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Gamified Augmented Reality Training for An Assembly Task: A Study About User Engagement

Gamified Augmented Reality Training for An
Assembly Task: A Study About User Engagement
Diep Nguyen
Heilbronn University
Max-Planck-Strasse 39
74081 Heilbronn, Germany
Gerrit Meixner
Heilbronn University
Max-Planck-Strasse 39
74081 Heilbronn, Germany
Abstract—Augmented Reality and Gamification are displaying
beneficial effects to enhance user experience and performance
in many domains. They are widespread across many areas like
education, industrial training, marketing, and services. However,
the idea of combining the two approaches for an innovative
training instrument is fairly new, especially in assembly training.
Moreover, learning about the effects of gamification on human,
user engagement, in particular, is a complicated subject. There
have been several efforts toward this direction, yet the overall
situation is still nascent. In this work, we present a gamified
augmented reality training for an industrial task and investigate
user engagement effect while training with the gamified and the
nongamified system. The result shows that people perform better
and engage to a greater degree in the gamified design.
AUGMENTED Reality (AR) is growing stronger than
ever. Market research predicts a 70 to 75 billion revenue
for AR by 2023 [5] and by 2019 AR for training, in particular,
will take place in 20% of large enterprise businesses [6]. AR
is the novel technology which superimposes virtual objects
upon the real world subjects or environment while enabling
real-time interactions [1]. In recent years, AR has captured
the research interests in many areas such as education and
training [2], [13], assembly and production operations [3],
[4]. As a result, the outcome of teaching and learning, skill
acquisition and development as well as user experience have
shown outstanding beneficial effects.
Gamification, on the other hand, is the term for adapting the
design elements which commonly characterize entertainment
games into other settings but gaming. While the academic
world is still debating on the consensus of definition and
scope, the benefits that gamification brings are undenialble.
It is not uncommon to say that games are addictive, yet
beyond entertainment purposes, they are believed to better
life in many aspects [9]. Gamification’s ultimate goal is to
simulate the fun elements that enhance the user experience,
improve worker productivity or advance student engagement.
Since gamification is often mistaken with the meaning of the
“serious game,” which is any full-fledged game that used for
other purposes exceeding pure entertainment, we limit the
work in this paper to the most widely accepted definition of
gamification [10]:
Fig. 1. The GAR design with gamification elements: points, progress bar and
“Gamification is the use of game design elements in non-
game contexts.
Since both AR and gamification already have their certain
contribution into the education field, in the context of training
especially, it is surprising that gamified AR systems have
not been popular for training in the production environment.
Accountable for this probably is the fine line between making
work fun and making fun of work [7]. Due to the nature of
productional work, the misuse of the gamified systems could
take away the user’s focus attention and result in damages or
even injuries. Therefore, here we attempt to form a gamified
AR application for an assembly training task following special
design requirements for a production environment. Our focus
is on the user engagement aspect because it is an important
factor contributes to the effectiveness of training.
Although the term “gamification” is relatively new, since
around 2003, its applications have already widespread across
many industrial as well as scholarly fields. Recently in the
Gamification 2020 report, Gartner predicted that gamification
in combination with emerging technologies will create a
significant impact on several fields including the design of
employee performance and customer engagement platform [8].
In this context, there are numerous examples of studies for
Proceedings of the Federated Conference on
Computer Science and Information Systems pp. 901–904
DOI: 10.15439/2019F136
ISSN 2300-5963 ACSIS, Vol. 18
IEEE Catalog Number: CFP1985N-ART c
2019, PTI 901
either AR training or gamified training, yet there was hardly
any work on the combination of those.
A recent survey of Seaborn et al. [14] provides a good
overview of gamification from a Human-Computer-Interaction
perspective in both theoretical and practical lights. The work
showed that gamification is primarily practiced in the domain
of education, e-learning especially. In the theoretical founda-
tions, there was a dynamic movement towards carving the
boundaries between gamification and other similar concepts.
