Comparison between simulation and conventional training: Expanding the concept of social fidelity

Daily operations onboard ships are very challenging due to man–machine interactions. To improve daily operational safety and to prevent losses due to machinery breakdown, effective risk management techniques need to be developed, considering various operational and environmental factors affecting the seafarers' performance. The current study explains the comparison between simulation and conventional classroom training to enhance safety in maritime operations in compromised environments. The contribution of this study lies in introducing the concept of social fidelity in simulator‐based training. This study bridges the gap between computer technology and collaborative learning activities in simulator‐based training. The result obtained through the simulation improves marine engineers' training and enhances the reliability of marine engines. This paper concludes by proposing a set of recommendations for the future design of simulator‐based training for marine engineers.


| INTRODUCTION
The aviation community has been using a simulator crew training program since the 1970s due to the high number of fatal accidents in the aviation industry, which were known to be caused by human error.
Human error is something that is unintentional, also known as skillbased error. 1 Simulator training has been a part of the aviation industry in order to improve crew skills and decision-making. 2 The Maritime industry started using a similar approach, that is, simulator-based training, in the 1990s after several accidents were caused by human error. 3 Simulator-based training and its history in providing opportunities for training in all crucial professions such as marine, aviation, and healthcare in a safer environment have surfaced due to the low-risk factor. 4 In the marine industry, time-consuming and otherwise costly skills are provided through simulator-based training that provides an actual feel of the ship. 5 The controlled simulator environment also has academic advantages, as exercises can be designed to train and gage specific learning outcomes, which are adjusted to the student's level of competence. 6 It has not only improved student understanding but has also assisted in their learning experiences. 7 Creating the Engine room learning environment is a challenging task, but with the increased development of communication technology, it has become comparatively easier and achievable. 8 The reliability of the training system increases as the environment becomes more like the actual physical work environment, for example, mimicking the ship's engine room along with the audio or visual effects. 9,10 In simulator training, a prior assumption has been that higher simulator fidelity corresponds to a higher resemblance of the technological attributes that represent a work environment and that physical analogy is a prerequisite for high-quality training of professionals. 4,11,12 This study explains the conventional understanding of the concept of simulator fidelity and finds out how additional factors may or may not influence discerned training quality among professional maritime officers. Simulator fidelity is defined as how close a simulator emulates reality. Student-centric teaching is the recommended approach to modern-day pedagogy, especially in outcome-based education; students get immediate feedback while the teachers serve as facilitators of learning activities rather than physically applying the traditional lecture. 13 Classrooms may need to be equipped with a complete simulator and sound system that would stimulate the students' enthusiasm to learn the lessons with interactive sounds from the teachers' presentations. Acquiring software applications for simulatorbased courses would provide hands-on experience for them to learn certain skills directly.
The main objective of this paper, as stated above and in accordance with the initial literature used, is to expand the existing understanding of the simulator and social fidelity and to explore other factors that may aid perceived training quality. Also, this paper will assess if the physical resemblance between the engine room simulator and the real engine room environment correlates at any level, bringing students to achieve a better understanding of the vessel.
It is analyzed from two angles: the first one is the comparison between simulator-based training and conventional classroom training. The second one is Social Fidelity.

| METHODOLOGY
In this study, the exploratory approach is used as two different training programs are observed for training, that is, simulator-based training and conventional classroom training. The study explains how trainer-trainee interactions, task factors, and simulator technology effects perceived level of fidelity and the quality of training. Focused feedback from the engine officers is also an integral part of the whole process. After developing daily engine room operational scenarios and identifying human-related activities, we will derive the human error probability (HEP) using the SLIM methodology, as shown in Figure 1.

| Step 1: Develop daily operational scenarios
The first step of the methodology is developing the engine room daily operational framework and identifying the operational marine activities. Each activity is designed in such a way that it starts with a basic skill level and gradually increases to an advanced level based on the difficulty of performing the task, leading to the completion of the task with a higher level of proficiency and critical thinking.

