Development of Diagnostic Skills in Dentistry Students using Gamiﬁed

Virtual Patients

Sneyder J. Sanchez M.

, Juan E. G

omez-Morantes

1,∗

, Carlos Parra

, Angela Carrillo-Ramos

, Adriana

I. Camacho

and Gloria C. Moreno

Systems Engineering Department, Pontiﬁcia Universidad Javeriana, Bogot

a, Colombia

Dental System Department, Pontiﬁcia Universidad Javeriana, Bogot

a, Colombia

{camacho-adriana, gcmoreno}@javeriana.edu.co

Keywords:

Virtual Patients, Serious Games, Dentistry Education, Endodontics, Diagnostic Skills.

Abstract:

The use of serious games, virtual patients, and other forms of digital learning technologies are starting to

emerge in dentistry schools around the world. However, because of their novelty, there is still a need for lit-

erature discussing the different challenges of computer-supported education in this ﬁeld. This paper presents

the design, development, and pilot validation of a serious game for the development of diagnostic skills in

dentistry students. Called RealTeeth, this game puts the student in a job interview context and asks him to

diagnose 10 endondontic cases. Each case allows the student to follow 5 different diagnostic routes with dif-

ferent information and resources. At the end of the 10 cases, the student will receive a job offer in accordance

with his or her performance on the cases. This game was tested with a cohort of student of the pre-clinic course

of endodontics in the Pontiﬁcia Universidad Javeriana in Bogot

a, Colombia. The results of this pilot valida-

tion were positive in terms of user acceptance and attitude, reinforcing the potential of computer supported

education in the ﬁeld of dentistry.

1 INTRODUCTION

Endodontics is a dentistry specialty that focuses on

the study of dental pulp and dental pulp diseases.

In the case of the Pontiﬁcia Universidad Javeri-

ana, endodontics is taught as part of the dentistry un-

dergraduate program with two obligatory pre-clinic

courses

and one emphasis course

. The two pre-

clinic courses are seen in the third year of the ﬁve-

year dentistry program, while the emphasis course is

seen in the fourth or ﬁfth year of the program.

The three endodontics courses are structured fol-

lowing Miller’s pyramid (see Figure 1). The ﬁrst

course is dedicated to what Miller calls knowledge

assessment, understood as “some assurance that a stu-

dent, a resident, a physician knows what is required in

order to carry out those professional functions effec-

∗

Corresponding author.

Pre-clinic courses are those that the student have to

complete before his or her clinic internship

Emphasis courses are optional courses that deal with

advance topics on the different disciplines of dentistry. Stu-

dents can select emphasis courses according to their per-

sonal o professional interests.

tively” (Miller, 1990, p. S63, emphasis in original).

For endodontics this includes all the knowledge re-

lated to tooth and dental pulp anatomy, endodontics

conditions (the 11 basic diagnosis

), the signs of the

11 basic diagnosis, and the tests needed to reach any

of the 11 diagnosis.

The second course is aimed at the competence as-

sessment level of Miller’s pyramid, deﬁned as the one

that evaluates that “graduates must also know how to

use the knowledge they have accumulated” (Miller,

1990, p. S63, emphasis in original), and is devoted to

semiotic competences.

Semiotic competences are related to interpretation

of data and symbols, which, in the case of endodon-

tics, are related to communicating with patients and

interpreting the data provided by them. These semi-

otic competences are intimately related to diagnostic

skills and include, “among other things, the skill of

There are 11 basic diagnosis in endodontics, which are

covered in the ﬁrst pre-clinic course. However, there are

other conditions that could include endodiotic signs or dis-

eases. For example, a periodontic condition could result in

an endodontic disease. Those associated conditions are not

covered in the ﬁrst pre-clinic course nor in RealTeeth.

124

M., S., Gómez-Morantes, J., Parra, C., Carrillo-Ramos, A., Camacho, A. and Moreno, G.

Development of Diagnostic Skills in Dentistry Students using Gamiﬁed Virtual Patients.