The applied research, meanwhile, painted a positive-leaning
but mixed picture about the effectiveness of gamified systems.
Despite usual expectation, similar gamified designs under
different settings returned clashing result over user experience
along with performance. The reason was believed to be highly
context-specific requirements. Furthermore, learning about the
effects of gamification on the human is a complicated subject.
The overall effort toward this direction is still nascent.
While the gamified system was well accepted in business
contexts, it is not necessarily the case in production training,
left alone Augmented Reality training. K. Lee [13] showed that
AR for education and training innovation was leaning towards
the “serious game” pole while gamification was left outside
of the picture. According to Lee, AR games were particularly
interested in by both “educators and corporate venues.” A role-
playing game for teaching history [11], for example, proved
the benefit of enabling students for problem-solving, increas-
ing collaboration and exploration via the virtual identities.
However, whether we like it or not, production training is
different from traditional classroom training. When transform-
ing the operational work into a game, a serious game, there
will always be a risk of taking the focus away from the task at
hand. This is when gamification comes to play as integrating
gamification can provide the fun aspect while still keeping the
workers’ full attention on the operative job [12].
Probably the most well-known gamification in production
is a series of works from Korn et al. [15], [16], [17], [12].
The center of his works is to evaluate users’ acceptance of
gamification in modern production environments. Different
designs, “Circles & Bars” and “Pyramid,” were proposed [12].
Both designs were used to visualize work steps as well as their
sequences. Color-coded from dark green to yellow, orange and
read is employed to indicate user specific time progression.
Later on, they were projected into users’ working space as
an assistive application for impaired individuals. The result
indicated a good acceptance level for gamification designs
and the “Pyramid” approach was favorable in general. While
the study showed a promising outcome, it focused on user
acceptance and did not measure the quantitative factor of
gamification on task completion time and error rates.
In this section, we present the implementation of the
application under study. A process of replacing the battery
for a robot arm was implemented based on the instruction
manual of the Mitsubishi Industrial Robot RV-2F Series [18].
The application ran on the Microsoft HoloLens [19]. Two
Fig. 2. The NGAR design with no gamification elements. Only text instruction
was provided.
prototypes were made, one with the gamification design and
the other without. The designs were named Gamification AR
(GAR) and Non-Gamification AR (NGAR) according to their
characteristics. Due to Microsoft HoloLens small field of
view, around 35 degrees, here we provide the user interfaces
captured from Unity Editor to showcase the whole scene setup.
Figure 1 and Figure 2 illustrate the GAR and NGAR design
A. The application
The process for changing the battery was identically built
for both prototypes. There were 21 actions made up 10
steps. Disassembling the cover of the battery compartment,
for example, included two steps of removing the screws and
removing the cover. While removing each of the screws was
counted as an action.
For navigating the process, we augmented the instruction
text for each step as a head-up display which was always
facing the user at the top right corner of the user view. An
instruction manager was used to control the flow of text
visualization. The requirement from the instruction manual
specified that the steps of the process had to be performed
in a fixed order that’s why only one instruction was displayed
at a time. The next instruction triggered when the user carried
the current step correctly.
Two main interaction types were used to simulate different
interactions. Air tap [19] was used for interacting with static
objects (e.g. pressing a button) while we utilized drag and drop
for assembling actions (e.g. removing the screw). Similar to
the real working space, disassembled objects were designed to
be placed at a specific location. For instance, the screws needed
to be placed inside a designated tray instead of dropped on the
To simulate a sense of reality, sounds such as robot arm
were running or turned off were used.
B. Gamification Design
The game design elements were implemented only for the
GAR version. It allows to isolate and analyze the effect
of gamified system on the user. This could be reflected by
comparing the outcome of the two experiments.
As a result of Korn’s investigation [12], gamification in the
production environment has its own specific requirements. To
avoid resistance from users or the potential of taking away
their main focuses, we followed the identified requirements
in designing gamified application for production settings.
