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Although Augmented Reality (AR) technology has entered many market and knowledge domains such as games and leisure activities, it remains rather limited in digital heritage. After studying the potentiality of using modern AR elements in a museum context, this paper proposes the use of additional game and educational elements in the core AR application in order to enhance the overall on-the-spot museum visitor’s experience. An agile AR application design methodology was followed by taking into account the needs of small-to-medium sized real-world museums. Moreover, a heuristic evaluation protocol was applied by a group of experts in order to test the proof-of-concept AR application, in which some novel elements were proposed such as the AR quiz game. The main findings indicate that enhanced AR experiences in museum settings can make a nice fit with the user environment, physical and perceptual abilities, known metaphors, and user position and motion in 3D space. Moreover, AR services can be provided under a minimum distraction and physical effort. As a conclusion, AR technologies are mature enough to be standardized for museum usage, while the audience seems to be ready to take advantage of the related enhanced museum experiences to maximize both user satisfaction and learning outcomes.
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applied
sciences
Article
A Gamified Augmented Reality Application for Digital
Heritage and Tourism
Ioannis Paliokas 1, *, Athanasios T. Patenidis 1, Eirini E. Mitsopoulou 1, Christina Tsita 1,
George Pehlivanides 2, Elli Karyati 2, Spyros Tsafaras 2, Evangelos A. Stathopoulos 1,
Alexandros Kokkalas 1, Sotiris Diplaris 1, Georgios Meditskos 1, Stefanos Vrochidis 1,
Eleana Tasiopoulou 3, Christodoulos Riggas 3, Konstantinos Votis 1, Ioannis Kompatsiaris 1
and Dimitrios Tzovaras 1
1Information Technologies Institute, Centre for Research & Technology Hellas, 57001 Thermi, Greece;
apatenidis@iti.gr (A.T.P.); emitsopou@iti.gr (E.E.M.); tsita@iti.gr (C.T.); estathop@iti.gr (E.A.S.);
akokkalas@iti.gr (A.K.); diplaris@iti.gr (S.D.); gmeditsk@iti.gr (G.M.); stefanos@iti.gr (S.V.);
kvotis@iti.gr (K.V.); ikom@iti.gr (I.K.); dimitrios.tzovaras@iti.gr (D.T.)
2Interaction Department, Tetragon S.A., 54641 Thessaloniki, Greece; interaction@tetragon.gr (G.P.);
info@tetragon.gr (E.K.); expo@tetragon.gr (S.T.)
3Research and Educational Programs Department, Piraeus Bank Group Cultural Foundation, 10558 Athens,
Greece; TasiopoulouE@piraeusbank.gr (E.T.); riggasch@piraeusbank.gr (C.R.)
*Correspondence: ipaliokas@iti.gr; Tel.: +30-2311-25776
Received: 19 October 2020; Accepted: 4 November 2020; Published: 6 November 2020


Featured Application: An Augmented Reality application designed to allow on-the-spot museum
visitors to navigate and view exhibitions using their own mobile devices by enjoying user
experience multipliers like interactive content and mixed reality quiz games.
Abstract:
Although Augmented Reality (AR) technology has entered many market and knowledge
domains such as games and leisure activities, it remains rather limited in digital heritage.
After studying the potentiality of using modern AR elements in a museum context, this paper
proposes the use of additional game and educational elements in the core AR application in order
to enhance the overall on-the-spot museum visitor’s experience. An agile AR application design
methodology was followed by taking into account the needs of small-to-medium sized real-world
museums. Moreover, a heuristic evaluation protocol was applied by a group of experts in order to test
the proof-of-concept AR application, in which some novel elements were proposed such as the AR
quiz game. The main findings indicate that enhanced AR experiences in museum settings can make a
nice fit with the user environment, physical and perceptual abilities, known metaphors, and user
position and motion in 3D space. Moreover, AR services can be provided under a minimum distraction
and physical eort. As a conclusion, AR technologies are mature enough to be standardized for
museum usage, while the audience seems to be ready to take advantage of the related enhanced
museum experiences to maximize both user satisfaction and learning outcomes.
Keywords: augmented reality; games; digital heritage; museums; usability evaluation
1. Introduction
In today’s digital cultural landscapes, people are increasingly dependent on technological tools to
access digital cultural content such as musical, pictorial, and multimedia expressions that surround
them [
1
]. In a broader sense, the digital transformation of culture has led us to the era of Smart Culture in
which Information and Communication Technologies (ICT) can help citizens to benefit from improved
cultural accessibility and inclusion [
2
]. Moreover, Cultural Technologies (CT)—which resulted from the
Appl. Sci. 2020,10, 7868; doi:10.3390/app10217868 www.mdpi.com/journal/applsci
Appl. Sci. 2020,10, 7868 2 of 18
integration of ICT into heritage organizations—have led to a change in the structure of the organizations
and have aected the management of collections and the visitor’s experience [3].
CT can hardly be defined, as they include a wide range of technologies used to support the digital
transformation of culture and the operation of memory institutions (museums, galleries, libraries,
etc.). Such technologies may include the Internet of Things (IoT), which may help museums oer
personalized services and thus complete their mission by building a better museum of education,
research, and appreciation of the heritage by wider audiences [4,5].
Augmented Reality (AR) is featured as an important part of modern CT and—according to
Uricchio [
6
]—it has become the “next big thing”, since most smartphones today have the necessary
hardware and software characteristics to reproduce AR experiences (for free), and this growth has been
propelled by the advertising industry. In addition, from a user-centered point of view, AR exposes
visitors to an alternative interaction style, which can trigger curiosity and interest and overall can give
a sense of accomplishment [7].
The main issue here is that although the use of AR has already penetrated certain market domains
such as leisure and games (e.g., Pokemon Go (https://pokemongolive.com/)), it remains rather limited
in the realm of other domains such as heritage education [
8
]. On the other hand, museums and cultural
organizations are willing to experiment using new methods of democratizing culture, such as the use of
mobile devices during an in-site visit, in order to reach their audiences and attract their attention [
9
,
10
].
A straightforward way to achieve these goals is to use AR for annotating museum scenes and providing
extra information about collections or individual artefacts. Advances may include game elements
introduced into the annotated scenes to oer gamified user experiences such as explorative navigation,
playful interaction with museum artefacts, fantasy tours in ancient times, and more [
11
]. According to
a Europe-wide study of Luna et al. [
8
] on this topic, it seems that most AR digital heritage proposals
reconstruct spaces and buildings in outdoors applications, and only a limited number of use cases
handle objects in indoors applications (excluding simple audio tour apps using mobile devices).
In the light of the new findings and recent technological advances, this study aims to introduce
AR technologies into museums and galleries as a User eXperience (UX) amplifier. Apart from covering
typical indoors museum AR applications that track a single object (2D or 3D artefact) and augment
virtual objects and content on the top of the existing one, this paper will present a novel AR quiz game
used to motivate users to revisit exhibitions. The gamified app allows on-the-spot museum visitors to
navigate themselves in exhibitions using their own devices, to interact with the museum’s educational
media in a dynamic and fun way, spend more time on the exhibitions, gain new knowledge from the
museum visit, and pay attention to details not seen in a first pass. Moreover, this study will describe
how AR markers were introduced in museum context in an aesthetically accepted way without any
reduction in 3D object detection stability and overall user experience quality.
