk about:
- How simulated learning is changing the way training is being imparted to technologists
- Simulating an agile learning roadmap
Technology teaches technology
If one were to breakdown the process of creating a computer program into two steps, here’s how it would appear:
Let us not miss out on the fact that the above representation is an oversimplification of the intricacies that surround computer programming. The code writing process is prone to syntax and semantics errors. With the advent of integrated code editors, the code writing process has simplified a bit, but not in totality. However, a simulated learning environment for prospective programmers, will educate them about expected errors, suggest corrective measures, etc. All of this would happen during the training period, so that once out in the real world, learners become better practitioners of good coding practices.
Simulating agile learning
The ‘agile way of working’ has started gaining a lot of traction across organizations all over the world. The demand for agile knowledge among IT enablers servicing clients has created a great need for learning opportunities in this field. Almost every organization has certified trainers, who impart classroom sessions, thereby enabling an agile workforce. However, a major drawback of a simple classroom session is that its scope is limited to theoretical aspects of agility. Moreover, in today’s new normal, it has become important to bring innovation to the process of imparting training. Moreover, with the Agile way of working gaining importance for obvious reasons, learners have started expecting much more than just having a conversation around the Agile manifesto and principles. And this is where simulated learning technique plays such a major role. There are various learning simulators that engage the learners by taking them on a persona-based journey. This helps the trainers with the balancing act of involving teaching as well application of what the participants have learned in the sessions. The simulator allows the participants to practice the concept of Agile estimation, backlog prioritization, facilitate meetings within the team or with the customer, etc. It also exposes them to near real-life situations, thereby stimulating their thought process.
Applying AI for simulated learning
The optimism around AI has increased exponentially, with advances in computing. AI techniques have almost become an integral part of the technology industry, helping us to overcome numerous challenges.
AI will play a major role in revolutionizing simulated learning techniques. If we think about it, today we are talking about applications that have a defined set of real-life scenarios to throw at the learners. However, with the application of AI, the simulators will come closer to what is expected in real life, and that is to expect the unexpected. Through AI, the simulators can be taught to formulate scenarios in real-time so that learners are forced to think on their feet and come up with a resolution. This kind of simulated learning, fully supported by AI, will give us firm and thoughtful decision-makers.
What do the naysayers say?
Simulated learning has been working wonders in the field of academics, classroom training, vocational training, etc. however, purists often cite numerous reasons why simulated learning is not a good option.
One of the most prominent arguments is around the claim of simulated learning to recreate real-life situations. Purists maintain that humans are so complex that simulating their way of thinking in an application or through a gamified technique is basically forcing them to limit their thought processes. Once they are out of the simulator, they might find it difficult to cope with the unexpected.
Another factor that is counted as a major drawback for simulated learning is that it uses technology. And in today’s world, technology changes at the snap of a finger, therefore the system needs to be updated regularly, and this might make the whole concept of simulation learning expensive. In addition to regular updates, the use of technology also requires training people who would be managing these applications, and this will incur additional costs for the organization or institution.
Conclusion
All said and done, the benefits of simulated learning far outweigh the deterrents. However, relying completely on simulated learning, and ignoring the basic theory, might not be a great idea. Hence, it is important to maintain the right balance between, the classroom way of teaching, and simulated teaching. Also, with the advent of technology as an enabler in almost every field, we sometimes tend to ignore the core element of the whole setup, and this would lead to a collapse of the whole system in the near future. Hence, apart from innovation, it is equally important that we do not lose sight of blind spots while designing a simulated learning experience.
REFERENCES
Lateef, Fatimah. “Simulation-Based Learning: Just like the Real Thing.” Journal of Emergencies, Trauma & Shock, 2010, pp. 348–352, 10.4103/0974–2700.70743
Guzdial, M. (2015). Learner-centered design of computing education: Research on computing for everyone. Synthesis Lectures on Human-Centered Informatics, 8(6), 1–165
Jenkins, T. (2002). On the difficulty of learning to program. In Proceedings of the 3rd Annual Conference of the LTSN Centre for Information and Computer Sciences, (vol. 4, №2002, pp, pp. 53–58)
Magana, A. J., & Silva Coutinho, G. (2017). Modeling and simulation practices for a computational thinking-enabled engineering workforce. Computer Applications in Engineering Education, 25(1), 62–78.
Xie, C., Schimpf, C., Chao, J., Nourian, S., & Massicotte, J. (2018). Learning and teaching engineering design through modeling and simulation on a CAD platform. Computer Applications in Engineering Education, 26(4), 824–840.
Kelly, M. A., Forber, J., Conlon, L., Roche, M., & Stasa, H. (2014). Empowering the registered nurses of tomorrow: Students’ perspectives of a simulation experience for recognising and managing a deteriorating patient. Nurse Education Today, 34(5), 724–729.
Rochester, S., Kelly, M., Disler, R., White, H., Forber, J., & Matiuk, S. (2012). Providing simulation experiences for large cohorts of 1st year nursing students: Evaluating quality and impact. Collegian, 19(3), 117–124.