First, “keep the visualization of gamification simple.” This
focuses mainly on avoiding animation, moving elements and
using complex graphical structures. The second and third
requirements come together as “avoid explicit interaction with
gamification elements” and “support implicit interaction with
gamification elements.” For that matter, in our designs we did
not ask for any user’s effort to direct input or reach out to the
gamified items.
1) Point System: The point system was built based on users’
actions. There was a maximum of 21 points according to 21
actions. Points were rewarded to the user when the action was
done. As the first attempt to study the effect of gamification
design on user engagement, we did not implement a complex
point system with losing points or rewarding extra points at
this stage.
2) Progress Bar: While the points were based on actions,
progress bar visualized the steps. As stated as one of the
requirements, the user interface was intentionally kept simple
with only one color. Additional text was in place for indicating
the percentage.
3) Signposting: Signposting aims to direct the user in the
right direction. While users without background knowledge
could be confused with the mechanical part names (e.g. Con-
troller box), signposting highlighted the part corresponding to
the currently displayed instruction. It provided the “just-in-
time” hints for the trainees, especially the totally beginner one.
The experiment was conducted to investigate how gamifica-
tion in AR training impacts user engagement and performance.
The studies for both conditions (GAR and NGAR) took place
in the same room at our research laboratory. To avoid the
learning effect, we employed the between-group design in
which each participant randomly exposed to only one design,
either GAR or NGAR.
Due to the fact that Microsoft HoloLens requires specific
hand gestures for interaction, the participants were asked if
they have experience with this device. In the case of none,
the participant used the default HoloLens “Learn gesture”
application. This was especially important because the main
task could not be carried on without this step. Before the
experiment, regardless of the HoloLens experience, we re-
peated the main information about the interactive gestures to
all participants.
Once the participants were confident interacting with the
device, the main experiment task proceeded. When the user
hit the “Start” button at the first scene of the application, the
timer for measuring task completion time was started until the
last step completed.
As we focused on the user engagement we used a post-
study questionnaire with the refined User Engagement Scale
(UES) [20]. UES is a five-point rating scale: strongly disagree,
disagree, neither disagree nor agree, agree and strongly agree,
respectively from 1 to 5 point. Given the task was not
complicated, the level of fatigue after that was expected not
to be high so that we decided to use the UES long form (UES
- LF). The UES - LF consists of 30 items covering 4 factors:
1) FA: Focused Attention
2) PU: Perceived Usability
3) AE: Aesthetic Appeal
4) RW: Reward Factor
As constructed in the guide to use of UES, all items were
randomized and the indicators (e.g. AE.1) were not visible to
the users.
Most of the participants reported having little or none expe-
rience with AR technology, in particular, Microsoft HoloLens,
before this experiment. So, a potential novelty effect when
initially establishing interaction with new technology might
influence the research result. The test population was 22 par-
ticipants with 11 regarding each condition. Participants ages
vary from 18 to 34 years old, 15 male and 7 female subjects.
Although some unease and uncertainty were expressed at the
beginning, all participants were more certain after the learning
gesture phase.
Figure 3 displays that the GAR design was rated better
in all sub categories. In general, it was clearly preferred to
the NGAR approach. The overall Engagement score was 15.2
(SD=1.8) in GAR and 13.3 (SD=3.5) in NGAR. However, this
did not make up a statistically significant difference between
the two groups. Table I provides the results in more detail,
looking at the average score, standard deviation and also the
result of a t-test for both the overall engagement score and its
The standard deviation in the overall user engagement
score was much lower in the GAR design (SD=1.8), versus
SD=3.5 in NGAR, which shows that the GAR subjects more
homogenously perceived the result throughout the group. This
tendency, lower standard deviation, remained true for all four
subfactors in the GAR design as shown in Figure 3. On the
other side, the opinions of NGAR subjects seem to be more
Looking at the training performance, the difference regard-
ing average task completion time (in seconds) between the two
study conditions is statistically significant. The t-test resulted
in p < 0.032. The average time was 306.9 (SD=123.2) and
439.5 (SD=134.4) for GAR and NGAR groups respectively.