DOI: 10.5220/0007708001240133

In Proceedings of the 11th International Conference on Computer Supported Education (CSEDU 2019), pages 124-133

ISBN: 978-989-758-367-4

Knowledge

Competence

Performance

Action

Figure 1: Miller’s pyramid: Framework for clinical assess-

ment. Adapted from (Miller, 1990).

acquiring information from a variety of human and

laboratory sources, to analyze and interpret these data,

and ﬁnally to translate such ﬁndings into a rational di-

agnostic or management plan” (Miller, 1990, p. S63).

Finally, the third course is an elective course with

advanced semiotic and clinical competences for stu-

dents with a special interest in endodontics.

Students start their clinic internship to put in prac-

tice and further develop the knowledge and skills ac-

quired in the pre-clinic courses. Since this is where

they put their skills into practice and get access to real

patients, this is where performance and action assess-

ment takes place (Miller, 1990).

This teaching structure, based on a pre-clinic com-

ponent and a clinic internship, is commonplace in

medical education (Miller, 1990; Brailovsky et al.,

2001; Brailovsky, 2001). However, climbing Miller’s

pyramid is a considerable challenge. In the assess-

ment front, there is a tendency to believe that knowl-

edge should be the core of medical education assess-

ment. As Miller says, “there are many who appear to

believe that this knowledge base is all that needs to be

measured” (Miller, 1990, p. S63, emphasis in origi-

nal). This view could be attributed to the difﬁculties

of assessments at the competence or performance lev-

els without including real patients.

The training front faces similar challenges. Since

the development of real-life skills is difﬁcult from

a classroom, most teaching efforts are geared to-

wards the knowledge level of Miller’s pyramid. How-

ever, since knowledge does not necessarily translate

to skill, competence and skill building remains elu-

sive. Some teaching methods like problem-based

learning have been explored as a possible solution

for this issue, but they have shown mixed results at

the pre-clinic level (Hartling et al., 2010). More re-

cently, and due to moderm technological advance-

ments included in medical education, simulation el-

ements have been introduced as a way to facilitate

the competence building process and its assessment

(Gaba, 2004; Issenberg et al., 2005).

It is clear, then, that new skill and competence

building methods should be explored in pre-clinic

endodontics education to avoid the shortfalls of a

knowledge-centric medical education. With that in

mind, this research proposes a simulation approach

materialized in a serious game in which pre-clinic stu-

dents have to act as dentists for virtual patients and

reach an adequate diagnosis. The objective behind

this technology introduction is twofold; ﬁrst, there is

the objective of providing a tool for students to ex-

ercise and develop their diagnostic skills. Second, it

can be used to asses the knowledge and competence

levels of Miller’s pyramid.

This paper starts with a brief overview of the rel-

evant literature in section 2. The methodology fol-

lowed in this research is presented in section 3. Af-

terwards, section 4 presents more details about Real-

Teeth and the pilot validation performed during this

research. Finally, the paper concludes in section 5

with a discussion about the lessons learned during this

project and outlines a research agenda based on these

lessons.

2 RELATED WORK

Computer supported education is a strong trend that

has permeated more and more disciplines as time goes

by. Endodontics, or dentistry at a more general level,

is no stranger to this trend and there is already a strong

body of work exploring the intersection between dig-

ital technologies and dentistry education. The cur-

rent literature in this domain can be classiﬁed in three

groups; the adoption of digital technologies among

dentistry students, teachers, or schools; the use of dig-

ital technologies as an educational tool; and the edu-

cation and training in digital technologies speciﬁc to

the dentistry profession.

The literature on adoption of digital technologies

among students, teachers, or schools follows a tra-

ditional adoption studies approach to evaluate ac-

ceptance, adoption factors, or likelihood of adop-

tion of digital technologies among the aforemen-

tioned groups. In general, there seems to be an ad-

equate set of adoption factors like previous experi-

ence with digital technologies (e.g. the Internet, smart

phones, personal computers) by students and teaches

opez Jordi et al., 2016; Mari

no et al., 2012), and

positive attitudes towards the use of digital technolo-

gies as a teaching aid (L

opez Jordi et al., 2016; Mc-

Cann et al., 2010; Ren et al., 2017; Amer et al., 2011).

