bradley.watt@ontariotechu.net

Ontario Tech University

Abstract

Simulation-based training is a widely used form of training across many disciplines. It allows instructors to expose students to a wide variety of problems and situations which require learners to utilize learned knowledge and skills. This chapter merges two existing simulation classification systems to define a specific type of simulation: experiential computer-based simulation (ECBS). The benefits and issues found in existing research surrounding the use of ECBS in training are examined. Benefits include safety, efficiency, skill development, replication of complex environments, engagement, and temporal control. Issues include an unwarranted focus on fidelity, a lack of grounding in instructional design, and a misunderstanding of how to employ simulation best. Based on these findings, best practices for instruction with ECBS are identified. The best practices are then grounded in Kolb’s Experiential Learning Cycle, with a model for effective instruction with ECBS emerging.

Keywords

experiential learning, performance, simulation, training

Introduction

Imagine a scene where the captain of a large ship is navigating through a narrow, winding waterway being crisscrossed by dozens of smaller vessels. As they attempt to round a turn, a critical failure occurs in the ship’s steering gear, forcing the captain to make a split-second decision to avoid colliding with other vessels or running the ship aground. Training for this scenario with a physical vessel would be impossible, as the circumstances would cause great risk to personnel and equipment. However, training with a simulation of this experience is possible, repeatable, and effective.

Using simulation to meet training requirements and improve human performance on the job has been well-validated (Stevens & Kincaid, 2015). While advancements in information technology have lowered the cost of computer-based simulations, purchasing, operating, and maintaining this technology is still quite costly. Because of this cost, time spent in simulations, particularly those with high fidelity, is a limited resource for most learners. Because of this, it is imperative that instructors make the most of the time available in simulation.

This chapter will address the benefits and issues of one type of simulation: experiential computer-based simulation. Principles for effective instruction will be deduced from existing research, and a practical model will be proposed.

Background Information

Defining the Concepts

Simulation is an umbrella term, and for our purposes, it needs to be narrowed significantly. To begin with, a simulation can be thought of as a reproduction of a particular aspect of an observed or possible reality (Landriscina, 2013). Simulations are active in that they occur over a period of time. They are also interactive, meaning that those participating in the simulation have some aspect of control or causal power. Simulations are often grounded in models, which are representations of real or imagined systems (Landriscina, 2013). When dealing with simulations using computers, models can be thought of as mathematics underlying the computer program itself.

Simulation-based training involves the use of a simulation to impart competencies or to teach someone how to do something (Kim et al., 2021; Salas et al., 2009). Theorists have devised several ways to categorize simulation-based training, and we will use two of them to define our scope further.

First, Salas et al. (2009) identify simulations as falling into one of three loosely defined categories, which are defined by the type of model engaged with. They include role-playing, physically based, and computer-based. Role-playing requires participants to engage with fictional problems, where interactions of the role players themselves create the model. An example of this is a practice interview, where the instructor plays the interviewer. Physical simulation requires participants to engage with a physical model. An example of this is the use of dummies in CPR training. Computer-based simulations require participants to engage with an electronic model, such as in a flight simulator.

Second, Landriscina (2013) classifies simulations into two types based on the nature of the student’s interaction with the model. Simulation building is characterized by a student’s active involvement in the construction of the model, such as elementary school students constructing a bridge from drinking straws. Simulation using is characterized by a student engaging with a previously developed model, such as a participant in fire extinguisher training extinguishing a small, controlled fire.

This chapter will examine a subset of simulations defined by combining the classification systems above, as depicted in Figure 1. It will focus on the “computer-based” subset of the Salas et al. (2009) model and the “simulation using” subset of Landriscina (2013). We will refer to these simulations as experiential computer-based simulations (ECBS). As the name ECBS implies, these simulations involve a student interacting with and learning from a computer-based simulation designed for the purpose of imparting specific competencies. The lower right section of Figure 1 represents ECBS.

Figure 1
Combination of Simulation Classification Models

Advantages of Experiential Computer-Based Simulation

The literature shows that ECBS training has well-established use cases in many fields. These include clinical training (Dawe, 2014), maritime navigation training (Kim et al., 2021), nuclear power plant operation training (Flandin et al., 2022), military training, and aviation training (Straus et al., 2019). The advantages offered to each field and each use case are unique. However, several general advantages of ECBS can be deduced from empirical research. These advantages are summarized in Table 1.

Table 1
Advantages of Experiential Computer-Based Simulation

Issues in Experiential Computer-Based Simulation

While ECBS offers many advantages in training, it is not without issues. First, ECBS has suffered from an overestimation of the importance of fidelity (Straus et al., 2019).  In general, fidelity can be described as the degree to which a simulation represents the real world (Kim et al., 2021). The urge of developers to increase fidelity is understandable. Computing resources and high-resolution visual displays have become cheaper, more powerful, smaller/thinner, and more widely accessible than ever. New technologies like virtual reality and augmented reality head-mounted displays are widely available and low-cost. The issue is that increases in fidelity have not been associated with increases in performance (Stewart et al., 2008; Straus et al., 2019). Rather it appears that while the relationship between fidelity and performance is generally positive, it is non-linear (Kim et al., 2021), meaning that the level of fidelity needs to be aligned with the training task.