After a short explanation of the methods used for the design and development of the
proof-of-concept application, it was evaluated with the participation of an expert team following a
heuristic evaluation protocol especially developed for AR applications. Evaluation results discovered
possible violations of the heuristic criteria, estimated the level of the violation’s severity, and finally
provided recommendations for fixes and further development, which were included in the final
version. The outcomes are expected to open new possibilities for museum visitor’s navigation,
content visualization, and playful and educational eective interaction with museum artefacts.
1.1. Cultural Heritage and Learning
Museums are places to share not only access to artefacts and their related stories
(museum narrations),
but also memories, experiences, and open questions. They develop new
knowledge by museological research, and they support the didactic transformation of knowledge
by developing and sharing documentation used inside and outside the museum. For example,
during school visits, it is quite common that teachers make first an introduction to the objectives of
a museum visit and outline the exhibitions of interest, and after the museum visit, they propose an
Appl. Sci. 2020,10, 7868 3 of 18
assignment or a structured discussion about what students have learned during the museum visit.
Moreover, museums organize activities to oer educational proposals for families and complement
formal school programs [12].
Cultural learning in museum settings is of a high environmental validity, meaning that the
museological narration and documentation is placed in a wider context of the learner
0
s environment,
thus enabling people to appreciate the museum contents, participate experiencing emotional
involvement, and create the feeling of ownership. Colizzi et al. [
13
] outline this inherent educational
nature of cultural heritage and support that it is well suited to school learning, thanks to its nature
and ability to support multidisciplinary learning. Following the same philosophy, Hourdakis and
Ieronimakis [
14
] examine the role of the museum regarding an individual’s education and see museums
as catalysts for dialogue and learning. Cultural heritage and learning are linked in multiple ways,
and this should come as no surprise as art and history educators in museums and schools share
common professional backgrounds and content fields, although they operate in dierent environments
and organizational contexts [15].
1.2. The Use of Augmented Reality in Museum Settings
Museums use a wide variety of demonstration and learning techniques based on the prior
experience visitors may have by using technology. For example, infrastructures used in smart cities
such as the Internet of Things (IoT) could be proposed in digital heritage leading to the Internet of
Cultural Things (IoCT) concept. This can be perceived as evidence that interruptive technologies play
a major role in transforming culture into ambient culture, as seen in a literature review conducted by
McKenna [16].
Furthermore, when navigation and exploration are combined with game elements, the final
outcome—from a user experience and engagement perspective—becomes really interesting.
Sigouros [
17
] considers that ICT tools are useful in historical literacy, as long as they carry on
supporting content to limit the time needed to find sources of information, provide direct and clear
feedback to the user, but also allow teachers to provide their students with external motivation for
learning, which in turn creates feelings of inner satisfaction.
Recent advances in mobile devices such as high screen resolutions, large mobile networking
bandwidth, and increasing processing power enabled the Bring Your Own Device principle [
18
] to be
the dominant information-sharing model in a variety of market domains, including Digital Heritage.
This trend reduced the cost of service distribution, but it also released the need to share specialized
hardware. For example, Saputro et al. [
19
] proposed the use of signal wireless sensor networks to help
with the position and identification problem inside museums using the triangulation method and
the Received Signal Strength Indicator (RSSI). Such solutions may give promising results, such as the
distributed self-gesture and artwork recognition system of Baraldi et al. [
20
], which uses wearable
devices (named by the authors as “ego-vision embedded devices”) but still requires the use of special
equipment and user education before use. In another example, wearable devices such as Smart Glasses
or AR Glasses are a kind of special equipment needed to introduce AR in museums [
21
]. The need
for specialized hardware is removed when talking about mobile AR, in which visitors use their own
device for position/orientation sensing and projection.
Practically, what AR does in a museum context is to combine real-time computer graphics and
high-quality museological content with Human–Computer Interaction (HCI) modalities to enrich
experiences after superimposing artificial objects on the real-world view of the museum. Thus,
the playful experiences turn into learning experiences, since the digital contents have taken the form of
a pedagogical processing. A few examples are the mobile guide to museum settings proposed by Damala
et al. [
22
] and the LifePlus project, which proposed a 3D reconstruction of ancient frescos enhanced with
animated avatars (artificial life) to oer dramaturgical narration in an immersive AR environment [
23
].
A key issue in almost all AR apps for digital heritage is the human activity monitoring, which allows the
application to adapt to the user’s intentions and their physical movement in the 3D space. This sensing
Appl. Sci. 2020,10, 7868 4 of 18
is usually performed through a marker or a marker-less technique to estimate where the user stands
and looks, and to display the right virtual objects on the screen. Those superimposed objects include
3D representations of museum artefacts and additional information [
24
], or virtual objects that are part
of a game concept [
25
]. Moreover, AR apps used for reconstructing cultural heritage for open spaces
become increasingly common [
26
], such as those used in archaeology. In marker-less techniques, AR
apps reveal features that become available from the physical objects in a scene (Kolivand et al., 2018).
Alternatively, AR applications in museum settings may use IoT devices such as beacons [27] to sense
the standing point of the users, but this may not be enough to obtain all the data required to accurately
superimpose virtual objects on the mixed scene.
Regarding contents, mobile AR applications in heritage contexts include museological narrations
of past or present times [
28
], 3D avatars to guide visitors through the collections of the museum [
29
],
interactive painting and recoloring of museum artefacts [
30
], and even presentations of spiritual
heritage elements, for example those related to the life of important personalities [
31
]. Quite often,
learning activities hosted in museums are followed by a short assessment (e.g., self-guided quiz).
Those quizzes are delivered in a paper-and-pencil form, or they can be interactive quiz games, such as
in Quakequiz of Prange et al. [
32
]. In the majority of cases, there is no use of AR technology during
this evaluation phase (quiz time).
1.3. Underlying Motivation
This paper will propose an AR quiz game designed to increase the time museum visitors interact
with artefacts and oer a playful way of navigation in the 3D space and as well an alternative
method of gained knowledge assessment. In this study, we accept that museum exhibitions have
a native educational purpose, and in this regard, we identify three main reasons for using modern
AR technologies:
Personalization: It can be said that from an educational point of view, what AR technology has
to oer is mainly personalization and visualization. Museum visitors, as potential learners of new
knowledge, can have a certain level of control over the learning speed or rhythm. Having museum
visitors with a wide range of ages, cultural and knowledge backgrounds, it becomes easily understood
why adjusting the pace of learning into one
0
s own needs could be so important. Interacting with the
educational content of a museum in your own device and under your own rhythm of interaction is
a very good example of learning speed adjustment to personal needs and preferences. Moreover,
visitors can follow their own navigation route through the information space and pay attention to
details of the museum artefacts they enjoy the most. AR technologies give the opportunity to make
such adjustments to the needs of individuals.
