Virtual reality enhances safety training in the maritime
industry: An organizational training experiment
with a non-WEIRD sample
Guido Makransky | Sara Klingenberg
Department of Psychology, University of
Copenhagen, Copenhagen, Denmark
Guido Makransky, Department of Psychology,
University of Copenhagen, Øster
Farimagsgade 2A, 1353 København K,
EUDP, Grant/Award Number: Virtual Reality
Objective: Many industries struggle with training dynamic risk assessment, and how
to bridge the gap between safety training and behavior in real life scenarios. In this
article, we focus on dynamic risk assessment during a mooring operation and investi-
gate the potential value of using immersive virtual reality (VR) simulations compared
to standard training procedures in an international maritime training organization.
Methods: In a pilot study, we compared two ways of implementing a VR simulation
(stand-alone or with post-simulation reflection) to a manual and a personal trainer
condition in a between-subjects design with 86 students in a maritime school. Based
on the results we compared the stand-alone VR simulation to the personal trainer
condition in a between-subjects design in a non-Western, Educated, Industrialized,
Rich, and Democratic (WEIRD) sample of 28 seafarers from the Kiribati Islands at an
international maritime training organization.
Results: The VR simulation group reported significantly higher perceived enjoyment
(d = 1.28), intrinsic motivation (d = 0.96), perceived learning (d = 0.90), and behavioral
change (d = 0.88), and significantly lower extraneous cognitive load (d = 0.82) com-
pared to the personal trainer group, but the differences in self-efficacy, and safety
attitudes were not significant.
Discussion: The results support the value of using VR to train procedures that are dif-
ficult to train in the real world and suggest that VR technologies can be useful for
providing just in time training anywhere, anytime, in a global market where
employees are increasingly cross-cultural and dislocated.
non-WEIRD sample, safety training, simulation, virtual learning, virtual reality
Confronting a vast array of economic, global, technological, and
labour market issues, today's organizations are tasked with a difficult
mission to develop effective, yet efficient training programmes to
educate, inspire and retain their workforce. At the same time, they
face the daunting challenge of maintaining high engagement and
motivation of a new generation of employees, who are increasingly
Received: 4 January 2022 Revised: 14 February 2022 Accepted: 12 March 2022
This is an open access article under the terms of the Creative Commons Attribution-NonCommercial-NoDerivs License, which permits use and distribution in any
medium, provided the original work is properly cited, the use is non-commercial and no modifications or adaptations are made.
© 2022 The Authors. Journal of Computer Assisted Learning published by John Wiley & Sons Ltd.
J Comput Assist Learn. 2022;38:1127–1140. wileyonlinelibrary.com/journal/jcal 1127
cross-cultural and dislocated (Farrell, 2018). Thus, companies are
challenged with the task of administering standardized training,
across a broad range of geographic locations, with an increasingly
global and diverse group of trainees (O'Leary & Cummings, 2007). A
standard solution to have trainers/trainees travel to conduct/receive
training is not sustainable due to the high cost, both in terms of
economy and energy (O'Brien & Aliabadi, 2020). Market analysis
show that in 2019 the total training expenditures in the
United States alone reached $83 billions of which $23 billions was
spent on travel costs, and similar expenditures have been reported
for 2020 (Statista, 2020). Furthermore, the COVID-19 pandemic has
brought about an abrupt and critical need to create flexible learning
and work environments that rethink the way we communicate by
using fluid pedagogical practices and incorporating technology
(Bailenson, 2021; Greenhow & Lewin, 2021). While the pandemic
has accelerated the need to rely on digital solutions for training, a
vast array of benefits including, but not limited to, reduced cost of
training (O'Brien & Aliabadi, 2020), higher flexibility and standardiza-
tion (Hertel et al., 2017), just-in-time training (Ahmad et al., 2020),
employee centred training (Berkley & Kaplan, 2019), and reduced
negative environmental impact (O'Brien & Aliabadi, 2020) suggest
that the digitalization of organizational training is here to stay.
Although digital solutions provide numerous advantages, a chal-
lenge with many online meeting forums such as Zoom, which are
increasingly used as training platforms, is that the social and environ-
mental presence that trainees experience through real world interac-
tions is difficult to replicate (Bailenson, 2021). Immersive virtual
reality (VR) on the other hand has the unique affordance of virtually
transporting trainees to a specific world or scenario that has a high
level of psychological fidelity (Bailenson, 2018), that is, ‘an environ-
ment in which the sensory information is compelling enough to create
perceptions of being physically present in the environment’(Ryan
et al., 2019, p. 18). This allows for interactive and experiential training,
where trainees can rehearse specific sequences with high resem-
blance to their real-world counterparts and learn from their mistakes
by receiving immediate feedback (Feng et al., 2018). Furthermore, it
removes traditional time and location constraints, making learning
possible to anyone, anywhere, anytime (Ryan et al., 2019). However,
although research related to the effectiveness of VR training in gen-
eral and safety training, specifically, is rapidly increasing, little is
known about how such programmes would work with employees
from non-Western, Educated, Industrialized, Rich, and Democratic
(WEIRD) populations (Henrich et al., 2010). Studies with non-WEIRD
samples in realistic training settings are thus needed to ensure that
the value of VR-based educational and training experiences is investi-
gated to ensure that VR is accessible to diverse populations (Mado
et al., 2021; Stanney et al., 2020).
