atw - International Journal for Nuclear Power | 2.2024

38
Operation and New Build
Fig. 8.
A graph showing that as players age, their dexterity for games that
require skill and reaction time reduces compared to the younger cohort.
players master the initial levels created by the
designer.
Work by Birk et al, [16] demonstrates a strong preference
for game type (e.g. puzzle vs adventure) with age. Their
work can be characterized by the graph shown in
Figure 8. Their work included results from different
game types-achiever, mastermind, and seeker for low
performance and conqueror, daredevil, and survivor
for high performance. Their work was recharacterized
in Fig. 8 as performance roughly correlates to skill
level.
The graph shown then would indicate that games may
need to be less performance-oriented to be tailored
to the older demographic. This, of course, risks less
engagement by the younger demographic. Short of
creating two different games, or using Generate AI,
some trade-offs will have to be made in game design to
reach the full demographic.
Given the success of the Health and Safety fields in
leveraging Serious Games/VR, their examples could
be used as a model for improving the update and
success in the nuclear field. There are a diverse set of
use cases that all could be applied to nuclear industry
applications.
It has also been promising to find evidence of the costeffectiveness
for the Serious Game/VR approach. While
this is probably just as true for the VR alone approach,
it does indicate that adding the Serious Game side does
not likely increase costs.
Some interesting results also indicate that data collection
can be much more effective using this approach.
This was a potential benefit that was not mentioned as
one of the potential benefits of the approach.
7. Conclusions
The following are the major findings of this literature
review.
⁃ The literature review reinforces that large opportunities
exist for study in the area of Serious Games
combined with VR Training.
⁃ The lack of papers and research in this area, as
compared to VR Training on its own, shows that the
need exists and should be explored. Specifically,
there are very few papers to be found in the area of
Nuclear Training.
⁃ Serious Games can be effectively designed and
analyzed using the Learning Mechanics-Game
Mechanics model, resulting in more effective
Serious Games.
⁃ We can conclude that the Serious Game/VR
approach is effective across a wide range of industries
and age groups. It can also provide us with
insights by providing data that might be very hard
to collect using other approaches.
⁃ There is an indication that this is a cost-effective
approach based on the low cost of headsets and the
relatively low accuracy required of a game versus a
Digital Twin.
⁃ There is no global standard for VR radiation protection/detection/shielding
training in industry
⁃ Industry focuses on training as opposed to education,
and Serious Games can be effective for
training
The final conclusion is that further research in this area
will be valuable and can contribute to the greater use
and acceptance of Serious Games combined with VR
training within the Nuclear Industry as well as providing
more impacting tools in this area.
References
[1] LaValle, S. M. (2017). Virtual reality. Cambridge:
Cambridge University Press.
[2] Jason Peterson. Virtual Reality, Augmented Reality, and Mixed Reality
Definitions. EMA, version, 1, Jul 2017
[3] The nuclear power industry’s ageing workforce: Transfer knowledge
to the next generation in IAEA-TECDOC-1399, June 2004
[4] Rodič, Blaž. “Industry 4.0 and the New Simulation Modelling Paradigm.”
Organizacija 50, no. 3 (July 31, 2017): 193–207. https://doi.org/10.1515/
orga-2017-0017.
[5] Schimanke, Florian, Robert Mertens, and Oliver Vornberger. “Spaced
Repetition Learning Games on Mobile Devices: Foundations and
Perspectives.” Edited by Dr Markus Ketterl, Dr Christopher Brooks, and
Mr Florian Schimanke. Interactive Technology and Smart Education 11,
no. 3 (January 1, 2014): 201–22. https://doi.org/10.1108/ITSE-07-2014-0017.
[6] Cagiltay, Nergiz Ercil, Erol Ozcelik, and Nese Sahin Ozcelik. “The Effect
of Competition on Learning in Games.” Computers & Education 87
(September 1, 2015): 35–41. https://doi.org/10.1016/j.compedu.2015.04.001.
[7] Michaud, Laurent, and Julian Alvarez. Serious Games : Advergaming,
Edugaming, Training... iDate Consulting and Research, 2008.
[8] Lameras, Petros, Sylvester Arnab, Ian Dunwell, Craig Stewart, Samantha
Clarke, and Panagiotis Petridis. “Essential Features of Serious Games Design
in Higher Education: Linking Learning Attributes to Game Mechanics.”
British Journal of Educational Technology 48, no. 4 (2017): 972–94.
https://doi.org/10.1111/bjet.12467.
[9] Bedwell, Wendy L., Davin Pavlas, Kyle Heyne, Elizabeth H. Lazzara, and
Eduardo Salas. “Toward a Taxonomy Linking Game Attributes to Learning:
An Empirical Study.” Simulation & Gaming 43, no. 6 (December 2012):
729–60. https://doi.org/10.1177/1046878112439444.
Ausgabe 2 › März