Motivation: AR can maximize the learner’s motivation, especially for young learners who love
storytelling, play leisure AR/VR games quite often, and can easily master mobile devices. From a
constructivist approach, AR museum games can be understood not only as mediums to capture and
maintain the attention of the audience but also as a way to reconstruct the meaning of the artefacts
through animated storytelling inserted into the AR scenarios. This museological storytelling is working
closely with visitor’s emotions and fantasy to maximize user engagement and interest. Moreover,
certain game elements such as competition, challenges, conflict, control, and awards for achieving goals
can work as “experience amplifiers” for all ages of museum visitors and prevent boring museum visits.
Learning Eciency: Perceiving learning speed as one of the success criteria for technology-based
educational activities, we can accept that learning in AR museum settings (e.g., using virtual
reconstructions of artefacts, possibly examining alternative conditions, taking risks in a safe
environment, etc.) can help master the skills and knowledge faster and/or deeper than in a classroom
or in other forms of typical education. The better learning curve observed when AR applications are
being used has frequently been reported in the literature [33].
Based on all of the above, the underlying motivation of this work is to explore the expected
educational benefits and models of user experience enhancement caused by introducing AR navigation
Appl. Sci. 2020,10, 7868 5 of 18
and games in museum settings, mainly in indoor exhibitions. The main objective is to achieve a
fair balance between leisure and usefulness without retreats to other qualities such as usability and
technology acceptance. The following sections present the e-Tracer AR application, which was designed
according to the principles previously discussed.
2. Materials and Methods
2.1. The e-Tracer AR Application in a Nutcel
The e-Tracer AR application is an educational and guide application for museums and galleries.
It was designed to allow on-the-spot museum visitors to navigate themselves in the museum exhibitions
using their own devices (mainly smartphones and tablets). Currently, the e-Tracer AR application
has been optimized for the permanent collections of the Silversmithing museum (http://www.piop.
gr/en/diktuo-mouseiwn/Mouseio-Argyrotexnias/to-mouseio.aspx), located in the castle of Ioannina,
Greece. The digital contents of the app were developed in compliance with the main objectives of the
permanent museum collection, which is to preserve the technical knowledge of epirote silversmithing
artists and to disseminate information about its tradition to the wider public.
The AR functionality starts by sensing a museum artefact of interest, which is being seen through
the mobile’s built-in camera. The marker-based object detection mechanism triggers the projection
of additional information (short description) related to this object (Figure 1), or it allows a virtual
projection of animated 3D objects when available. There is an underlying multilingual support system,
and currently, the information and educational content are provided to visitors in the English and
Greek languages. Exhibitions in the Ioannina Silversmithing museum are mostly static and thus, in a
hand-held AR setting, the object projection is expected to be performed in standard positions in the
physical museum settings and in view of the visitor’s distance to the object. Our solution has been
technically tested for working at a distance up to 1.5 m from the artefact (Figure 2).
Appl. Sci. 2020, 10, x FOR PEER REVIEW 5 of 18
usability and technology acceptance. The following sections present the e-Tracer AR application,
which was designed according to the principles previously discussed.
2. Materials and Methods
2.1. The e-Tracer AR Application in a Nutcel
The e-Tracer AR application is an educational and guide application for museums and galleries.
It was designed to allow on-the-spot museum visitors to navigate themselves in the museum
exhibitions using their own devices (mainly smartphones and tablets). Currently, the e-Tracer AR
application has been optimized for the permanent collections of the Silversmithing museum
(http://www.piop.gr/en/diktuo-mouseiwn/Mouseio-Argyrotexnias/to-mouseio.aspx), located in the
castle of Ioannina, Greece. The digital contents of the app were developed in compliance with the
main objectives of the permanent museum collection, which is to preserve the technical knowledge
of epirote silversmithing artists and to disseminate information about its tradition to the wider public.
The AR functionality starts by sensing a museum artefact of interest, which is being seen through
the mobile’s built-in camera. The marker-based object detection mechanism triggers the projection of
additional information (short description) related to this object (Figure 1), or it allows a virtual
projection of animated 3D objects when available. There is an underlying multilingual support
system, and currently, the information and educational content are provided to visitors in the English
and Greek languages. Exhibitions in the Ioannina Silversmithing museum are mostly static and thus,
in a hand-held AR setting, the object projection is expected to be performed in standard positions in
the physical museum settings and in view of the visitor’s distance to the object. Our solution has been
technically tested for working at a distance up to 1.5 m from the artefact (Figure 2).
Figure 1. Screenshot of the e-Tracer Augmented Reality (AR) user interface (user’s view).
Figure 2. Physical setting of the augmented object projection (observer’s view).
Figure 1. Screenshot of the e-Tracer Augmented Reality (AR) user interface (user’s view).
Appl. Sci. 2020, 10, x FOR PEER REVIEW 5 of 18
usability and technology acceptance. The following sections present the e-Tracer AR application,
which was designed according to the principles previously discussed.
2. Materials and Methods
2.1. The e-Tracer AR Application in a Nutcel
The e-Tracer AR application is an educational and guide application for museums and galleries.
It was designed to allow on-the-spot museum visitors to navigate themselves in the museum
exhibitions using their own devices (mainly smartphones and tablets). Currently, the e-Tracer AR
application has been optimized for the permanent collections of the Silversmithing museum
(http://www.piop.gr/en/diktuo-mouseiwn/Mouseio-Argyrotexnias/to-mouseio.aspx), located in the
castle of Ioannina, Greece. The digital contents of the app were developed in compliance with the
main objectives of the permanent museum collection, which is to preserve the technical knowledge
of epirote silversmithing artists and to disseminate information about its tradition to the wider public.
The AR functionality starts by sensing a museum artefact of interest, which is being seen through
the mobile’s built-in camera. The marker-based object detection mechanism triggers the projection of
additional information (short description) related to this object (Figure 1), or it allows a virtual
projection of animated 3D objects when available. There is an underlying multilingual support
system, and currently, the information and educational content are provided to visitors in the English
and Greek languages. Exhibitions in the Ioannina Silversmithing museum are mostly static and thus,
in a hand-held AR setting, the object projection is expected to be performed in standard positions in
the physical museum settings and in view of the visitor’s distance to the object. Our solution has been
technically tested for working at a distance up to 1.5 m from the artefact (Figure 2).
Figure 1. Screenshot of the e-Tracer Augmented Reality (AR) user interface (user’s view).
Figure 2. Physical setting of the augmented object projection (observer’s view).
Figure 2. Physical setting of the augmented object projection (observer’s view).
Appl. Sci. 2020,10, 7868 6 of 18
What was described up to now covers mostly the typical functionality expected from an AR
application in museum settings. Considering similar applications, the use of QR codes appears to be
the dominant way of delivering information about artefacts. For example,
Pérez-Sanagustín et al. [34]
developed two ways: one using a visitor ’s smartphone and QR codes and a second one using a
screen located next to the exhibits, but finally, they chose the first one after measuring the eect
QR codes had on visitors. QR codes with image recognition are also being used as the main object
identification method in commercial AR applications such as Layar (https://www.layar.com) and
Gamar (https://www.gamar.com). Thus, e-Tracer advocates the use of QR codes for indoor or outdoor
use, but at the same time, it takes advantage of the aesthetically superior illustrations of artefacts,
which can be equally strong at object detection. Pikov et al. [
35
] also used Unity to develop an indoors
AR application and QR codes to integrate preprocessed 3D models, but they used a large display to
make details of exhibits more accessible for visitors. In contrast, the e-Tracer AR app allows visitors to
download the preprocessed 3D models on their mobile device and project the (animated) models in a
dynamic zoom in/out mode.