However, there are warnings against purely virtual

Development of Diagnostic Skills in Dentistry Students using Gamiﬁed Virtual Patients

125

models. In this sense, (McCann et al., 2010) indi-

cates that most students see digital learning tools as

complements to face-to-face teaching rather than a re-

placement. This is consistent with the work of (Reiss-

mann et al., 2015) that demonstrates a high accep-

tance of blended models and the use of digital learn-

ing tools by dentistry students.

There are, however, few studies that focuses ex-

plicitly on the adoption rate of digital learning tools

among dentistry schools. This is a big gap in the liter-

ature because, as (Ren et al., 2017) shows, acceptance

and intention to adopt does not necessarily lead to ac-

tual adoption of digital technologies in the classroom.

The literature on the actual use of digital learning

tools in dentistry education is more diverse, covering

the development of virtual patients or serious gam-

ing for dentistry students, the development of learn-

ing platforms (Bravo-Torres et al., 2017; MacPherson

and Brueckner, 2003), and the evaluation of impact of

digital learning tools in the performance of dentistry

students.

Serious games for education, or game-based

learning (GBL), is a popular subject in computer-

supported education literature. At its core, serious

games explores the use of game technologies or me-

chanics in education applications. In this sense, and

because of the interactive nature of games, it lends

itself to support problem-based, inquiry based or

learning-by-doing methodologies (Shih et al., 2010).

In terms of technologies, virtual reality, mobile or

ubiquitous computing, digital social networks, and

adaptive systems are among the most common tech-

nologies used in the development of GBL systems

(Shih et al., 2010). Virtual reality and human-

computer interaction technologies allow for the de-

velopment of 3D systems that could be manipulated

by traditional means (keyboard and mouse peripher-

als) or more sophisticated means like Nintendo Wii

remotes, Microsoft Kinect sensors, or wired gloves.

In this sense, virtual reality in GBL could lead to an

immersive experience for students. Mobile an ubiqui-

tous technologies could be used to support location-

based learning (e.g. ﬁeld works or explorations) and

uses GPS information to create an augmented reality

experience for students. Digital social networks can

be used to implement social-heavy GBL systems or

to integrate social features in other GBL tools. Fi-

nally, adaptive systems can be used in conjunction

with other technologies to create GBL tools that adapt

to different aspects of the use like preferences, learn-

ing pace, learning styles, among others.

The development of virtual patients, usually ac-

companied by gamiﬁcation elements, is the most

common for of game-based learning in the ﬁeld of

dentistry and is a popular theme in this literature

(Antoniou et al., 2014; Sipiyaruk et al., 2017; Van-

naprathip et al., 2016). However, as pointed out in

(Sipiyaruk et al., 2017), serious games have some lim-

itations and teachers should be cautious about the mix

up of education and gaming objectives by students.

The impact of these digital learning tools on the

performance of dentistry students has been studied

with some detail, but no consensus has been reached

in this regard. While some studies suggest a positive

impact (Busanello et al., 2015; Ratka-Kr

uger et al.,

2018), other found no statistically signiﬁcant impact

when comparing traditional teaching techniques with

new computer-supported teaching techniques (Amer

et al., 2011). Indirect measures of the effectiveness

of digital learning tools can also be found in the lit-

erature. One example is the work of (Jackson et al.,

2018) studying the usage patterns of self-directed dig-

ital learning tools and ﬁnding a strong tendency to-

wards heavy usage in the days leading up to examina-

tions. Given that the heavy lifting of preparation for

examinations is usually left for 2 or 3 days before the

exam, the fact that students invest such valuable time

in digital learning tools is an indicator of their value.

This discrepancy could be explained, in part, by

exploring the adequacy of digital learning tools in dif-

ferent education levels. In this sense, (Browne et al.,

2004) found that face-to-face interaction was more ef-

fective for inexperienced learners (e.g. undergrad stu-

dents), while e-learning was more effective for expe-

rienced learners (e.g. professional dentists enrolled in

a continuous professional development program).