This positive outcome probably directly influenced by the
signposting design element.
As a preliminary result, this work demonstrates the potential
of gamified AR training for assembly tasks in improving user
engagement and performance. Nevertheless, there is a need for
Fig. 3. User Engagement Score as a bar chart with indicated standard
Factor Mean Score (SD) p value
Focused Attention 3.5 (0.6) 3.2 (0.8) 0.418
not significant
Perceived Usability 3.7 (0.5) 3.4 (0.7) 0.281
not significant
Aesthetic Appeal 3.9 (0.7) 3.3 (1.2) 0.162
not significant
Reward Factor 4.0 (0.5) 3.4 (1.2) 0.128
not significant
Overall Score 15.2 (1.8) 13.3 (3.5) 0.153
not significant
further investigation focusing on both short-term and long-
term training effectiveness. A consideration over skills and
knowledge acquisition should be taken into account. To serve
this goal more complex tasks should be implemented with
a higher level of gamification, different training levels and
challenges design for individual specific demands for example.
As we focused on the improvement of user engagement
in gamified AR training, we did not take in to account the
isolated effect of how each game design elements affects the
user. As mentioned in the Related Work, gamification design is
highly context-specific so that the next important step will be
a qualitative study on how the users perceive different design
elements and their impacts.
The use of gamification in combination with AR for pro-
duction training is still new and its potential needs further
exploration. In this paper, we developed a gamified training
for an assembly task in AR setting and studied its effects on
user engagement.
The result showed that the users displayed a higher level of
engagement as well as better performance with the support of
gamified AR training. The statistical analysis, though, did not
indicate a significant difference.
While the implementation of gamification may not yet
fully integrate into the training process, this work certainly
contributes to the existing knowledge body of gamified AR
training for production domain. This research area also needs
a greater amount of works to identify its benefits alongside
with how to tackle its challenges.
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The implementation of Industry 4.0 in the enterprise forces increased digitization, production flexibility, improvement of employees’ competences and the integration of employees and IT systems. For this purpose, cutting-edge IT systems and solutions such as Virtual, Augmented and Mixed Reality (VR/AR/MR) are increasingly used. These technologies can be used, in training processes of ma-chines and equipment operating procedures. The paper is a case study on the possibility of using MR applications in training in the use of electrical devices (ARS 2 Pro switch disconnector). The aim of the work is to compare MR and standard training and evaluate their effectiveness in this type of training. The paper briefly describes developed applications and preliminary test-results.A group of 20 people in the age group 20 to 40. The participants were divided in-to 2 subgroups in order to properly analyze the effectiveness of individual training tools.KeywordsMixed realityIndustrial trainingOperating procedures
Virtual, Augmented, and Mixed Reality (VR/AR/MR) or Extended Reality (XR) applications may be used as an innovative educational tool. Devices such as Oculus Quest 2 offer the possibility of using passthrough view and hand tracking which enables user to interact with virtual environment and see his surroundings. These functions enable the preparation of training applications, in which the user is able to simultaneously see his workplace and the number of generated job instructions or practice work-related activities without losing contact with the environment. This opens up a number of opportunities related to broadly understood education. The article briefly discusses the developed concept that allows for training in XR, in which user interactions with virtual elements are as close to the real ones as possible. The development of interactions using hand tracking and passthrough are described.KeywordsMixed realityEducation processObject manipulation
Background In mega-biodiverse environments, where different species are more likely to be heard than seen, species monitoring is generally performed using bioacoustics methodologies. Furthermore, since bird vocalizations are reasonable estimators of biodiversity, their monitoring is of great importance in the formulation of conservation policies. However, birdsong recognition is an arduous task that requires dedicated training in order to achieve mastery, which is costly in terms of time and money due to the lack of accessibility of relevant information in field trips or even specialized databases. Immersive technology based on virtual reality (VR) and spatial audio may improve species monitoring by enhancing information accessibility, interaction, and user engagement. Methods This study used spatial audio, a Bluetooth controller, and a head-mounted display (HMD) to conduct an immersive training experience in VR. Participants moved inside a virtual world using a Bluetooth controller, while their task was to recognize targeted birdsongs. We measured the accuracy of recognition and user engagement according to the User Engagement Scale. Results The experimental results revealed significantly higher engagement and accuracy for participants in the VR-based training system than in a traditional computer-based training system. All four dimensions of the user engagement scale received high ratings from the participants, suggesting that VR-based training provides a motivating and attractive environment for learning demanding tasks through appropriate design, exploiting the sensory system, and virtual reality interactivity. Conclusions The accuracy and engagement of the VR-based training system were significantly high when tested against traditional training. Future research will focus on developing a variety of realistic ecosystems and their associated birds to increase the information on newer bird species within the training system. Finally, the proposed VR-based training system must be tested with additional participants and for a longer duration to measure information recall and recognition mastery among users.