What e-Tracer has to oer more as added-value functionality is the interactive game-like
self-evaluation questionnaire, which is based on the AR component. After visiting the museum
exhibitions, museum visitors are asked to participate in a quiz about the new knowledge gained
from the museum visit. What is new is the AR questions that instead of asking users to select
one of the available options (which is very typical in closed-type questionnaires such as the one
presented in Figure 3a), they ask people to revisit museum collections, search for artefacts with specific
characteristics, and scan them with the camera of their tablet. The AR app will recognize the featured
object as a correct choice and will reward the user with symbolic awards (collected points and user
visibility on a top-ten leaderboard). For example, in the app’s prompt: “Identify in the museum’s
collections of secular artifacts a pen-case with an incorporated inkpot or otherwise “Kalamari””,
users have to go back and look for the silver pen-case, such as in a treasure hunt game (Figure 3b).
Appl. Sci. 2020, 10, x FOR PEER REVIEW 6 of 18
What was described up to now covers mostly the typical functionality expected from an AR
application in museum settings. Considering similar applications, the use of QR codes appears to be
the dominant way of delivering information about artefacts. For example, Pérez-Sanagustín et al. [34]
developed two ways: one using a visitor’s smartphone and QR codes and a second one using a screen
located next to the exhibits, but finally, they chose the first one after measuring the effect QR codes
had on visitors. QR codes with image recognition are also being used as the main object identification
method in commercial AR applications such as Layar (https://www.layar.com) and Gamar
(https://www.gamar.com). Thus, e-Tracer advocates the use of QR codes for indoor or outdoor use,
but at the same time, it takes advantage of the aesthetically superior illustrations of artefacts, which
can be equally strong at object detection. Pikov et al. [35] also used Unity to develop an indoors AR
application and QR codes to integrate preprocessed 3D models, but they used a large display to make
details of exhibits more accessible for visitors. In contrast, the e-Tracer AR app allows visitors to
download the preprocessed 3D models on their mobile device and project the (animated) models in
a dynamic zoom in/out mode.
What e-Tracer has to offer more as added-value functionality is the interactive game-like self-
evaluation questionnaire, which is based on the AR component. After visiting the museum
exhibitions, museum visitors are asked to participate in a quiz about the new knowledge gained from
the museum visit. What is new is the AR questions that instead of asking users to select one of the
available options (which is very typical in closed-type questionnaires such as the one presented in
Figure 3a), they ask people to revisit museum collections, search for artefacts with specific
characteristics, and scan them with the camera of their tablet. The AR app will recognize the featured
object as a correct choice and will reward the user with symbolic awards (collected points and user
visibility on a top-ten leaderboard). For example, in the app’s prompt: “Identify in the museum’s
collections of secular artifacts a pen-case with an incorporated inkpot or otherwise “Kalamari””, users
have to go back and look for the silver pen-case, such as in a treasure hunt game (Figure 3b).
The design of the AR application took into account the needs of museum visitors of all ages.
Dynamic adaptation to the preferred level of difficulty is performed automatically in case of young
children and school students (based on their profile previously created). Moreover, the designers
took into account the findings of Sylaiou et al. [36] derived from evaluating the ARCO (Augmented
Representation of Cultural Objects) application [37] regarding the wished qualities, which were
found to be: intuitive User Interface (UI), high-quality 3D representations (photorealistic), sense of
control, obvious exit, embedded help, and a challenging game concept.
(a) (b)
Figure 3. Screenshot of the e-Tracer Augmented Reality (AR) Quiz (user’s view): (a) Typical quiz
question (multiple choice); (b) Augmented Reality question (look and find).
2.2. Museum Artefact Detection
Despite the technological progress made on Wi-Fi, Bluetooth, Radio-frequency identification
(RFID) technologies and more, orientation in mobile AR applications in indoor places is still an open
question [22]. Market-ready solutions are based on easy-to-implement and reliable techniques in
Figure 3.
Screenshot of the e-Tracer Augmented Reality (AR) Quiz (user’s view): (
a
) Typical quiz
question (multiple choice); (b) Augmented Reality question (look and find).
The design of the AR application took into account the needs of museum visitors of all
ages. Dynamic adaptation to the preferred level of diculty is performed automatically in case
of young children and school students (based on their profile previously created). Moreover,
the designers
took into account the findings of Sylaiou et al. [
36
] derived from evaluating the ARCO
(Augmented Representation of Cultural Objects) application [
37
] regarding the wished qualities,
which were found to be: intuitive User Interface (UI), high-quality 3D representations (photorealistic),
sense of control, obvious exit, embedded help, and a challenging game concept.
Appl. Sci. 2020,10, 7868 7 of 18
2.2. Museum Artefact Detection
Despite the technological progress made on Wi-Fi, Bluetooth, Radio-frequency identification
(RFID) technologies and more, orientation in mobile AR applications in indoor places is still an open
question [
22
]. Market-ready solutions are based on easy-to-implement and reliable techniques in
order to oer smooth visitor experiences without breaks and interruptions while keeping technology
transparent. Following this trend, the e-Tracer AR scenes are subdivided into applications that require
a marker to detect a museum artefact and project a 3D object on top of that. Those that do not require
an additional identifier but use the museum artefact itself (displayed through the mobile camera
0
s
image) as an identifier are still under development. The use of printed Quick Response Codes (QRC)
as markers, although they are easy and cheap to be produced by museums using their own equipment,
was finally avoided, mainly because they are not human readable, and thus, people may not always
understand which marker corresponds to which museum artefact. Moreover, QRC markers are not
aesthetically accepted in a museum or gallery context and are relatively small in sizes; thus, they may
cause a loss in object detection stability. On the other hand, markers that contain a printed copy of
the depicted artifact were considered more appropriate for museum settings for a number of reasons:
they are aesthetically accepted, relatively small in size, cheaper to be produced with the museum’s own
equipment, require relatively low device profiles, and provide eective object detection in controlled
environments. In the physical environment, the AR markers were located next to the artefacts after they
had received optimization for a better object detection accuracy to fix certain problems caused by the
marker-less and QR code techniques (e.g., not human-readable, poor detection quality in low-lighting
conditions, ecient algorithms too demanding for mobile devices). From a technical point of view,
the initial markers (Figure 4a) were first pre-validated using their grayscale histogram in order to
evaluate their initial suitability as markers. Images that combined a low overall contrast and a narrow
and sharp grayscale histogram were not likely to be selected as target markers. In contrast, if the
grayscale histogram was found wide and flat, the image had a good chance to be selected as a marker,
since it contained a nice distribution of visual features.
Appl. Sci. 2020, 10, x FOR PEER REVIEW 8 of 18
(c) (d)
Figure 4. Museum artefacts used as AR markers: (a) example of original picture evaluated by the
object detection algorithm as a 3-star marker, (b) optimized picture evaluated as a 4-star marker for
the same object, (c) a second example of a 4-star object marker (inkwell), (d) another example of an
object marker seen from two different angles (pistol).