|
Step 2: Identify human-related activities A very prominent factor of this research is to recognize human-related activities. All the tasks are divided into two categories: Critical Tasks and Noncritical Tasks. Critical tasks are those that are to be completed in a specific guided sequence in order to avoid accidents led by human error. All tasks, other than critical, are known as noncritical tasks.
Human error is a critical factor in the shipping industry, and the numerous human errors that occur during the maintenance of marine engines cannot be ignored. 14 The motive behind identifying the human-related activities is to later incorporate them in simulator training to minimize the occurrences of human error and prevent accidents, which will be achieved through the evaluation of operational performance on the simulator.

| Step 3: Training and data collection
The sample we have is divided into two groups: Group A and Group B. Group A will receive the simulator-based training, whereas Group B will be given conventional classroom training by the marine experts.
An expert questionnaire is also developed, which will aid in acquiring results from quantitative and qualitative data collected from both the training groups. Upon selecting a relevant panel of experts who carried out the F I G U R E 1 Methodology flow chart. HEP, human error probability assessment, selection, rating, and weighting of PSFs, ascertaining the consensus of expert judgment is essential in this study as the rating of PSF is very important for calculating SLI in the SLIM process. The "ideal 9 rating" for each PSF was then selected, ranging from 0 to 9 (9 mean maximum value and zero mean minimum value). As mentioned above, marine operational activities are rated first, and then weighing has been done for these performance shaping variables to develop SLI. This study selected marine engineers with at least 10 years of industry experience for weighing and rating. HEP is measured using the relevancy of the figures, which represent the relative importance of each task. These ratings are then multiplied by weighing to produce SLI for each task. To enhance the accuracy of the outcome, HEP was estimated after acquiring SLI for each activity. However, "a" and "b" constants are then calculated by measuring the lowest (0.15) and highest (105) HEP values along with the measurement of SLIs. The final equation is as follows 15 :

| Step 4: Evaluation of results
By using Equation (1), HEP values are estimated for the above five operational activities, which contain 65 tasks. Simulator HEP is compared with Experts HEP to find the correlation between simulator-based training and real ship experience.

| CASE STUDY (APPLICATION OF METHODOLOGY)
One of the most important and critical daily operations is starting the diesel generator and synchronizing it with the running generator. In an alternating current electric power system, electrical synchronization is the process of matching the speed and frequency of a Diesel Generator (D.G.) to a running network or an existing power supply system. 16  The considered operational process is starting DG number 2 and manually synchronizing it with DG number 1. For completing this process, it is necessary to complete five activities, as shown in Figure 2, and each activity has its critical and noncritical task.
The complexity of task increases with each step.

| F.W. system tasks
The diesel engines are subjected to various forms of thermal stresses due to temperature variations. The combustion process creates an excessive amount of heat, and the temperatures in the combustion chamber elevate up to 2000 C. When exposed to such high temperatures, the metal of cylinder heads, liners, and pistons heat up excessively and eventually weaken and are unable to withstand the high cylinder pressures. 20 Heat extraction from diesel engine components must be such that they operate at optimum temperatures within the strength limits of the materials used by the jacket water system.
In the engine jacket cooling water system shown in Figure 2

| Synchronizing DG 2 with DG 1 manually tasks
Diesel Generator synchronization is the procedure of matching technical electrical parameters such as voltage, frequency, phase angle, phase sequence, and waveform of the Diesel generator with a healthy or running power system. 16,20 This is required to be done just before the generator is reconnected to the power system. Lack of synchronizing or poor synchronizing can trip the reverse power relay, thus damaging the generator and the prime mover ( Figure 8).
F I G U R E 5 Seawater system-critical and noncritical task flow chart