In this article, we explore a growing paradigm in organizational
training and development by investigating the value of a VR-based
safety training by comparing it to standard training solutions in the
maritime industry. Specifically, we investigate the function of such
training programmes with seafarers from the Kiribati Islands, which is
among the 47 least developed countries in the world according to the
United Nations (United Nations, 2020). We have chosen to focus on
employee safety training within the maritime industry, because the
maritime industry has the fundamental challenge of having geographi-
cally dispersed employees with diverse cultural backgrounds, while at
the same time it is responsible for ensuring that safety knowledge
and skills on board all vessels live up to international standards. Thus,
just-in-time safety training with realistic environments is relevant in
Taking this as a point of departure, the main research question
investigated in this article is:
Research question 1: Is VR-based safety training superior to
standard safety training for a non-WEIRD sample of professional
There is mounting evidence that the efficiency of VR-based learn-
ing and training interventions is related to the method by which VR
simulations are implemented (e.g., Klingenberg et al., 2020;Makransky,
Andreasen, et al., 2020; Meyer et al., 2019;Petersenetal.,2020). More
specifically, studies suggest that combining VR with a generative learn-
ing strategy that allows students to reflect over the material after the
lesson can increase learning outcomes (e.g., Klingenberg et al., 2020;
Makransky, Andreasen, et al., 2020;Parong&Mayer,2018). Further-
more, a criticism of VR-based cross media experiments is that conclu-
sions greatly depend on the media which is selected as the control
To address these concerns, we conducted a pilot study with mari-
time students prior to conducting the main study with the non-
WEIRD sample of seafarers to investigate the following research
•Research question 2a: Are there significant differences between a
stand-alone VR safety simulation and the same VR simulation
followed by a reflection activity?
•Research question 2b: Are there significant differences between a
safety training administered through a personal trainer or a
In the following sections, we will describe challenges related to safety
training in the maritime industry. We then elaborate on the rationale
for employing VR-based safety training and why assessing the value
of such training experiences with non-WEIRD samples is particularly
important in this field. Based on these considerations, we finally pre-
sent theoretical frameworks that have informed our choice of instruc-
tional design in the VR simulation, and highlight ways in which this
addresses current challenges in maritime safety training.
2.1 |Safety training in the maritime industry
Since 1945, international trade has experienced an explosive growth.
About 11 billion tons of goods are transported by ship each year and in
1128 MAKRANSKY AND KLINGENBERG
2019, the annual world shipping trade exceeded a total value of 14 tril-
lion US Dollars (International Chamber of Shipping, 2021). This has
made international shipping responsible for transporting approximately
90% of world trade (Dobie, 2020). Nonetheless, while the growth is
predicted to continue in the forthcoming years, a general decrease in
the number of crew members on-board vessels has been observed
(Turan et al., 2016). This places extra demands on the individual crew
member and can potentially lead to situations prone to human error,
which is estimated to be a contributing factor in 75%–95% of marine
incidents (Dobie, 2020). Therefore, it is no surprise that in a recent
report, the Maritime Training Insights Database (2020)considers
‘reducing accidents’and ‘improving safety performance’as two main
drivers of maritime training.
From an employee perspective, seafarers perceive the quality of
their training onboard to be significantly less than optimal (Maritime
Training Insights Database, 2020). This draws attention to a transfer
problem, that is, that participating in safety training by no means guar-
antees that it is effective in improving safety (Krauss et al., 2014). One
explanation is that, currently, safety training is often delivered through
standard training courses which use one-size-fits-all methods, without
assessing individual needs or providing the opportunity for users to
experience the immediate relevance of the training material (Ricci
et al., 2016). Another is that traditional training methods have a low
level of physical and psychological fidelity, which contributes further to
the creation of a transfer gap (Makransky, Borre-Gude, & Mayer, 2019).
This may advance the compartmentalization of safety, that is, that
safety is viewed as separate from the operation and not related to daily
work procedures, which can lead to diffusion of responsibility for safety
(Turan et al., 2016). Furthermore, a majority of operators rely on in-
person and work-based training assessment and 21% of the responding
operators do not assess training outcomes at all (Maritime Training
Insights Database, 2020). We address these concerns by assessing the
effect of a user-centred VR maritime safety simulation on the topic
dynamic risk assessment during a mooring operation on board a vessel
and compare it to standard training methods.
2.2 |The relevance of VR in safety training
Krauss et al. (2014) highlight several features that can positively affect
safety training outcomes including employee characteristics
(e.g., motivation, self-efficacy, beliefs, values), instructional design
characteristics (e.g., interactive and experiential training), commitment
of the management and opportunities to apply the learned material
immediately following training. This is supported by a meta-analysis
by Burke et al. (2006), which found that engaging training was roughly
three times more effective in fostering safety training knowledge and
skill acquisition compared to non-engaging training. In effect, more
engaging training methods are expected to improve knowledge acqui-
sition and transfer as well as the development of anticipatory thinking
(Burke & Sockbeson, 2015).
VR-based simulations are highly engaging because they promote a
high level of the psychological presence (the feeling of ‘being there’in
the virtual environment; Lee, 2004) and agency (experience of controlling
one's own actions, Makransky & Petersen, 2021). Through a head-
mounted display (HMD) that renders the virtual environment stereoscop-
ically,itispossibletocreatehighlycomplex and realistic representations
of real-world scenarios that are too difficult, expensive, or dangerous to
produce in real life (Dalgarno & Lee, 2010). This can provide familiarity
with the associated real-world environment and eliminate potentially dis-
tracting variables (Renganayagalu et al., 2021).
Within recent years, an increasing number of large companies have
begun to explore the vast number of opportunities offered by VR for
corporate training, for example, Wallmart, Verizon (Bailenson, 2020),
and VR simulations are increasingly used in different areas of safety
training, including construction safety training (e.g., Li et al., 2018), med-
ical training (e.g., Andreatta et al., 2010), fire and rescue training
(e.g., Cohen-Hatton & Honey, 2015; Saghafian et al., 2020)andmari-
time safety training (e.g., Markopoulos et al., 2019; Markopoulos
et al., 2020; Markopoulos & Luimula, 2020). Thus, recent systematic
reviews of VR for professional training conclude that VR is particularly
useful for safety training because it provides the opportunity for
trainees to practice procedures immediately and in a safe environment
(Grassini & Laumann, 2020;Naranjoetal.,2020), and it provides mean-
ingful, contextual, and situated learning experiences that increase learn-
ing engagement and motivation (Renganayagalu et al., 2021); two
factors important for safety training according to Burke et al. (2006).