Before and after modifications, the pictures of the objects were evaluated against their suitability
to be used as markers in the e-Tracer AR application. The evaluation criterion was based on the
evaluation algorithm of the Vuforia (https://engine.vuforia.com/engine) engine, which computes the
number of high contrast points. For simplicity, the overall quality is expressed in a range of 1 to 5
stars. Before any modification, the pictures of the museum artefacts were not exceeding 2 or 3 stars
at maximum, while after modifications, the quality rose to 4 stars at minimum. Part of the validation
process was testing against tolerance to rotation, but since the object detection engine returned a 6
Degrees of Freedom (DoF) pose of the target to the application layer, it was possible to automatically
determine the amount of rotation and finally to project the 3D augmented object on the right angle.
2.3. Development Process and Tools
The overall AR app development process (Figure 5) was based on a modified Herzig [41]
approach, which was used to insert game elements into a knowledge domain, such as the digital
heritage in this case. The AR app development was separated from the development of the rest of the
e-Tracer platform, which is about designing and developing a system that, exploiting innovative
spatial interconnection technologies for multiple sites of environmental, cultural and touristic
interest, will discover semantic information from multiple data sources, providing users with the
ability to organize integrated touristic routes across Via Egnatia in Northern Greece. Although
separated in development, the e-Tracer platform and its AR applications are being offered to
customers through a single-entry point (web view).
Figure 4.
Museum artefacts used as AR markers: (
a
) example of original picture evaluated by the object
detection algorithm as a 3-star marker, (
b
) optimized picture evaluated as a 4-star marker for the same
object, (
c
) a second example of a 4-star object marker (inkwell), (
d
) another example of an object marker
seen from two dierent angles (pistol).
Appl. Sci. 2020,10, 7868 8 of 18
Afterwards, potential markers were optimized according to the Vuforia’s guidelines [
38
] for
achieving a better object detection accuracy:
Gamma correction: Gamma encoding is applied on images usually to optimize the usage of bits
during compression, by taking advantage of the non-linear manner in which humans perceive
colors and light [
39
]. Here, gamma correction was applied with powers larger than 1 to make the
shadows of the artefact darker (Figure 4b).
Local contrast enhancement adjustments: An overall contrast/brightness adjustment helped
enhance visual features, especially around corners and borders of flat surfaces. A lighter color in
the background layer resulted in more feature points, while higher contrast and lower brightness
on foreground features improved the feature’s quality.
Laplacian filter: applied to detect edges, enhance them, and thus increase the points of interest,
making them easily discoverable in museum rooms, even with varying lighting conditions.
Additional adjustments such as cropping images to remove areas without a density of features
(for example, the barrel of the pistol in the top-right corner of Figure 4d) could improve the overall
rating of the marker, but such modifications were not applied, since the markers are museum artefacts
themselves, and any cropping could lead to a poor visual representation of the historical objects.
Finally, the real object is being detected as its characteristics are compared with the characteristics of
the models that are known in advance as a marker [40].
Before and after modifications, the pictures of the objects were evaluated against their suitability
to be used as markers in the e-Tracer AR application. The evaluation criterion was based on the
evaluation algorithm of the Vuforia (https://engine.vuforia.com/engine) engine, which computes the
number of high contrast points. For simplicity, the overall quality is expressed in a range of 1 to
5 stars. Before any modification, the pictures of the museum artefacts were not exceeding 2 or 3 stars at
maximum, while after modifications, the quality rose to 4 stars at minimum. Part of the validation
process was testing against tolerance to rotation, but since the object detection engine returned a
6 Degrees of Freedom (DoF) pose of the target to the application layer, it was possible to automatically
determine the amount of rotation and finally to project the 3D augmented object on the right angle.
2.3. Development Process and Tools
The overall AR app development process (Figure 5) was based on a modified Herzig [
41
]
approach, which was used to insert game elements into a knowledge domain, such as the digital
heritage in this case. The AR app development was separated from the development of the rest of
the e-Tracer platform, which is about designing and developing a system that, exploiting innovative
spatial interconnection technologies for multiple sites of environmental, cultural and touristic interest,
will discover semantic information from multiple data sources, providing users with the ability to
organize integrated touristic routes across Via Egnatia in Northern Greece. Although separated in
development, the e-Tracer platform and its AR applications are being oered to customers through a
single-entry point (web view).
The e-Tracer AR app was developed in Unity (Unity, https://unity.com) and uses the ARCore
Software Development Kit (SDK) provided by Google (https://en.wikipedia.org/wiki/ARCore).
More specifically, the e-Tracer application consumes the motion tracking, environmental understanding,
and light estimation services of the SDK. The detailed 3D models of the Ioannina Silversmithing
museum’s artefacts (the most heavy or not movable ones) were provided by the supervising organization
(Piraeus Bank Group Cultural Foundation), while the modeling of supplementary virtual elements
was performed in Google Sketchup (https://www.sketchup.com), 2018 version. Some light objects
such as silversmithing hand tools were scanned using a portable Sense 3D Scanner (Cubify 3D Sense,
https://www.3dsystems.com), but with moderate results, as the resulted 3D models need retouching to
achieve our quality standards. The processing of the AR markers was performed in a freeware version
of PaintShop Pro (https://www.paintshoppro.com). The main object detection processing is performed
Appl. Sci. 2020,10, 7868 9 of 18
on the user’s mobile device, while 3D models are being automatically downloaded from the cloud
services of the e-Tracer system and become available to the user on demand to allow them to examine
hidden sides or details of the artefact (Figure 6).
Appl. Sci. 2020, 10, x FOR PEER REVIEW 9 of 18
Figure 5. Overall AR development process.
The e-Tracer AR app was developed in Unity (Unity, https://unity.com) and uses the ARCore
Software Development Κit (SDK) provided by Google (https://en.wikipedia.org/wiki/ARCore). More
specifically, the e-Tracer application consumes the motion tracking, environmental understanding,
and light estimation services of the SDK. The detailed 3D models of the Ioannina Silversmithing
museum’s artefacts (the most heavy or not movable ones) were provided by the supervising
organization (Piraeus Bank Group Cultural Foundation), while the modeling of supplementary
virtual elements was performed in Google Sketchup (https://www.sketchup.com), 2018 version.
Some light objects such as silversmithing hand tools were scanned using a portable Sense 3D Scanner
(Cubify 3D Sense, https://www.3dsystems.com), but with moderate results, as the resulted 3D
models need retouching to achieve our quality standards. The processing of the AR markers was
performed in a freeware version of PaintShop Pro (https://www.paintshoppro.com). The main object
detection processing is performed on the user’s mobile device, while 3D models are being
automatically downloaded from the cloud services of the e-Tracer system and become available to
the user on demand to allow them to examine hidden sides or details of the artefact (Figure 6).
Figure 5. Overall AR development process.
Appl. Sci. 2020, 10, x FOR PEER REVIEW 10 of 18
Figure 6. Screenshot of a high-poly rotated 3D model projected on demand—when available—to
allow users to examine details on the surface of the artefact.