Finally, the literature on education and training

in digital technologies speciﬁc to the dentistry pro-

fession explores the transition towards a professional

practice with increasing number of digital compo-

nents and tools (Afshari et al., 2017), and the chal-

lenges of training dentistry students in techniques

such as CAD/CAM technologies, digital radiography,

or digital microscopy (Afshari et al., 2017; Brown-

stein et al., 2015; Farah and Maybury, 2009).

The literature reviewed in this section demon-

strates 3 main things; the adequacy of computer sup-

ported teaching methods in dentistry, the predomi-

nance of blended models over purely virtual models,

and the challenges and risks of the implementation of

digital learning tools in dentistry curricula. Of partic-

ular importance for this project, this literature shows

the importance of keeping a balance between gami-

ﬁcation and pedagogical elements in serious games,

and the importance of truly integrating digital learn-

ing tools as complements to face-to-face teaching.

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126

3 METHODOLOGY

The methodology followed in this research had three

main phases; a learning styles diagnosis, a scenario

design, and the development of the RealTeeth online

game. Finally, a pilot validation with a cohort of pre-

clinic students was performed.

In order to determine the best kind of content to

include in the simulations, a learning styles diagnosis

among pre-clinic endodontics students was performed

based on the visual, auditory, and kinaesthetic (VAK)

learning styles (Bandler and Grinder, 1990). A ques-

tionnaire with 40 closed-answer questions

was dis-

tributed in a cohort of pre-clinic endodontics students,

obtaining 32 fully answered questionnaires. The re-

sults of these questionnaires indicated that most stu-

dents were predominantly kinaesthetic (42%) or vi-

sual (39%) learners, while only 19% were predomi-

nantly auditory learners.

The main objective of this assessment was to pri-

oritize the time and resources devoted to the different

kinds of materials that could be included in this type

of simulations. With that in mind, and considering

that only 19% of students are predominantly auditory

learners, no auditory elements will be included in the

simulation. Visual learners, on the other hand, rep-

resent 39% of students. Hence, the simulation will

be rich in visual aids like x-rays and photos from

real cases to guide the user experience. Kinaesthetic

learners are a challenge because kinaesthetic learn-

ing implies movement and usage of tools. However,

since this project is focused on semiological compe-

tences, which have little intersection with movement

in the case of endodontics, no real kinaesthetic ele-

ments will be included in the simulation.

The scenario design phase focused on the design

of user experience and the learning experience for the

students. This included a case model, an evaluation

model, and a gamiﬁcation context design. This was

done in conjunction with the current teachers of the

pre-clinic endodontics courses. These designs were

later used for the development of RealTeeth, which

was done following a Scrum software development

lifecycle to allow for constant validation and feedback

from the endodontics teaching team. For a pilot vali-

dation, RealTeeth was then deployed and tested with

a cohort of 19 dentistry students and 3 domain expert

(see Figure 2).

Since this paper reports only on the initial devel-

opment of RealTeeth, the results from the pilot valida-

tion phase are commented in section 4.3, but haven’t

been included nor implemented at the time of writing.

The questionnaire was taken from (De la Parra Paz,

2004, p. 85)

Figure 2: Pilot test of RealTeeth.

4 REALTEETH

RealTeeth could be described as a patient simulator

that was designed and developed as an answer to the

challenges for endodontics education in the Pontiﬁcia

Universidad Javeriana (see section 1). It covers the

two pre-clinic courses and the elective course; and

contributes to the knowledge, competence, and per-

formance levels of Miller’s pyramid. Furthermore, it

includes gamiﬁcation elements to facilitate and stim-

ulate usage and learning from endodontics students.

To facilitate it’s deployment and usage, it is built as a

web application.