Furthermore, empirical studies and reviews on VR training suggest that
the affordances of the medium can increase engagement (Buttussi &
Chittaro, 2021; Di Natale et al., 2020; Makransky, Petersen, &
Klingenberg, 2020), knowledge retention (Baceviciute, Lopez-Cordoba,
Wismer, et al., 2021; Buttussi & Chittaro, 2021; Chittaro & Buttussi,
2015), safety behaviour (Makransky, Borre-Gude, & Mayer, 2019)and
transfer (Buttussi & Chittaro, 2021; Checa & Bustillo, 2020; Stevens &
Kincaid, 2015). In this way, VR encompasses several affordances that
enhance safety training outcomes according to Krauss et al. (2014).
2.3 |The importance of non-WEIRD samples
Data in the behavioural sciences are dominated by samples drawn
from WEIRD populations. In fact, Henrich et al. (2010) report that
96% of psychological samples come from countries representing only
12% of the world's population. Not only are these samples not repre-
sentative of the worlds' population, according to Henrich et al. (2010)
‘WEIRD subjects are particularly unusual compared with the rest of
the species’(p. 61). More recent examinations suggest that these
empirical patterns persist (Apicella et al., 2020), which once again
actualizes questions regarding the generalizability of previous
research findings and accentuate the need for studies with diverse
non-WEIRD populations (Henrich et al., 2010).
This is particularly relevant within the area of organizational train-
ing, where employees in a global sector such as the maritime industry
are cross-cultural, and crews are on board vessels in different parts of
the world. According to the International Chamber of Shipping (2022),
‘The world fleet is registered in over 150 nations, and manned by over
MAKRANSKY AND KLINGENBERG 1129
a million seafarers of virtually every nationality’. With the five largest
supply countries for all seafarers being China, the Philippines, Indonesia,
the Russian Federation and Ukraine, it is important that studies investi-
gating safety training in this industry do so with non-WEIRD samples.
Apart from being relevant in the maritime industry, this is of high
importance in the field of technology. Linxen et al. (2021) describe
how computer technology is often designed in technology hubs in
Western countries, invariably making it WEIRD. In their review of
papers published in the proceedings of the 2021 CHI Conference on
Human Factors in Computing Systems they find that 73% were based
on Western participant samples. Looking at a recent review on indus-
trial VR training by Naranjo et al. (2020), we found that 54% of the
included papers consisted of purely technological contributions, with-
out testing a human sample. Of the 20 papers that did include human
testing, most of them focused on usability testing and well-explored
samples such as students from Western societies. Furthermore, only a
handful of the 20 papers included testing in a high-ecology experi-
mental setting, such as integrated training connected to the workplace
(Naranjo et al., 2020). This highlights the importance of using non-
WEIRD samples within actual organizational contexts when investi-
gating the value of VR-based training.
2.4 |Designing effective training in VR
There is increasing evidence that the efficiency of VR-based learning
and training interventions is related to how the VR simulations are
designed (e.g., Baceviciute et al., 2021,c; Bower & Jong, 2020;
Cavalcanti et al., 2021; Makransky, Borre-Gude, & Mayer, 2019;
Makransky & Petersen, 2021; Parong & Mayer, 2018; Petersen
et al., 2020,2022). Therefore, we developed the VR-based safety
training simulation using best practice instructional design principles
from multimedia learning (Mayer, 2014), and immersive media
(Makransky & Petersen, 2021). In addition, we used Burke and
Sockbeson's (2015) worker characteristic-work criteria-work context
framework for safety training, which highlights dependent variable
categories that affect safety training interventions.
The Cognitive Affective Model of Immersive Learning (CAMIL) offers
an evidence-based framework for creating VR learning experiences
(Makransky & Petersen, 2021). According to CAMIL learning in VR
can be enhanced if effective instructional methods take advantage of
the technological affordances of the medium. CAMIL identifies two
general psychological affordances of VR: presence and agency which
are positively influenced by technological factors such as immersion,
control factors and representational fidelity (Makransky &
Petersen, 2021). Furthermore, presence and agency can influence
learning, behavioural change, and performance through a number of
cognitive and affective factors such as interest, intrinsic motivation,
embodiment, and cognitive load (Makransky & Petersen, 2021).
Therefore, CAMIL predicts that a higher level of presence and agency
allows VR training simulations to closely mimic realistic training sce-
narios, thereby allowing trainees to construct knowledge based on
realistic interactions with the environment.
While CAMIL provides a theoretical perspective for understanding
and assessing the benefits of technology-based training, other theoreti-
cal models are related specifically to safety training. According to Burke
and Sockbeson's (2015) framework, safety performance that workers
engage in, that is, the work criteria, can be viewed with respect to safety
compliance, which refers to the expected safety behaviours; safety par-
ticipation, which refers to actions of a more discretionary nature and
safety outcomes, which refers to consequences of unsafe work such as
accidents, injuries etc. Safety training interventions can furthermore be
directed at different worker characteristics. These can be broadly classi-
fied as either safety knowledge, understood as the factual, declarative,
and procedural knowledge that the training is aimed at, or safety moti-
vation, referring to interventions aimed at modifying the effort workers
are exerting to engage in safe work behaviour, such as self-efficacy and
confidence. Situational characteristics that might moderate the effects
of safety training is suggested to be safety climate,workplace hazards
and cultural characteristics.
We designed the VR training content based on these models
which are described in more detail in the Methods section. Further-
more, we used these models to assess important training process and
outcome variables including enjoyment, intrinsic motivation, self-effi-
cacy, extraneous cognitive load, reflection, perceived learning, safety
attitudes and expected behavioural change in this study, which we will
elaborate on in the following:
Research on learning in VR suggests that the increased opportunities
to practice in VR, can enhance learning transfer (e.g., Schank, 2005;
Zyda, 2005) and Burke and Sockbeson (2015) found that different
worker characteristics including safety knowledge and safety motivation
are key factors for the transfer of training (Grossman & Salas, 2011). To
address transfer, we measured behavioural change, which in this study
can be defined at the trainee's intentions to change safety behaviour.