2.4. Evaluation Method
The current e-Tracer AR prototype has been evaluated—at first—by a group of experts. Although
user testing is in the future plans, the expert review method is considered equally accurate in case of
skillful and knowledgeable usability experts [42,43]. Moreover, a systematic review of Dey et al. on
AR usability studies published from 2005 to 2014 [44] indicated that user studies—which is the most
common evaluation approach—may not be enough, and that heuristic evaluation on AR applications
needs to be further developed. The usability heuristics proposed by Nielsen [45] are generally
accepted in this study, but since they are oriented to productivity software and not to Digital
Heritage, finally, the listing of Endsley et al. [46] was preferred, as it can better frame the multiple
aspects of the AR experience design.
The classification of issues (heuristic criteria violations) according to their severity was taken
from the International Software Testing Qualifications Board, which defines “the degree of impact
that a defect has on the development or operation of a component or system” [47]. According to the
above, four classes of heuristic criterion violations were proposed: Blocking/Critical, Major, Minor,
and Insignificant.
2.5. Evaluation Protocol
In this study, four (4) experts in museum technology were employed as volunteers in the spring
semester of 2020. From those, three (3) were males and one (1) was female, all in the range of 39 to 65
years old. The members of the expert panel represent four different but interconnected communities:
academics, schoolteachers, artists, and museum curators. More specifically, one expert is a University
professor with a specialty in multimedia applications in visual arts and museums, another one is an
active educator, book author, and expert in didactic interventions using art and ICT tools, a third one
is a chief curator at a national museum (of contemporary art), and the last expert is a school art
educator with experience in educational applications. It is worth mentioning that those people were
not involved in the development stages of the AR system or in the e-Tracer project.
The purposes and the protocol of the evaluation were explained on a one-to-one basis, according
to which experts were able to ask their own questions and receive additional information about the
AR app. According to the Experts Team assessment method, the experts were invited to critically
review the AR system and were involved based on their experience and expertise in evaluating ICT
applications in education and in digital heritage. Each member of the expert group evaluated the
prototype individually, after they were instructed to explore the application through its demo materials.
An online questionnaire was established using a common e-Survey engine to collect reviewer’s
feedback against the heuristic criteria explained in the following section.
Overall, it was expected that the expert group would discover possible violations of the given
heuristic criteria, estimate the level of severity, and finally provide recommendations for further
development on the functional characteristics of the application.
Figure 6.
Screenshot of a high-poly rotated 3D model projected on demand—when available—to allow
users to examine details on the surface of the artefact.
2.4. Evaluation Method
The current e-Tracer AR prototype has been evaluated—at first—by a group of experts.
Although user testing is in the future plans, the expert review method is considered equally accurate in
Appl. Sci. 2020,10, 7868 10 of 18
case of skillful and knowledgeable usability experts [
42
,
43
]. Moreover, a systematic review of Dey et al.
on AR usability studies published from 2005 to 2014 [
44
] indicated that user studies—which is the most
common evaluation approach—may not be enough, and that heuristic evaluation on AR applications
needs to be further developed. The usability heuristics proposed by Nielsen [
45
] are generally accepted
in this study, but since they are oriented to productivity software and not to Digital Heritage, finally,
the listing of Endsley et al. [
46
] was preferred, as it can better frame the multiple aspects of the AR
experience design.
The classification of issues (heuristic criteria violations) according to their severity was taken
from the International Software Testing Qualifications Board, which defines “the degree of impact
that a defect has on the development or operation of a component or system” [
47
]. According to the
above, four classes of heuristic criterion violations were proposed: Blocking/Critical, Major, Minor,
and Insignificant.
2.5. Evaluation Protocol
In this study, four (4) experts in museum technology were employed as volunteers in the spring
semester of 2020. From those, three (3) were males and one (1) was female, all in the range of 39 to
65 years old. The members of the expert panel represent four dierent but interconnected communities:
academics, schoolteachers, artists, and museum curators. More specifically, one expert is a University
professor with a specialty in multimedia applications in visual arts and museums, another one is an
active educator, book author, and expert in didactic interventions using art and ICT tools, a third
one is a chief curator at a national museum (of contemporary art), and the last expert is a school art
educator with experience in educational applications. It is worth mentioning that those people were
not involved in the development stages of the AR system or in the e-Tracer project.
The purposes and the protocol of the evaluation were explained on a one-to-one basis, according to
which experts were able to ask their own questions and receive additional information about the
AR app. According to the Experts Team assessment method, the experts were invited to critically
review the AR system and were involved based on their experience and expertise in evaluating ICT
applications in education and in digital heritage. Each member of the expert group evaluated the
prototype individually, after they were instructed to explore the application through its demo materials.
An online questionnaire was established using a common e-Survey engine to collect reviewer’s feedback
against the heuristic criteria explained in the following section.
Overall, it was expected that the expert group would discover possible violations of the given
heuristic criteria, estimate the level of severity, and finally provide recommendations for further
development on the functional characteristics of the application.
3. Results
This section provides a concise and precise description of the experimental results. Table 1presents
the heuristic criteria used for the evaluation of the e-Tracer AR application (including the AR quiz),
the possible violations identified by the members of the expert team, and their comments on how
violations—or their eects on usability—could have been mitigated.
Apart from closed questions, a second part of the review was introduced a couple of weeks later
to let experts express themselves regarding the advantages of AR technology when used in museums
and the advances of the proposed application over conventional systems. Three out of four invited
experts responded in this second part and provided valuable feedback. The questions were given to
reviewers in the local language (Greek); however, English translations are provided below.
In the question (RQ1), “In your opinion, what is the advantage of using Augmented Reality during
a museum tour?”, one expert made a direct comparison to the standard audio tour, and two others
mentioned the immersion and interaction eect. More specifically, it was explained that AR is far
better than a pause-and-play audio experience, which is the dominant model so far. One member
of the expert team explained that visitors frequently complain about audio interfaces because it can
Appl. Sci. 2020,10, 7868 11 of 18
easily become “annoying to search for the artefact number, type it to the audio device, press the playback button,
and then go back and forth all the time because the narration may go too fast”. Such small diculties and
interruptions can ruin the overall visitor’s experience. In contrast, AR apps can sense what the visitor
is looking at and display the right information without inconvenience. In addition, it was said that AR
can provide a more interactive and immersive journey in the museum and actually can help visitors
develop a new kind of relationship with the artefacts. In other words, apart from creating a memorable
journey, AR can develop the feeling of ownership and can maximize the time visitors spend on site.
Table 1. Heuristic evaluation criteria for AR [46] and experts’ responses.
A/A Heuristic Criterion Violations Comments and Mitigation Actions
1
Fit with user environment and task:
visualizations and metaphors should
match the user’s mental models
Expert 1:
Expert 2:
Expert 3:
Expert 4:
Although visual metaphors were
self-explained, it was not clear if the
available time (gauge bar) refers to the
quiz or only to the first question.
2
Form communicates function: Virtual
elements should rely on existing
metaphors to communicate
aordances and capabilities
Expert 1:
Expert 2:
Expert 3:
Expert 4:
Visual metaphors are well known to
users. Flashing brackets are OK, but it
was recommended to display a message
to prompt the user explore the physical
space in AR questions.