RealTeeth puts the student in the place of a newly

graduated dentist looking for a job position at a big

dentistry practice. In order to get the job, the student

has to show his or her endodontics skills by diagnos-

ing 10 patients (see Figure 3). Once the 10 virtual

patients are diagnosed, the student will be classiﬁed

in a basic-intermediate-advanced scale. Students with

an advanced classiﬁcation will be offered the position

of Chief Endodontist. Students with an intermediate

classiﬁcation will be offered the position of Junior En-

dodontist. Finally, students with a basic classiﬁcation

will see their job application rejected.

Every student starts at a basic level and will be

Development of Diagnostic Skills in Dentistry Students using Gamiﬁed Virtual Patients

127

Figure 3: RealTeeth welcome screen for students.

presented with basic-level cases until he or she ad-

vances to the intermediate level. In order to do this,

the student has to get three consecutive basic-level

cases right. Once this happens, the student will be

presented with intermediate-level cases. If the student

is capable of getting three consecutive intermediate-

level cases right, he or she will move to the advanced

level and will be presented with advanced-level cases

(see Figure 4). The student will be demoted to the

previous level if he or she fails a case.

Figure 4: RealTeeth dashboard screen for students.

The cases are structured around the standard diag-

nosis protocol in endodontics (see Figure 5). Cases

have 5 possible diagnostic routes; pain assessment,

clinical exam, periapical tests, sensibility tests, and

x-rays. The student can choose any of the 5 diagnos-

tic routes to start his diagnosis. Each diagnostic route

will give different information, and some of them (e.g.

x-rays or clinical exam) will show images or photos

(see Figure 6). Additionally, each diagnostic routes

allow the student to ask questions and RealTeeth will

provide answers

. At the end of a diagnostic route the

The nature of the questions and answers depends on

the nature of the diagnostic route. The clinical exam, for

example allows the student to ask additional questions to

the patient and RealTeeth will show the answer given by

the patient. X-rays, on the other hand, allow the student to

ask questions about the x-ray and RealTeeth will provide

expert answers.

student has to reach a conclusion based only on the

information provided by the route (see Figure 7). Af-

ter completing the 5 diagnostic routes the student can

ﬁnally provide a diagnosis (see Figure 8). Based on

the conclusions of the 5 diagnostic routes and the ﬁ-

nal diagnosis, the case is evaluated using a rubric and

provides feedback to the student (see Figure 9).

has a

answers

offers

1..*

reaches a

evaluated by

considers

Case

Diagnostic route Question

Student

Level

High Medium Basic

Answer

Rubric

Conclusion

Diagnosis

Figure 5: Case model.

The use protocol is as follows (see Figure 10).

The student starts by seeing an introductory screen ex-

plaining the rules of the game. The student then starts

with the ﬁrst case in basic level. A case introduction

is shown at the beginning of each case with informa-

tion regarding the reason for consultation given by the

patient. Later, the student can choose one of the ﬁve

diagnostic routes and follow it until a conclusion is

reached on that route. When the student completes

the 5 routes, a diagnosis must be given. The case will

be evaluated using a pre-deﬁned rubric and the stu-

dent will be informed if the case was passed or not.

Based on previous performance, the student will be

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128

Figure 6: Main screen of the x-ray examination diagnostic

route.

Figure 7: Analysis screen of the x-ray examination diagnos-

tic route.

promoted or demoted. This process will be repeated

until the student completes 10 cases. Once this hap-

pens, the result of the game session will be shown to

the student.

The interaction between the student and RealTeeth

throughout this process is form-based and gives a

great deal of control to the student. In this sense, the

student can choose where to start (i.e. the order of the

diagnostic routes) and the order in which to ask ques-

tions to the system. The student can also go back to

previous diagnostic routes to double check informa-

tion or change his or her diagnostic. After the ﬁnal

diagnosis is made, the student is shown if this diag-

nosis is correct or not. Additionally, the details of

the evaluation (i.e. the full rubrics for every diagnos-

tic route) is shown (see ﬁgure 9) in order to allow the

student to analyze his or her performance and identify

any weaknesses that should be addressed.