Second, ECBS has suffered from a lack of grounding in instructional design and models of learning (Landriscina, 2011; Stewart, 2008). It seems that many instructors assume that having an experience in a simulator is enough to facilitate learning, and so little actual instruction is done (Zigmont, 2011). This belief can lead to most resources being put into the development of an ECBS and little effort put into guidance for teachers on what content should be taught and the methods to do so (Straus, 2019). Flandin et al. (2022) have pointed out that the weight of academic literature is equally skewed toward issues of fidelity over instructional design.

A third issue that can be identified in the literature is that practitioners and researchers often misunderstand how best to employ ECBS in the learning process. As noted in the section above, ECBS has unique benefits, which allow it to excel in specific areas over physical simulation. But what is commonly found in ECBS is training structured as if it were a physical simulation using real equipment and forcing students to proceed ‘lock step’ through a pre-determined number of repetitions, as opposed to training to competence (Stewart et al., 2008). Additionally, Zigmont et al. (2011) note that classroom climate and group dynamics are often overlooked in all forms of simulation. They argue that trust, respect, and rapport are essential for learning in simulation because much of the learning occurs as part of a group.

Applications

Principles of Effective Instruction Using Experiential Computer-Based Simulation

Effective instruction using ECBS can be thought to hinge largely on the learning environment and processes occurring around the simulation itself. Often the instructor has little to do with the simulator design but is largely responsible for creating the learning environment and processes surrounding the simulator’s use. The following four principles may help an instructor create effective instruction using ECBS.

First, ECBS should be viewed as a place to experiment and elaborate on knowledge (Flandin et al., 2022). Second, instructors should view ECBS as providing an environment to construct and alter their mental models (Landriscina, 2011). Third, instructors should ensure that they are orienting students toward learning, providing scaffolding, and offering regular feedback (Zigmont et al., 2011). Finally, instructors should ensure that opportunities for interactions with other students are provided (Kim et al., 2021).

Grounding Experiential Computer-Based Simulation in Theory – Experiential Learning

Grounding training using ECBS in a learning theory may help an instructor to apply the four principles of effective instruction, as well as to address its issues. At its heart, ECBS aims to provide students with an experience that facilitates learning. Kolb’s Theory of Experiential Learning shares this focus on experience as the basis for learning (Kolb, 2014). The experiential learning cycle, depicted in Figure 2, is a component of Kolb’s Theory. It provides a viable framework to ground the use of ECBS in training. This cycle can be used as an adaptable template to create lessons, courses, and programs (Kolb & Kolb, 2018). It consists of four stages: concrete experience, reflective observation, abstract conceptualization, and active experimentation (Kolb, 2014).  In plain language, the process can be thought of as a learner having an experience, reflecting on their experience, forming, changing, or confirming their beliefs, and acting or testing these new (or confirmed) beliefs.

Figure 2
Kolb’s Experiential Learning Cycle

Within ECBS, the experiential learning cycle may take on a somewhat specific form. One design, which may be used, is depicted in Figure 3 and is described below.

• The simulation experience initiates the learning cycle. It should be a complex situation requiring learners to use existing mental models (Salas et al., 2009; Zigmont et al., 2011).
• Following the simulation, a skilled instructor debriefs the activity with individuals and/or groups. They should focus on providing feedback, facilitating reflection, challenging reasoning, and helping students see context (Sellberg, 2018; Zigmont et al., 2011).
• The debrief and reflection will aid the student in constructing and altering mental models associated with their experience. For the instructor, it is important to note that this process should be given time and not placed under emotional pressure (Kolb & Kolb, 2014).
• Students then test and experiment with their updated models in follow-on simulations. For the instructor, this means that scheduling and skill progression should be flexible, aimed at reaching competence, and not linked to specific “time in simulator” requirements (Dawe, 2014).

Figure 3
Proposed ECBS Design Framework

Conclusions and Future Recommendations

ECBS offers instructors a powerful tool to help students learn complex knowledge and skills. This type of simulation can offer students a safe, engaging environment to practice and learn. There is also a benefit to instructors who can replicate challenging conditions and easily pause, reset, and repeat scenarios. However, the effective implementation of ECBS can be challenging, and instructors frequently encounter issues with simulation fidelity, instructional design, and ineffective use of simulations. Kolb’s Experiential Learning Cycle offers instructors a framework to organize their instruction using ECBS. This framework incorporates many of the best practices identified by empirical research.

References

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