3
Minimize distraction and overload:
minimize accidental distraction as AR
apps can easily become
visually overwhelming
Expert 1:
Expert 2:
Expert 3:
Expert 4:
There is a well-stepped process in
accessing the museum information (first
short info and then full artifact screen).
4
Adaptation to user position and
motion: virtual elements are useful
and usable from the variety of
viewing angles, distances,
and user’s movements
Expert 1:
Expert 2:
Expert 3:
Expert 4:
The system is stable and reliable only in
good lighting conditions. In poor
lighting, the markers cannot
be identified.
5
Alignment of physical and virtual
worlds: Placement of virtual elements
should make sense in the
physical environment
Expert 1:
Expert 2:
Expert 3:
Expert 4:
Virtual objects appear nicely near
markers and are aligned with
architectural elements of the physical
world (e.g., walls).
6
Fit with user’s physical abilities: AR
experience should not require
physically challenging or
dangerous actions
Expert 1:
Expert 2:
Expert 3:
Expert 4:
No physically challenging or dangerous
actions were found.
7
Fit with user’s perceptual abilities:
The app should not present info in
ways that fall outside of an intended
user0s perceptual thresholds
Expert 1:
Expert 2:
Expert 3:
Expert 4:
The visual elements size, colors, and
motion are well designed. Resolution is
appropriate for tablets and distance to
AR markers aordable.
8
Accessibility of o-screen objects: AR
UI should make it easy to find/recall
the items users need to manipulate
when those items are outside the field
of view
Expert 1:
Expert 2:
Expert 3:
Expert 4:
No violations to this heuristic
were found.
9
Accounting for hardware capabilities:
AR apps should meet the capabilities
and limitations of the user’s mobile
devices
Expert 1:
Expert 2:
Expert 3:
Expert 4:
Some of the app components could not
overcome the limitations of the
hardware (not all devices are supported,
especially older ones).
The next question (RQ2) was about the advantages of the e-Tracer AR app (“Based on the AR
application you evaluated, what do you think is its biggest advantage over existing applications?”). The main
advantages can be summed up as follows: the use of images instead of QR codes, the interactive
learning model, the playful interaction with the artefacts, and the 3D model projection capabilities.
Appl. Sci. 2020,10, 7868 12 of 18
Especially in the Silversmithing museum, there are plenty of small objects such as jewelry placed one
next to the other; thus, a typical QR code marker method would have practical diculties. It is worth
mentioning that apart from the evident advantage of using 2D or thin artefacts as markers themselves,
existing posters, graphical illustrations, and historical photographs already placed on the walls can be
used as markers as well. An expert said that the advantage of the e-Tracer AR app is the 3D projection
capabilities: “It is nice that you can rotate the 3D model and see hidden parts of it. I liked the 3D zoom in/out
feature, which allows people to study details.” The projection of 3D models is of particular interest in
cases of small jewelry or unique or very expensive artefacts that are protected inside glass boxes and
cannot be seen from all angles or viewed up close. Another expert mentioned that the AR question
functionality is the biggest advantage of the app under testing, but this is discussed below as it is more
related to the next question. The third reviewer appreciated the immersion capabilities and the fact
that, “Somehow, this app forces visitors to deal exclusively with them (artefacts) during the virtual tour.
The last open question (RQ3) was about the new type of question introduced in the e-Tracer quiz
app and is based on the AR technology. The question was, “Based on the AR application you evaluated,
what you think is the advantage of using Augmented Reality in the self-assessment quiz?” Experts appreciated
the interactive learning model being used and the play-to-learn experiences it could create to visitors,
especially the younger ones. Circulating quizzes after a museum visit is not something new, nor the
fact that the quiz is delivered through a mobile device. However, as an expert explained, it is the
combination of AR experience, treasure game, and new knowledge self-assessment that makes this
feature unique and dierent than other AR apps. This feature is significant because it allows people
to construct complete mental shapes (concepts) about artefacts as they have the chance to revisit,
have a second look at artefacts, and pay attention to details. The second expert supported that the
innovative use of the AR question gives the user the opportunity to revisit exhibits”, while the third one
explained that the AR component of the quiz “applies some force to visitors to meditate on the application
and thus makes them to recall the information displayed and compare it with prior knowledge”. Authors can
add here that the AR questions do not simply test knowledge gained in the museum (this could be
considered pretentious) but provide a playful way to (re)explore exhibitions without having missed
important parts of it.
4. Discussion
This section will discuss the evaluation results of the e-Tracer AR app and will perform comparisons
with the results of other studies regarding similar applications. AR apps that require special equipment
such as wearables, Smart Glasses, IoT devices, and prior user education/training on how to use the
special equipment are excluded from these comparisons. Those should be considered non-similar
approaches in the context of everyday museum experience by wide audiences.
In general, AR technology opened up new navigation and visualization possibilities for museum
visitors. It can introduce interactivity, tour guides, games, and 3D projection capabilities without a
possible damage to the artefact: qualities that are needed to balance static museum content and fight
visitor’s boredom. According to other researchers [
8
,
48
] and also the experts’ panel in this study,
these seem to be the main advantages of the technology-supported augmentation AR has to oer in
visitor’s experience.
Regarding the e-Tracer AR application, one very important usability result that emerged from
the experts’ estimates is that the used visual metaphors and the overall interaction design were
self-explained and well-known to users from other AR experiences and apps they may have used.
One expert found that the visual metaphor for the available time that appeared as a green line
(gauge bar), which progressively moves to the right of the screen as time elapses, was not very clear.
More specifically, it was not clear to the reviewer if the time bar refers to the overall quiz time or the
time given to the current question. This issue was noted as major, and finally, it was fixed by explaining
in the help files that each question may have a dierent available time, according to its diculty.
Appl. Sci. 2020,10, 7868 13 of 18
Although not a heuristic violation, one expert recommended that the AR quiz app should display a
message to prompt the user to explore the physical space in the AR questions. This message, in addition
to the flashing brackets, would reduce the risk of user’s laziness or boredom.
Two experts identified a problem in the system’s ability to adapt to the position and orientation of
the user, especially in poor lighting conditions. It is true that the interior of the Silversmithing museum
at Ioannina is quite atmospheric, leading to an intended low lighting condition; thus, the object
detection algorithm of the AR app would have diculties performing well under such conditions.
This issue could be overcome if markers were placed in the center of bright spotlight cones. There could
be more places in the museum where light would be enough to allow maximum performance for the
object detection mechanism, but this may require either the rearrangement of museum exhibitions or
the placement of additional spotlights targeting the museum artifact markers.
Another issue that was identified as blocking/critical by two of the experts was the non-adaptability
of the app to poor device profiles. Actually, the e-Tracer AR app requires a relatively new hardware
profile and updated software from the hosted tablets; otherwise, the app may not start at all. Luckily,
the mobile devices used by the wider audiences are getting better and better, and in the near future,
this will not be an issue. On the other hand, within the e-Tracer project, there is a provision for the
supported museums to supply tablets to the visitors who wish to experience the AR functionality of
the application.