Furthermore, we measured motivational and affective factors, including
safety attitudes,enjoyment,motivation,andself-efficacy, which have been
shown to be important for transfer of training (Blume et al., 2010;
Burke & Hutchins, 2007; Burke & Sockbeson, 2015;Kraussetal.,2014).
Safety attitudes are known to affect transfer of learning (Gegenfurtner
et al., 2009) and behaviour (Ajzen, 1991). Enjoyment and intrinsic motiva-
tion are also factors important for learning (Pekrun, 2006) and empirical
research comparing learning through VR to learning through less
immersive media have found lessons in VR can lead to higher levels of
enjoyment and intrinsic motivation (e.g., Makransky & Lilleholt, 2018;
Meyeretal.,2019). Similarly, a range of empirical studies have demon-
strated that self-efficacy, defined as one's perceived capabilities for learn-
ing or performing certain actions (Bandura, 1977), can be increased
through VR-based lessons because learners are given immediate feed-
back to realistic training scenarios (e.g., Buttussi & Chittaro, 2018;
Klingenberg et al., 2020; Makransky, Andreasen, et al., 2020). This is also
supported by studies on safety training, which compare VR with a less
immersive media (e.g., Lovreglio et al., 2020; Nykänen et al., 2020). Addi-
tionally, we measured extraneous cognitive load, which is influenced by
the instructional design and therefore, has been identified as a factor par-
ticularly important for learning in VR, where both the learning content
and the media might be novel (Makransky & Petersen, 2021).
1130 MAKRANSKY AND KLINGENBERG
A pilot study was used to investigate research questions 2a and 2b
with the objective of identifying the best virtual and standard training
method. In the pilot study, we randomly assigned trainees to one of
four conditions: (1) A training manual, (2) Personal trainer instruction,
(3) A stand-alone VR simulation (VR), and (4) A VR simulation followed
by reflection with a personal trainer (VR Reflection).
The sample in the pilot study consisted of 86 students (18 female,
67 male, 1 non-binary). They were from a vocational school (n=18) or
first year students at Svendborg International Maritime Academy
(SIMAC) which is Denmark's largest maritime education centre (n=68).
Most of the students ranged in age from 16 to 34, while three were
above 40 (Mdn =22). A total of 42 (48.8%) responded that they had
never experienced using a VR headset, 35 (40.7%) reporting using VR
for less than 2 h, and 9 (10.5%) had used VR for more than 2 h.
The experiment was implemented as part of students' safety training
in dynamic risk assessment on board a vessel on the topic of safety
during a mooring operation. It took place over the course of 2 days
with participants entering in groups of eight students at a time. The
procedure for all groups followed the same set up and took approxi-
mately 1 h to complete. An overview of the experimental procedure
and the four conditions is provided in Figure 1.
Initially, participants received a common oral introduction. They
were informed that they would be learning about dynamic risk assess-
ment as part of a research study and therefore were expected to
respond to several surveys during the lesson. They were then asked to
sign a consent form which made it clear that their data was gathered
anonymously and that they could withdraw from the experiment at any
time. Students were then given a random ID-number, which blindly
assigned them to one of the four experimental conditions: training
manual (n=17), personal trainer instruction (n=21), VR (n=23), or
VR followed by a reflection exercise (n=25). Then, they were given
the link to the pre-test, which they completed on their own laptops.
For the main part of the experiment, participants were separated into
four different rooms (one for each condition) to avoid distractions and
to ensure that they were blind to the other conditions. Specific precau-
tions regarding the COVID-19 pandemic including wearing face masks
and disinfecting the HMDs with CLEANBOX technology were taken.
3.3 |The four conditions
The training material consisted of four versions of a dynamic risk
assessment training on the topic of safety in a mooring activity on
board a vessel (manual, personal trainer, VR, and VR Reflection).
Extreme care was taken to ensure that the training material included
3.3.1 | Manual condition
Participants in the manual condition were asked to study a safety
training manual individually. The manual was composed of screen
shots from the VR simulation with explanations of the content. It con-
sisted of the same information as the VR simulation in order to main-
tain consistency across conditions. This condition mimicked a scenario
that is currently the most common training method in the industry,
where trainees are provided with manuals related to risk assessment and
training and are asked to learn the material on their own.
3.3.2 | Personal trainer condition
In this condition, a trainer well-known to the students presented a
power point slide show with the same pictures and information
used in the manual to ensure consistency across conditions. Stu-
dents were given the personal training two to four trainees at a
time. During the training lesson, they were able to ask questions
and discuss the topics in more detail. This was designed to mimic a
personal training situation where an expert could introduce trainees
to the topic in detail.
3.3.3 | VR condition
In this condition, participants engaged in the VR simulation described
below. This condition was designed to mimic a scenario where
trainees had access to a stand-alone VR training simulation, without
access to assistance or help from a professional trainer, which is a sce-
nario that would be practical on-board vessels in the maritime indus-
try. It reflects a situation in which HMDs could be readily available
making just-in-time training possible anywhere, anytime.
3.3.4 | VR Reflection condition
Trainees engaged in the VR simulation as described in the previous
condition. However, in addition they were able to reflect over the
training material in a semi-structured session with a teacher from the
school. It was structured around four slides with screen shots from
the simulation identifying the safety hazards that the trainees had
encountered in the simulation. The reflection activity gave trainees an
opportunity to discuss the dynamic risk situations: how they dealt
with them in the simulation and how they would deal with them in a
realistic scenario. This condition was designed to mimic a scenario
where trainees could access professional help after having engaged in
the VR simulation. An example would be on board a vessel where a
MAKRANSKY AND KLINGENBERG 1131
captain or another responsible person could provide additional sup-
port following the training, for example by acting as an instructor who
helps the trainee reflect over the content of the simulation.