This exploratory study examines the white-collar worker perception of the three most common game elements in learning Level, Points and Badges applied in online training. Through surveys and interviews, the study reveals that the perception of the gamified course design was engaging. The game elements Levels and Badges were considered positive, while Points was viewed as indifferent. The study also detects that respondents in both the surveys and interviews had not noticed parts of the gamification design, making them negative towards the gamified course due to lack of coherence in the design. The authors of the paper suggest that further studies should address multimodal feedback, juiciness, and gamification to disclose which type of feedback is paramount in various gamified situations.
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User engagement (UE) and its measurement have been of increasing interest in human-computer interaction (HCI). The User Engagement Scale (UES) is one tool developed to measure UE, and has been used in a variety of digital domains. The original UES consisted of 31-items and purported to measure six dimensions of engagement: aesthetic appeal, focused attention, novelty, perceived usability, felt involvement, and endurability. A recent synthesis of the literature questioned the original six-factors. Further, the ways in which the UES has been implemented in studies suggests there may be a need for a briefer version of the questionnaire and more effective documentation to guide its use and analysis. This research investigated and verified a four-factor structure of the UES and proposed a Short Form (SF). We employed contemporary statistical tools that were unavailable during the UES’ development to re-analyze the original data, consisting of 427 and 779 valid responses across two studies, and examined new data (N=344) gathered as part of a three-year digital library project. In this paper we detail our analyses, present a revised long and short form (SF) version of the UES, and offer guidance for researchers interested in adopting the UES and UES-SF in their own studies.
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Gamification is an ever more popular method to increase motivation and user experience in real-world settings. It is widely used in the areas of marketing, health and education. However, in production environments, it is a new concept. To be accepted in the industrial domain, it has to be seamlessly integrated in the regular work processes. In this work we make the following contributions to the field of gamification in production: (1) we analyze the state of the art and introduce domain-specific requirements; (2) we present two implementations gamifying production based on alternative design approaches; (3) these are evaluated in a sheltered work organization. The comparative study focuses acceptance, motivation and perceived happiness. The results reveal that a pyramid design showing each work process as a step on the way towards a cup at the top is strongly preferred to a more abstract approach where the processes are represented by a single circle and two bars.
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Using video game elements to improve user experience and user engagement in non-game applications is called "gamification ". This method of enriching human-computer interaction has been applied successfully in education, health and general business processes. However, it has not been established in industrial production so far. After discussing the requirements specific for the production domain we present two workplaces augmented with gamification. Both implementations are based on a common framework for context-aware assistive systems but exemplify different approaches: the visualization of work performance is complex in System 1 and simple in System 2. Based on two studies in sheltered work environments with impaired workers, we analyze and compare the systems' effects on work and on workers. We show that gamification leads to a speed-accuracy-tradeoff if no quality-related feedback is provided. Another finding is that there is a highly significant raise in acceptance if a straightforward visualization approach for gamification is used.