The results of the comparison between the e-Tracer AR app and other AR applications for museums
(based on literature findings and the opinions expressed by the experts) presented evidence that
AR games appear to be a promising approach that is meant to create extra motivation to museum
visitors, especially young children. This is in line with the e-Tracer AR design, which invested in
the combination of a gamified AR experience with self-evaluation through a quiz to oer the chance
to discover a dierent aspect of the exhibitions in a second route and to create memorable playful
experiences for younger visitors. As an example, Antoniou et al. [
49
] agree that online Serious Games
can attract the interest of more visitors and thus make cultural heritage sites known and increase
physical visits to the sites. Other researchers found that museum visitors need support tools to facilitate
their informal learning [
50
] and that game elements in AR applications for museums can support
learning. Indeed, Oh et al. [
51
] found that the game component in the AR app they had designed made
learners achieve a better learning performance than those who had had a similar AR experience but
without the game element.
The e-Tracer AR app was designed to serve educational, museological, and user experience
objectives. The realization of a heuristic evaluation protocol created the first evidence that it can
fit very well in the user’s environment and physical movement, known concepts, mental models,
navigation metaphors, physical/perceptual abilities, and museological context for which it was designed.
Moreover, experts found that a unique combination of game elements, cutting-edge AR technology,
immersion, interaction, and self-assessment of new knowledge was achieved in the e-Tracer AR app.
It is expected that those features will be beneficial to museum guidance and the time visitors spend on
exhibitions, as well as to information gathering through 3D models superimposition and finally to
learning through the AR questions, which give the opportunity to revisit and pay attention to details
not seen before. All of the above justify the playful design of the e-Tracer AR and informal learning
components, which were both very well represented by the AR quiz component.
Additional features
such as the use of image markers and the projection of 3D content on top of the static artefacts
on demand complete the puzzle of a modern AR application which makes exhibits appear alive,
more appealing, and ready to be explored. Similar unobtrusive marker approaches can be found in
Khan et al. [
52
], which used printed black-and-white markers detected by a smartphone’s camera,
or in a case study of the Museo Diocesano of Milan [
53
] in which natural printed markets were used.
All these studies can confirm that low-cost unobtrusive markers can be a well-working solution for
low-to-medium sized museums.
Appl. Sci. 2020,10, 7868 14 of 18
On the other hand, this study may have some limitations, which are mostly related to the sample
and selection of reviewers. Although expert team evaluation using heuristic criteria is a common
formative evaluation and has certain advantages [
54
], according to the white paper of Mahmoud [
55
],
there is a possible bias in the selection of experts. This refers to the possible future involvement
of the experts in the new product, sharing a lot of similarities such as backgrounds and sources
of information, having non-suitable expertise and unknown bias, if experts are outsiders. In the
current study, eort was made to minimize those risks by recruiting experts who (1) will not get
involved anyhow in the future product, (2) have dierent backgrounds (academia, typical education,
museum exhibitions organization and art educators/creators) and (3) have hands-on expertise in
cultural technology. The only remaining risk—according to the way Rabie describes it—is related to
unknown bias, as experts are external to the project.
5. Conclusions
Most state-of-the-art AR solutions depend on the use of special equipment (such as wireless
sensors, IoT devices, see-through AR glasses, or other wearable devices) to catch the attention of the
museum visitors and enhance their experience. However, apart from being expensive, this special
hardware needs maintenance. Moreover, education on how to use hardware should be provided to the
visitors. Although most of those solutions give impressive results in usability, they suer from the fact
that they cannot be used in a context of a massive attendance of visitors.
To overcome these drawbacks, the e-Tracer AR application does not make use of any other special
equipment than the user’s smartphones and tablets. The proposed application is intended to be used
by numerous small-sized museums distributed in the Greek province. Local museums operate under
limited financial means, and unfortunately, the number of tickets they issue each day does not justify
buying expensive equipment or developing AR applications using their own means. Thus, the e-Tracer
project proposed AR horizontal use-case scenarios that can get the most out of AR technology using
the visitors’ own devices.
According to the above, the e-Tracer AR app was designed for the museum’s network of the Piraeus
Bank Group Cultural Foundation giving emphasis on a visitor’s navigation, learning, and gaming
experiences. Mobile AR technology was used to display digital versions of artefacts next to their
physical position in the museum, bring objects to life, and make an interactive narration out of the
available information about artefacts. The element of originality here lies in the AR quiz component
used to give visitors motivation to revisit museum collections, spend more time interacting with
the museum collections, and oer a memorable game-like experience, which may be of particular
interest to younger visitors. Moreover, it could be used to measure growth in knowledge for in situ
museum visitors.
Apart from being in line with the results of other similar AR projects for museums, e-Tracer has
some unique new features to propose. The originality lies with a novel AR quiz in which questions
are proposals for revisiting exhibitions, seeing artefacts from a new perspective, paying attention to
details, and participating in a game-like AR activity inside the museum. Moreover, the identification
of an object is based on more aesthetically accepted markers than QR codes, which may not reveal
much about the artifact they correspond to and may disorientate visitors.
Overall, AR proposes a unique set of challenges for technology designers to integrate interactive
AR experiences into the museum context. Apart from user’s positioning and attention, there are
environmental conditions that may influence the overall user experience of the museum visitor.
Those conditions are not always known in advance, and thus, developers need to follow both design
guidelines and evaluation protocols before being confident that their AR software services can assess
the general required usability and there are no barriers to sustainability.
Future plans of the e-Tracer AR app include the evaluation of the prototype by museum visitors
via extensive trials that will be carried out during the e-Tracer project lifecycle. After a successful
first evaluation of the prototype using the experts team protocol and having scalability in mind,
Appl. Sci. 2020,10, 7868 15 of 18
the prototype will be further developed to handle a growing amount of work by adding more content
such as 3D models, multimedia, and object’s metadata, and by supporting simultaneous users in
more than one museum. Thus, the final evaluation will include cross-museum visitor experience
assessment. Dierences regarding AR technology acceptance and overall engagement between groups
of people with dierent demographic characteristics will be researched as a topic of particular interest.
Moreover, it will be investigated how visually impaired people could take advantage of the gamified
quiz application based on successful existing paradigms on map exploration using mobile devices [
56
].
Author Contributions:
The individual contributions of the authors are (according to CRediT taxonomy):
conceptualization, methodology and investigation I.P. and A.T.P.; software, A.T.P., E.E.M., A.K. and E.A.S.;
validation, I.P., G.P., G.M. and S.T.; formal analysis, I.P.; writing—original draft preparation, I.P.; writing—review
and editing, I.P., E.E.M. and E.A.S.; visualization, E.K., C.T., G.P., C.R. and E.T.; supervision, S.D., S.V., K.V., I.K.
and D.T.; project administration, I.K., and K.V. All authors have read and agreed to the published version of
the manuscript.
Funding:
This research was funded by the European Union and Greek national funds through the Operational
Program Competitiveness, Entrepreneurship and Innovation, under the call RESEARCH-CREATE-INNOVATE
(grant number: T1EDK-00410) with a project name e-XNHΛATHΣ(e-Tracer in English).
Conflicts of Interest:
The authors declare no conflict of interest. The funders had no role in the design of the
study; in the collection, analyses, or interpretation of data; in the writing of the manuscript, or in the decision to
publish the results.
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