3.4 |The simulation
The VR simulation was administered on Oculus Quest HMDs and
developed in Unity 2020. Interactivity in the simulation occurred
through movements of the head and use of controllers. The simulation
was designed as a collaboration between the experts from a VR devel-
opment company, an international shipping company, a maritime edu-
cation academy and the research team from a large European
University to ensure that important work criteria were considered.
The simulation was targeted individual dynamic risk assessment dur-
ing a mooring operation, that is, when the vessel is secured to a per-
manent structure such as a quay or a pier on the shore.
The simulation was designed based on multimedia design princi-
ples (Makransky, 2021; Mayer & Fiorella, 2021), and to mirror the
recent change in safety training focus from what can go wrong to mak-
ing sure things go right. Therefore, it was structured around abilities
which can be considered the functional cornerstones of resilience
(Hollnagel, 2011). This includes being able to anticipate (events
beyond the current operation) monitor (know what to focus on and
perceive changes in performance and environment), react (successfully
detecting, recognizing, and assessing events in time) and learn (pro-
mote, facilitate, and enhance learning from experience). The learning
goals of the safety training simulation were therefore being aware of
potential dangers, recognizing signs of dangers in varying conditions,
responding to dangerous situations, and learning from the outcome of
actions during a mooring operation.
Participants experienced the simulation from a first-person per-
spective. Upon entering the virtual environment, they found them-
selves in a classroom setting. Here, they received general instructions
explaining the purpose of the training as well as practical information
regarding the forthcoming exercise from a virtual instructor. They
were also introduced to the equipment that they would use in the
scenario (see left panel of Figure 2for a screen shot from the initial
training phase). This included how to use a radio to communicate,
how to operate a winch, which is used to control the tension on the
mooring line by pulling the controller forwards or backwards, and how
to use a hand signal to indicate danger and alert other crew members.
FIGURE 1 Illustration of pilot study research design
1132 MAKRANSKY AND KLINGENBERG
In the main scenario, participants were placed on a deck from
where they had to lead the mooring operation. During this part of the
simulation, they had to follow the operation and make sure proce-
dures were carried out correctly and safely as they were responsible
for directing other crew members on board the vessel. First, partici-
pants were instructed by the captain to observe conditions and sur-
roundings to react in time through radio communication and
communication with colleagues on deck (see middle panel of Figure 2)
and on the quay. For instance, they had to notice changing weather
conditions such as increasing wind to predict that this could result in
an increased tension of ropes that could potentially burst. A bursting
rope is a safety threat, and the responsible person must therefore
adjust the ropes to keep them from bursting. At the same time, he or
she must make sure their employees are out of the way to keep them
from being hit if the ropes burst. Thus, the simulation was designed to
make participants anticipate, monitor, and react to specific dangers
such as crew members not wearing appropriate personal protective
equipment (PPE), watch out for bights, and ensure that crew members
are not in the snap back zone (see right panel of Figure 2for a screen
shot of a crew member being injured because they were in the snap
back zone during a rope burst). The participants had to monitor these
different safety risks while being responsible for sending in the lines.
If failing to do these things, participants would experience the conse-
quences of poor safety performance. Ultimately, severe failures
resulted in fatal consequences and the simulation would end. How-
ever, if participants successfully managed to anticipate, monitor, react
and learn the required safety procedures, they would finally return to
the virtual classroom setting, where an instructor summarized key
concepts from the safety training lesson and participants were able to
reflect on their performance.
3.5 |Pre- and post-test measures
The pre-test questionnaire measured demographic characteristics (age,
gender, degree programme and educational level), experience using VR,
and prior knowledge. The post-test consisted of scales measuring enjoy-
ment (Tokel & _
Isler, 2015); intrinsic motivation (Deci et al., 1994); self-
efficacy (Pintrich et al., 1993); extraneous cognitive load (Andersen &
Makransky, 2020), safety attitudes (Lu & Tsai, 2008), perceived learning
(Lee et al., 2010), and behavioural change (Baceviciute, Lopez-Cordoba,
Wismer, et al., 2021). A complete list of items is available in the Appen-
dix S1. All items were on 5-point Likert scales ranging from (1) strongly
disagree to (5) strongly agree.
3.6 |Pilot study results
One-way ANOVAs indicated that the groups did not differ signifi-
cantly on age, p=0.784; prior knowledge, p=0.525; or experience
with VR, p=0.278. Furthermore, a chi square test indicated that the
groups did not differ significantly on gender, p=0.676.
3.6.1 | Research question 2a: Comparing VR and
VR reflection conditions
The left columns of Table 1provide the means and standard devia-
tions for VR and VR reflection conditions on all outcome variables
used in the study. Non directional independent samples t-test indi-
cated that students in the VR condition reported significantly higher
intrinsic motivation t
=2.667, p=0.011, d=0.79, and self-
=2.312, p=0.025, d=0.67, compared to the VR reflec-
tion condition. The differences between the groups on the other five
outcome variables were not significant (see Table 1). The VR condition
without reflection will therefore be used in the main study to investi-
gate research question 1.
3.6.2 | Research question 2b: Comparing manual
and personal trainer conditions
The right columns of Table 1provide the means and standard deviations
for manual and personal trainer conditions on all outcome variables used
in the study. Non-directional independent samples t-test indicated that
students in the personal trainer condition reported significantly higher
FIGURE 2 Screenshots from the virtual reality safety simulation: The left panel shows the introduction phase; the middle panel shows the
trainees view of the pier; the right panel shows a scenario where an accident occurred because the trainee failed to warn a crewmember of
MAKRANSKY AND KLINGENBERG 1133
=2.123, p=0.041, d=0.68; self-efficacy, t
p=0.034, d=0.72; safety attitudes, t
=2.424, p=0.021, d=0.78;
perceived learning, t
=2.139, p=0.039, d=0.69; behavioural
change intentions, t
=2.905, p=0.006, d=0.95; and significantly
lower extraneous cognitive load, t
=2.609, p=0.013, d=0.84,
compared to the manual condition. The differences between the groups
on intrinsic motivation was not significant. The personal trainer condition
will therefore be used in the main study to investigate research
The main study was used to investigate research question 1 by com-
paring the VR-based safety training to the personal training condition
in a non-WEIRD sample of professional seafarers.