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Context-aware assistive systems (CAAS) have become ubiquitous in cars or smartphones but not in industrial work contexts: while there are systems controlling work results, context-specific assistance during the processes is hardly offered. As a result production workers still have to rely on their skills and expertise. While un-impaired workers may cope well with this situation, elderly or impaired persons in production environments need context-sensitive assistance. The contribution of the research presented here is three-fold: (1) We provide a framework for context-aware assistive systems in production environments. These systems are based on motion recognition and use projection and elements from game design (gamification) to augment work. (2) Based on this framework we describe a prototype with respect to both the physical and the software implementation. (3) We present the results of a study with impaired workers and quantifying the effects of the augmentations on work speed and quality.
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Gamification is about understanding and influencing human behaviours that organizations want to encourage amongst their workforce or customers. Gamification seeks to take enjoyable aspects of games – fun, play and challenge – and apply them to real-world business processes. Analysts are predicting massive growth of gamification over the next few years, but is there any substance to the benefits being touted? This article takes a critical look at the potential of gamification as a business change agent that can deliver a more motivated and engaged workforce.
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Gamification has drawn the attention of academics, practitioners and business professionals in domains as diverse as education, information studies, human-computer interaction, and health. As yet, the term remains mired in diverse meanings and contradictory uses, while the concept faces division on its academic worth, underdeveloped theoretical foundations, and a dearth of standardized guidelines for application. Despite widespread commentary on its merits and shortcomings, little empirical work has sought to validate gamification as a meaningful concept and provide evidence of its effectiveness as a tool for motivating and engaging users in non-entertainment contexts. Moreover, no work to date has surveyed gamification as a field of study from a human-computer studies perspective. In this paper, we present a systematic survey on the use of gamification in published theoretical reviews and research papers involving interactive systems and human participants. We outline current theoretical understandings of gamification and draw comparisons to related approaches, including alternate reality games (ARGs), games with a purpose (GWAPs), and gameful design. We present a multidisciplinary review of gamification in action, focusing on empirical findings related to purpose and context, design of systems, approaches and techniques, and user impact. Findings from the survey show that a standard conceptualization of gamification is emerging against a growing backdrop of empirical participants-based research. However, definitional subjectivity, diverse or unstated theoretical foundations, incongruities among empirical findings, and inadequate experimental design remain matters of concern. We discuss how gamification may to be more usefully presented as a subset of a larger effort to improve the user experience of interactive systems through gameful design. We end by suggesting points of departure for continued empirical investigations of gamified practice and its effects.
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There are many different ways for people to be educated and trained with regard to specific information and skills they need. These methods include classroom lectures with textbooks, computers, handheld devices, and other electronic appliances. The choice of learning innovation is dependent on an individual’s access to various technologies and the infrastructure environment of a person’s surrounding. In a rapidly changing society where there is a great deal of available information and knowledge, adopting and applying information at the right time and right place is needed to main efficiency in both school and business settings. Augmented Reality (AR) is one technology that dramatically shifts the location and timing of education and training. This literature review research describes Augmented Reality (AR), how it applies to education and training, and the potential impact on the future of education.
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This paper introduces an approach for implementing motivating mechanics from game design to production environments by integrating them in a new kind of computer-based assistive system. This process can be called “gamification”. By using motion recognition, the work processes becomes transparent and can be visualized in real-time. This allows representing them as bricks in a “production game” which resembles the classic game Tetris. The aim is to achieve and sustain a mental state called “flow” resulting in increased motivation and better performance. Although the approach presented here primarily focuses on elderly and impaired workers, the enhanced assistive system or “wizard” can principally enrich work in every production environment.
Augmented reality (AR) is a novel human–machine interaction that overlays virtual computer-generated information on a real world environment. It has found good potential applications in many fields, such as military training, surgery, entertainment, maintenance, assembly, product design and other manufacturing operations in the last ten years. This paper provides a comprehensive survey of developed and demonstrated AR applications in manufacturing activities. The intention of this survey is to provide researchers, students, and engineers, who use or plan to use AR as a tool in manufacturing research, a useful insight on the state-of-the-art AR applications and developments.