| Training and data collection
Thirty-six volunteers with zero or few months of sailing experience participated in this study. The steps adopted for collecting data are illustrated in Figure 3. For training and parametric testing, two groups were designed and each participant was allocated to one of two groups for the training, namely, GA and GB. GA was simulator-based training, whereas GB was conventional/traditional classroom training. Participants in both groups attended 10 weekly sessions. The teaching method was different for both the groups, whereas content was the same.
In GA, a teacher played their role as a facilitator, in order to develop the critical thinking of the student. They initiated and F I G U R E 6 Freshwater system-critical and noncritical task flow chart F I G U R E 7 D.G. system-critical and noncritical task flow chart S34 facilitated individual and collective training. Feedback mechanism was used in this study. Moreover, records of performance were also maintained and a replay system was used for measuring student's performance. However, in training sessions, GA was provided feedback on their performance in simulator testing scenarios in each session.
This was done in an organized manner as part of a continuous process during the whole training course with the motive of making the participants conscious and reflective about their behavior and decision process, as shown in Figure 3.
In GB, a teacher played their role as an expert. Different concepts, principles and facts were explained to the participants in this training method. GB was provided feedback from the trainer after each assessment. After 10 weeks of training, both the groups were assessed in the same operational task. GB received additional 1-week simulator familiarization training before assessment.
Thirty-six experts with marine engineering unlimited license and 10 years' experience took part in this experiment. Each expert rated the influence of each PIF to perform the same operational task on board.

| RESULTS AND DISCUSSION
The result shows how technology increases learning and retaining ability in a simulator-based training environment along with advanced computer technology and other extensive collaborative activities.

| Comparison between simulator and conventional training
The level of complexity in developed scenarios increased gradually with each exercise. Fuel oil system and Lube oil system required a low-competency level. Freshwater and seawater systems required a medium competency level. Starting DG and synchronizing DG required a high-competency level.  Here in Figure 9, based on our statistical analysis, it has been confirmed that GA performed better in critical tasks than GB considering the extra week of training before assessment.
The descriptive statistics again take us to our explanation that the critical thinking and emergency tasks were carried out better by GA than GB showing a ratio of 6:1 ( Table 2).
Result of Groups A and B show that the last task, which required critical thinking and engineering skill, including confidence, was completed by 6 Group A students and 1 Group B students.   Providing training in a risk-free environment where repetition of challenging situations can be recreated and then discussed in depth so the performance error reduces in an actual onshore scenario, the simulator-based training proves to be advantageous for trainees as per the results obtained from our data. Implementation of this methodology helps in making a decision instantly, which, in turn, supports the internal safety program. It also ensures industrial maintenance safety of the maritime field.

| Simulator-based training
For this, we used the Pearson two-tailed correlation test in order to determine the correlation between the simulator and expert HEP.
The two-tailed test was used so we could see the positive and negative approaches to our hypothesis. The table denotes that the experts' human error probability and SIM human error probability are significantly correlated at 0.01 level that corresponds to a 99% result, proving that simulator-based training is much more helpful in decreasing the amount of human error and other problems faced by seafarers than the conventional training.
It is best for maritime officers to train under simulator training based on the above results derived from the Pearson two-tailed correlation test as the significance of simulator-based training and better performance of students GA than GB, which we showed in the graph Figure 4. There is a need to structure the program in accordance with the technical requirements and challenges for both critical and noncritical tasks. The simulator training gives a unique opportunity to students, and it is very effective in creating a training environment that is close to actual maintenance procedures that accompany real events.
Literature used in this study and other similar studies have shown that simulators are considered as important tools for maritime training as training tools are developed to produce specific learning outcomes.
Consistent and significant results were seen in the service and training institutions because of simulator training, as per the research.

| CONCLUSIONS
The focus of this study was to elaborate the concept of simulator fidelity and its understanding. Our analysis proved, based on the results obtained from statistical analysis, how the collaborative and technical factors collectively contribute to simulator fidelity and the quality of training given out by the marine relevant professionals. The analysis indicated that a complicated and challenging task like synchronizing the diesel generator can be well trained in a simulator. These suggestions draw us to the conclusion that the general implications of this research will help both in the shipping industry and the training of other professionals such as powerplant engineers. As per the development and increasing technology, it has been predicted how in coming years the marine system will become completely autonomous and to cope with that, future training of marine engineers needs to be upgraded so the margin of human error decreases. Simulator training may highly aid their expertise if implemented further on.

DATA AVAILABILITY STATEMENT
The data that support the findings of this study are available on request from the corresponding author. The data are not publicly available due to privacy or ethical restrictions.