4.1 Case Design and Teacher-oriented

Features

This initial version of RealTeeth offers 4 features for

teachers: case creation, case editing, case search, and

case removal.

The case creation feature allows teachers to create

a complete case, including case description, basic in-

formation for the 5 diagnostic routes, uploading of x-

rays and other images used in the case, the questions

and answers of each diagnostic route, the conclusions

for each diagnostic route, the right diagnosis for the

case, and the evaluation rubric.

The case editing feature allows teachers to modify

the information and structure of a pre-deﬁned case.

This was proven to be of key importance during our

pilot validation of RealTeeth since even though the

cases were designed by experts on the ﬁeld, some mi-

nor errors where discovered in the cases. These errors

where detected when too many students were fail-

ing the same case, when students capable of reaching

an advanced level were consistently failing the same

lower-level case, or when differences of opinion about

a case level arouse among the teaching team.

The case search feature allow teachers to ﬁnd

cases based on the difﬁculty level.

Finally, the case removal feature allow teachers to

delete one or multiple cases.

4.2 System Architecture

RealTeeth was developed using a traditional web-

oriented architecture following the Model-View-

Controler (MVC) pattern. The backend was devel-

oped in PHP using the Symfony 2.7 framework. The

frontend was developed using Javascript, HTML 5

and CSS 3. Finally, MySQL was used as DBMS. The

system was deployed using Amazon Web Services.

Speciﬁcally, AWS EC2 was used to host RealTeeth,

and AWS RDS was used to handle the database (see

Figure 11). It is important to note, however, that Real-

Teeth can be deployed in any linux-based server with

Apache Web Server, PHP, and MySQL installed.

4.3 Pilot Validation

Two kinds of tests were done in RealTeeth: functional

testing and usability testing.

The functional testing was done using the

PHPUnit testing framework and following the Clean

Code (Martin, 2009) and SOLID principles (Arora,

2017). Additionally, RealTeeth has been tested in

the latest versions (at the time of writing) of Google

Chrome, Mozilla Firefox, and Safari web browsers.

Development of Diagnostic Skills in Dentistry Students using Gamiﬁed Virtual Patients

129

Figure 8: Case diagnosis screen.

Figure 9: Results and feedback screen.

The usability test was done using a survey handed

to the 19 students that participated in the pilot test

of RealTeeth. This usability test evaluates the effec-

tiveness, efﬁciency, and user satisfaction of RealTeeth

following the ISO 9241-11 and ISO/IEC 9126-4 stan-

dards. The main results from this usability test are

that the gamiﬁcation elements included in RealTeeth

were well understood and accepted by the students.

However, a general comment was that these gamiﬁca-

tion elements should be further developed to increase

the motivation of the student. Some ideas gathered

in the questionnaire included stating different salaries

for the different job positions offered at the beginning

of the game, or including different perks associated

with each job position. This highlights the importance

of gamiﬁcation to ensure user engagement in digital

learning tools.

Regardless of some user interface problems (e.g.

button placement, text size and fonts, confusing nav-

igation at especiﬁc points, etc.), the pilot validation

could be considered a success. Furthermore, and re-

gardless of these navigation issues, the students seem

very satisﬁed with RealTeeth, with 100% stating that

the information provided in RealTeeth was close to

real-life cases and 81% stating that they would like to

use RealTeeth frequently. Finally, some of the com-

ments made by the students include “this is something

new in pre-clinic and would be interesting to use it

during the semester”, “this was an interesting exer-

cise and we’ve never done anything like this before”,

and “this helps to close the gap between theory and

practice”. This shows that RealTeeth was capable of

fulﬁlling the objective highlighted in section 1.

5 LESSONS LEARNED AND

FUTURE WORK

The pilot validation of RealTeeth suggests that it has

high acceptance levels from both students and fac-

ulty. Additionally, there seems to be a high percep-

tion of usefulness coming from students and faculty.

But regardless of this positive attitude towards Real-

Teeth, or digital learning tools in general, this expe-

rience yielded valuable lessons for future versions of

RealTeeth.

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130

Figure 10: RealTeeth use protocol.