The sample consisted of 28 male participants, who were all crew
members with several years' experience working on a vessel (20 had
over 5 years, four had between two and 5 years, and four had
between 1 and 2 years of experience). All had previously participated
in a mooring activity; eight in the role of the responsible person and
20 as crewmembers. Participants were between the ages of 24 and
65 years (Mdn =35). All crewmembers were from the Kiribati Islands,
and the training took place as part of a formal training at the head-
quarters of an international maritime training organization. None of
them reported having used VR for more than 2 h, 6 (21%) reported
having used it but for less than 2 h, and 22 (79%) reported never hav-
ing used VR before. The technological readiness of the sample was
generally low. This was exemplified in trainees needing technical sup-
port to turn on and use the tablets that were used for the surveys.
TABLE 1 Pilot study means, standard deviations, two tailed p-values, and effect sizes for the outcome variables included in the study
Virtual training comparisons Standard training comparisons
Outcome VR VR reflection p-Value Cohens dManual Personal trainer p-Value Cohens d
Enjoyment 4.36 (0.70) 4.07 (0.59) 0.121 0.45 3.24 (0.89) 3.81 (0.78) 0.041 0.68
Intrinsic motivation 4.17 (0.53) 3.67 (0.73) 0.011 0.79 3.81 (0.61) 3.98 (0.67) 0.426 0.27
Self-efficacy 3.99 (0.63) 3.55 (0.68) 0.025 0.67 3.49 (0.74) 3.97 (0.60) 0.034 0.72
Cognitive load 2.10 (0.92) 2.36 (0.90) 0.333 0.29 2.35 (0.72) 1.75 (0.71) 0.013 0.84
Safety attitudes 4.20 (0.64) 3.96 (0.72) 0.229 0.35 3.85 (0.73) 4.31 (0.45) 0.021 0.78
Perceived learning 4.14 (0.72) 4.04 (0.63) 0.591 0.15 3.65 (0.82) 4.16 (0.66) 0.039 0.69
Behavioural change 3.96 (0.79) 3.88 (0.63) 0.710 0.11 3.40 (0.93) 4.11 (0.56) 0.006 0.95
Bold values represent significant differences (alpha =.05).
Abbreviation: VR, virtual reality.
FIGURE 3 Illustration of main study research design
1134 MAKRANSKY AND KLINGENBERG
Overall, the experimental procedure resembled the procedure in the
pilot study. However, only two experimental conditions were
implemented: VR (n=15) in which participants engaged in the VR
safety simulation, and personal trainer instruction (n=13) in which
participants were trained in groups of 2–4 by an experienced trainer
from the international training organization (see Figure 3). The surveys
were administered on iPads supplied by the organization.
The experiment was conducted over the course of 1 day with
participants entering in groups of up to eight at a time. The procedure
for all groups followed the same set up as in the pilot study (see
Figure 3for an overview). Following an oral introduction, participants
completed an online pre-test. Based on their random assignment to
one of the two experimental conditions, they were led to different
rooms, where they engaged in the safety training. Then, participants
were asked to complete an online post-test. Specific precautions
regarding the COVID-19 pandemic were taken during the entire
experiment. The entire procedure took approximately 1 h.
The VR safety simulation used in the main study was identical to the
one used in the pilot study (see above for a description). The pre-test
questionnaire measured demographic characteristics (age and gender),
experience working on a vessel, experience with mooring operations,
and experience using VR. The post-test included the same items as in
the pilot study (see list of items in Appendix S1).
4.4 |Main study results
Independent samples t-tests indicated that the groups did not differ
significantly on age, p=0.053; prior knowledge, p=0.848; or experi-
ence with VR, p=0.291. Table 2provides the means and standard
deviations for the VR and personal trainer conditions for all outcome
variables used in the study. Independent samples t-tests indicated
that the VR group (M=4.58, SD =0.54) reported enjoying the train-
ing significantly more than the personal trainer group (M=3.85,
SD =0.60), t
=3.384, p=0.002, d=1.28. Similarly, the VR group
(M=4.47, SD =0.58) reported significantly higher intrinsic motiva-
tion related to safety training than the personal trainer group
(M=3.83, SD =0.76), t
=2.508, p=0.019, d=0.96. The differ-
ence between the two groups on self-efficacy was not significant
=1.600, p=0.112, d=0.61. Moving to Extraneous cognitive
load, the VR group (M=2.09, SD =0.82) reported significantly lower
extraneous cognitive load compared to the personal trainer group
(M=2.64, SD =0.52), t
=2.089, p=0.047, d=0.82. However,
the difference between the two groups was not significant for safety
=1.788, p=0.085, d=0.66. The difference did reach
statistical significance, with the VR group reporting significantly higher
perceived learning (M=4.53, SD =0.52) than the personal trainer
group (M=4.15, SD =0.32), t
=2.288, p=0.031, d=0.90.
Finally, the VR group scored significantly higher (M=4.42, SD =0.47)
than the personal trainer group (M=3.92, SD =0.66), t
p=0.030, d=0.88 on behavioural change.
The aim with this study was twofold: to investigate the value of using
VR-based training compared to standard training with a non-WEIRD
sample (Research question 1), and to investigate ways in which such a
training intervention is most effectively implemented based on seven
variables of interest (Research question 2a and 2b).
Regarding our first research question, we found that employing
a VR safety simulation among a non-WEIRD sample of professional
seafarers resulted in significantly higher levels of enjoyment, moti-
vation, perceived learning and behavioural change, and significantly
lower cognitive load compared to a personal training procedure but
the difference in self-efficacy between groups was not significant.
Many of these findings are consistent with results from previous
research studies with WEIRD samples that have compared learning
in VR to standard procedures. Thus, our findings contribute to a
growing pool of evidence suggesting that immersive VR simulations
can lead to significantly higher enjoyment (e.g., Cavalcanti
et al., 2021; Makransky & Lilleholt, 2018; Meyer et al., 2019);
intrinsic motivation (Dalgarno & Lee, 2010; Makransky, Borre-
Gude, & Mayer, 2019; Sanchez-Sepulveda, Fonseca, et al., 2019),
TABLE 2 Main study means,
standard deviations, one tailed p-values,
and effect sizes for the outcome
variables included in the study
Outcome Personal trainer VR p-Value d
Enjoyment 3.85 (0.60) 4.58 (0.54) 0.002 1.28
Intrinsic motivation 3.83 (0.76) 4.47 (0.58) 0.019 0.96
Self-efficacy 4.18 (0.55) 4.49 (0.47) 0.112 0.61
Extraneous cognitive load 2.64 (0.52) 2.09 (0.82) 0.047 0.82
Safety attitudes 4.19 (0.52) 4.53 (0.51) 0.085 0.66
Perceived learning 4.15 (0.32) 4.53 (0.52) 0.031 0.90
Behavioural change 3.92 (0.66) 4.42 (0.47) 0.030 0.88
Bold values represent significant differences (alpha =.05).
Abbreviation: VR, virtual reality.
MAKRANSKY AND KLINGENBERG 1135
behavioural change (Makransky, Borre-Gude, & Mayer, 2019;
Mottelson et al., 2021; Vandeweerdt et al., 2022) and perceived
learning (e.g., Hamilton et al., 2021; Makransky & Lilleholt, 2018;
Wu et al., 2020) compared to training methods using less immersive
media. Importantly, the results suggest that the positive outcomes
of learning with VR simulations, identified in the studies referred to
above as well as recent meta-analyses (e.g., Luo et al., 2021;Wu
et al., 2020), are not limited to WEIRD samples.
Not all research points to the positive outcomes of VR-based
interventions. For instance, a recent review on VR serious games
reports that only 30% of the included studies find that VR enhances
learning (Checa & Bustillo, 2020) and a study by Leder et al. (2019)
specifically related to safety training found that VR-based safety train-
ing was less effective than a PowerPoint lesson (Leder et al., 2019).
Thus, our results specifically highlight the importance of using
evidence-based instructional design principles in a developing
immersive simulations. This is theoretically supported by the Immer-
sion Principle of Multimedia Learning (Makransky, 2021) which states
that immersive virtual environments promote better learning when
they incorporate multimedia design principles. That is, immersive
media do not necessarily improve learning but effective instructional
methods within immersive virtual environments do improve learning.
The finding that no significant difference in self-efficacy between
conditions was observed stands in contrast to previous research that
suggests VR simulations increase self-efficacy more than standard
methods (e.g., Buttussi & Chittaro, 2018; Klingenberg et al., 2020;
Makransky, Andreasen, et al., 2020). Several differences between our
main study and previous studies could account for this discrepancy:
First of all, our sample was non-WEIRD, which may have affected
trainees' self-reported answers (Henrich et al., 2010). Furthermore,
the study was conducted with professional seafarers, who had signifi-
cantly higher mean self-efficacy scores (M=4.35, SD =0.52), com-
pared to the students in the pilot study (M=3.76, SD =0.69),
=4.149, p< 0.001. This indicates that the seafarers had a high
initial level of self-efficacy based on actual experience on board a ves-
sel, making the effect of a single training intervention less impactful
than for a student sample. In accordance with previous research, this
indicates that level of professional experience may influence VR-
based outcomes (Sanchez-Sepulveda, Torres-Kompen, et al., 2019).
In contrast to previous findings comparing VR to less immersive
media (e.g., Makransky, Terkildsen, & Mayer, 2019; Parong &
Mayer, 2021), participants in the VR condition reported lower extra-
neous cognitive load than participants in the personal trainer condi-
tion. One explanation of the finding could be that the VR simulation
was learner-paced meaning that trainees could control the pace of the
lesson through their interactions, whereas the personal training took
place in groups of two to four, making it more instructor paced. This
emphasizes affordances of VR, such as the opportunity for creating
individualized, immersive, and interactive content, which allows for
‘learning by doing’(Cavalcanti et al., 2021; Renganayagalu
et al., 2021). This may be specifically relevant for the non-WEIRD
sample of seafarers who were not as accustomed to traditional train-
ing methods as the students at the maritime school, and who, due to
their experience at sea, may have found it easier to relate the content
of the simulation to real life scenarios. Thus, results from this study
point to the many opportunities offered by VR in training, and opens
the doors to exploring these effects with a diverse group of users in
In regard to our second research question, concerning best prac-
tices for implementing VR-based training, some important empirical
contributions can also be inferred. The finding that the VR simulation
that was used alone was just as effective as when the VR simulation
was used in conjunction with a follow-up reflection exercise in the
pilot study provides some support for the viability of using VR
broadly. It suggests that embedding generative learning strategies
such as reflection exercises within the simulation can promote the
successful implementation of VR-based training. Furthermore, it
underscores importance of the relationship between learning content
and choice of design when developing VR simulations for training
(Makransky & Petersen, 2021; Radianti et al., 2020), and highlights
the importance of iterative feedback from users and designers during
the development process. In this study, this was made possible by
developing the VR simulation through a collaboration between
experts within the domains of instructional design, technological
development, and maritime safety training.