User Device

Amazon EC2

RealTeeth

Amazon RDS

MySQL

+HTTP

+Doctrine/ORM

Figure 11: Deployment diagram for the RealTeeth system.

The ﬁrst lesson is that digital learning tools should

be designed for classrooms and not for individual stu-

dents. This was evident in the case creation-process,

especially when it came to assigning a difﬁculty level

to the cases. The current version of RealTeeth relies

on expert opinion (i.e. faculty member) as the only

input to assign the difﬁculty level to cases. However,

since case difﬁculty is subjective, some difference of

opinion did arise during this process. Having more

input sources, such as the historical performance of a

good amount of users, will allow for a more objective

and dynamic assignment of difﬁculty levels. In this

sense, future versions of RealTeeth should be able to

consider the performance of several students in each

case to provide information usable for, for example,

assigning the difﬁculty level of cases in a dynamic

and objective manner, ﬂagging cases with incomplete

or inconsistent information (e.g. cases in which even

high-performing students fail consistently), and dis-

covering topics that should be revisited in class or in

external tutoring sessions (e.g. topics that are heavily

present in cases in which a particular set of students

are showing an atypical failure rate).

Additionally, this would allow for the inclusion of

further gamiﬁcation elements like students leagues or

leaderboards.

A second lesson was the importance of deep per-

sonalization of the user experience according to pre-

vious performance. In its current version, RealTeeth

only uses the difﬁculty of previous failed/passed cases

in order to select the next case for the student. How-

ever, since diagnosis skills are multidimensional, fac-

ulty member expressed their desire for cases to be se-

lected not only based on difﬁculty level but also on di-

agnosis dimension. In this sense, a student with prob-

lems in one diagnosis dimension will be shown cases

that focus on that particular dimension (i.e. cases in

which the most important information is in the x-ray

evaluation or cases in which the most important infor-

mation is in the periapical test). The student can also

be given the option to select a diagnosis dimension to

use in a particular RealTeeth session. This will allow

students to identify and work on their weaknesses or

to focus their preparation for speciﬁc examinations.

Beyond these lessons, this experience, coupled

with the literature review shown in section 2, can be

used to inform the research agenda on computer sup-

ported education in the ﬁeld of dentistry.

The ﬁrst and perhaps more important area of fur-

ther research is the impact of digital learning tools in

dentistry education and the factors that determine this

impact. As shown in section 2, there is no consensus

on the impact of digital technologies on the perfor-

mance of dentistry students or professionals. Addi-

tionally, there seems to be external factors (i.e. fac-

Development of Diagnostic Skills in Dentistry Students using Gamiﬁed Virtual Patients

131

tors that are not within the boundaries of the digital

learning tool) that determine the impact of these tools

on the performance of students (Browne et al., 2004).

More research on this area is imperative not only to

determine if digital learning tools do indeed have a

positive impact on student’s performance (hence mak-

ing them worthy of attention by researchers on the

ﬁeld and dentistry schools) but also under what con-

ditions (hence triggering changes in course design, in-

structional design, curricula, or classroom material).

The second area of further research is inspired by

(Bravo-Torres et al., 2017), and (Jackson et al., 2018)

and has to do with the adoption and usage pattern of

digital learning tools by students, faculty, and schools.

Key questions on this regard include what are the

adoption factors of digital learning tools in the ﬁeld of

dentistry?, what is the pattern followed by this adop-

tion?, what usage is given to digital learning tools by

dentistry students and faculty members?, and what is

the relationship between digital learning tools and tra-

ditional training in the ﬁled of dentistry?. Addition-

ally, for the case of serious games, and following the

ﬁndings of (Sipiyaruk et al., 2017), it is important to

do more research on the prevalence of learning objec-

tives over gaming objectives of serious games.

Finally, it is important to note that most research

on the ﬁeld is centred on students and there is little

work centred on faculty members or schools. More

research tackling the role, challenges, and impacts of

this set of actors in computer supported education in

the ﬁeld of dentistry is much needed.

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