5.1 |Practical implications
The finding that VR training was superior to the personal trainer condi-
tion in the main study is promising. Firstly, because the main study was
conducted as part of a real training intervention within an organiza-
tional context, which echoes Radianti et al. (2020) call for more VR-
based research that is integrated within actual interventions. Secondly,
because it was conducted with a non-WEIRD sample of employees
from a country on UN's list of the 50 least developed countries who
did not have a high level of technology literacy. As an example, several
seafarers needed help to begin the pre-test survey on an iPad because
they were not familiar with the technology. Nonetheless, after a brief
introduction to the controls and the HMD, it was surprising to see how
quickly the seafarers adapted to the scenario and interacted naturally
with the virtual environment. The successful implementation of the VR
simulation highlights the potential immersive technologies have with a
broad range of users in the future. This is becoming relevant with digi-
talization of education and training, and the continuing development of
online platforms, such as the Metaverse, which will likely improve
remote collaboration in the future (Gartner, 2022; Kelly, 2022).
Furthermore, this article highlights the benefits of using VR in
future maritime safety training, where relevant stakeholders may take
advantage of its ability to create situated learning experiences in a
safe environment. Besides being a cost-effective way of administering
standardized training across a broad range of geographic locations, it
may reduce the current transfer gap in safety training by making train-
ing available to anyone, anywhere, anytime (Ryan et al., 2019). Fur-
thermore, the finding that a VR simulation can increase enjoyment
and motivation is consistent with expectations employees in the
1136 MAKRANSKY AND KLINGENBERG
maritime industry have about the technology. A recent report from
the Maritime Training Insights Database (2020) asked respondents
about ‘ideal’training initiatives they would prefer if budget and
resources were not limiting factors; common responses among vessel
operators were ‘implementing more Virtual Reality simulation’(p. 29),
‘increased simulation and practical training’(p. 29) and ‘using gaming
technology in training’(p. 29) suggesting a general interest and moti-
vation to use immersive technology in future maritime training.
5.2 |Limitations and future research
Although the results of this study are promising, several limitations
and future research directions should be highlighted. One limitation in
this study was the inability to test the training on board a vessel. From
an organizational training perspective, the ultimate goal would be to
have VR headsets on board vessels for just in time training. Future
studies should therefore investigate the potential of using VR simula-
tions on location rather than in formal training centres as in this study.
Furthermore, it was not possible to assess actual safety behaviour on
board a vessel in a real mooring scenario in this study due to practical
and ethical considerations. Although intentions are considered ante-
cedents of actual behaviour (Ajzen, 1991), research has consistently
shown that people do not always follow their intentions (Sheeran &
Webb, 2016). Previous studies have found that VR safety training
simulations as superior to traditional training methods when assessed
in terms of actual safety behaviour in a realistic environment
(e.g., Makransky, Borre-Gude, & Mayer, 2019). Nevertheless, future
studies should attempt to investigate the effect of VR safety simula-
tions on actual safety behaviour and transfer of training.
The finding that a reflection activity did not improve training out-
comes following the VR simulation suggests that it was possible to intro-
duce generative learning activities within the VR simulation. This finding
is promising and highlights the need to conduct more research related to
instructional design features that can improve learning and training out-
comes in immersive simulations. In general, more research is also needed
to investigate if the mounting evidence related to using VR simulations
in education and training generalizes to non-WEIRD samples.
This article demonstrates the value of VR-based safety training by
comparing it to standard training solutions in the maritime industry.
In a pilot study, students from a maritime school engaged in training
either through a manual, a personal trainer instruction, a VR simula-
tion, or a VR simulation followed by reflection on the topic of
dynamic risk assessment during a mooring operation. Results showed
that personal trainer instruction was superior to a manual, and that
when reflection was already embedded into a VR simulation, adding
a post-simulation reflection exercise did not further improve training
outcomes. Based on our findings from the pilot study, we employed
two conditions (personal trainer instruction and VR) in a main study
on maritime safety training with a group of experienced seafarers
from the Kiribati Islands, which is among the 47 least developed
countries in the world according to the United Nations (2020).
Results demonstrated that the VR simulation group had significantly
higher levels of enjoyment, motivation, perceived learning and
behavioural change intentions and significantly lower extraneous
cognitive load compared to personal trainer instruction. This indi-
cates that VR has potential benefits over standard training solutions
and is effective in delivering training to a non-WEIRD population
with limited technological experience. To conclude, this research
draws attention to the prospects of immersive technologies not only
as potential viable solutions for future organization training, where
flexible, standardized, cost efficient, just-in-time training solutions
are needed, but also as an emerging media that can be employed
with a broad range of users.
We would like to thank Christian Schrøder and Jens Lauritsen along
with their team from Virsabi for developing the simulation used in this
study. We would also like to thank Jeanette Aliaj Juul Jakobsen, Per
Larsen, and Fini Patrick Holsting and their team for their work in orga-
nizing the virtual training that was used in the main study, as well as
Jan Askholm and his team from SIMAC for coordinating the pilot
study data collection. Finally, we would like to thank Adéla Plechatá,
Gustav Bøg Lassen Petersen, Liisalotte Ord
oñez-Bueso, Zuzanna Bald,
David Hvidbak Østergaard and Martin Kampmann for helping run the
experiments described in this manuscript.
CONFLICT OF INTEREST
The authors declare no conflict of interest.
The peer review history for this article is available at https://publons.
DATA AVAILABILITY STATEMENT
The data that support the findings of this study are available on
request from the corresponding author.
Guido Makransky https://orcid.org/0000-0003-1862-7824
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Additional supporting information may be found in the online version
of the article at the publisher's website.
How to cite this article: Makransky, G., & Klingenberg, S.
(2022). Virtual reality enhances safety training in the maritime
industry: An organizational training experiment with a
non-WEIRD sample. Journal of Computer Assisted Learning,
38(4), 1127–1140. https://doi.org/10.1111/jcal.12670
1140 MAKRANSKY AND KLINGENBERG