Ontology-based Representation of Digital Devices

Used in Educational Guidance

Marie Gribouval

, Cecilia Zanni-Merk

2 a

and Davy Monticolo

1 b

ERPI, Lorraine University, Nancy, France

LITIS, Rouen University, Rouen, France

Keywords:

Ontology, Digital Device, Educational Guidance.

Abstract:

School counseling is a decision-making process in which high school students have to decide what higher

education course they will register for. Many digital devices support high school students in this guidance

process. Given the diversity of architectures and services offered by existing devices, the main goal of this

project is to predict their impact on high school students.

It is necessary, therefore, to propose a formal characterization of digital devices for school counseling. This

paper proposes an ontology to represent knowledge of digital guidance devices. An instantiation of the ontol-

ogy is performed for each device to be studied.

The ontology is built to be able to identify the different functions of the digital devices, their types, and the

relationships between the tools of the digital devices and the guidance actors.

The ontology includes the tools that the user may use, the topics covered by the device, the elementary com-

ponents, and the support used (mobile application, computer application, or website).

1 INTRODUCTION

In school counseling, various devices support the high

school student guidance. We focus here on the study

of the analysis of digital devices dedicated to guid-

ance. The term digital device is a broad notion that

includes tablets, mobile phones, and laptops (Vilo-

ria et al., 2020), (Lam and Tong, 2012) but also in-

cludes the interaction between the user and a digital

tool (e.g. the possibility to change the display of con-

tent)(Treleani, 2014). As the difference between the

terms platforms, devices, resources, and digital envi-

ronment is not always clear (Durand et al., 2015), it

is necessary to deﬁne a digital device in our context.

Here we consider a digital platform as an ”extensi-

ble codebase of a software-based system that provides

core functionality shared by the modules that interop-

erate with it and the interfaces through which they in-

teroperate”, modules allow additional functionality to

be added to the platform (Tiwana et al., 2010).

Using this deﬁnition, we consider immersive

worlds, websites, and mobile applications. Not all

have the same architecture, some devices offer an ex-

https://orcid.org/0000-0002-5189-9154

https://orcid.org/0000-0002-4244-684X

change tool, while others do not but have a job direc-

tory for example. In the context of guidance, digital

devices do not all have the same objectives; some aim

to inform, others to answer questions or to give ideas

about careers. The motivation for this work lies in the

fact that there is a diversity of architectures and ser-

vices offered by existing devices. We propose to carry

out a comparison and an evaluation of the latter. The

ﬁnal goal of this project in the future is to predict the

impact of the digital devices on the users, i.e. on the

students during their orientation process, for device

developers.

It is necessary, therefore, to propose a formal char-

acterization of digital devices for school counseling.

With this aim, this paper proposes an ontology as a

representation of digital guidance devices. Ontolo-

gies have appeared as suitable tools to represent the

digital devices used in educational guidance. Accord-

ing to Gruber et al. (Gruber, 1993) an ontology is ”an

explicit speciﬁcation of a conceptualization” and Noy

et al. (Noy et al., 2001) “properties of each concept

describing various features and attributes of the con-

cept, and restrictions on slots”.

In this paper an ontology-based representation to

characterize the digital devices related to guidance is

proposed. The remainder of the paper is structured

200

Gribouval, M., Zanni-Merk, C. and Monticolo, D.

Ontology-based Representation of Digital Devices Used in Educational Guidance.

DOI: 10.5220/0011551700003335

In Proceedings of the 14th International Joint Conference on Knowledge Discovery, Knowledge Engineering and Knowledge Management (IC3K 2022) - Volume 2: KEOD, pages 200-206

ISBN: 978-989-758-614-9; ISSN: 2184-3228

as follows: Section 2 presents a review of ontology-

based approach to characterize the digital devices or

to characterize the guidance process. In section 3 we

describe existing digital devices. Section 4 gives an

overview of the proposed ontology. Finally, conclu-

sions and perspectives are given in Section 5.

2 PREVIOUS WORK

Ontologies serve as a unifying framework for dif-

ferent points of view and capture the concepts used

and the relationships between these concepts (Gan-

don, 2002) using a common vocabulary (Noy et al.,

2001). Ontologies have several types of components:

• Classes: they represent the relevant concepts in

the domain of interest and group objects sharing

characteristics. They can contain instances and

have subclasses.

• Relationships: these are used to link concepts to-

gether.

• Instances: these are named and concretely identi-

ﬁable objects.

The construction of an ontology requires deﬁning,

identifying, and prioritizing these components in a

speciﬁc domain of interest. Concerning educational

ontologies, there exist several widely accepted and

reusable ontologies across different applications.

Delestre et al. have proposed a description stan-

dard for education in France, part of which is repre-

sented as an ontology (Delestre et al., 2019). The on-

tology is a description of educational resources, these

resources are notably linked to a ”target audience”,

and have ”learning activities”. Bourdeau et al (Bour-

deau et al., 2007) also propose an ontology in the ﬁeld

of education, their ontology is learner-centered. It

allows for a description of the learner, such as their

behavior, knowledge, and level. Learning is a do-

main in which several researchers wish to build on-

tologies since we also ﬁnd the OMNIBUS ontology

(Mizoguchi and Bourdeau, 2016). This ontology aims

to help educational staff to apply knowledge from ed-

ucational theories and to establish a method to build

educational systems taking theories into account.

E-learning is a domain close to digital guidance

devices since high school students using a digital

guidance device are likely to be in a learning process.

Guinebert et al (Guinebert et al., 2017) and Bennani et

al (Bennani et al., 2020) deal with this domain using

ontologies. The former (Guinebert et al., 2017) use

their ontology to describe the scenario of the educa-

tional game, the roles that the players can take. This

ontology describe the objective of the game and that

of the teacher. Bennani et al (Bennani et al., 2020)

have created an ontology on adaptive gamiﬁcation in

e-learning, which allows for example to represent the

user, the interactions, and experiences he can have.

The adaptation to the user of the digital device is also

treated by Bacha et al (Bacha et al., 2010) but this

time without the notion of a game, their ontology al-

lows them to describe the user (his proﬁle, his prefer-

ences, ...), the platform and the environment in which

the user uses the platform (location, date, ...).

The ontologies presented above allow for the de-

scription of the learner or user of the device in context

but take less account of the tools available to the user

or the type of interface with which the user interacts.

3 EXISTING DIGITAL DEVICES

Existing digital devices have varying objectives,

themes, or media. It is interesting to present some

of them to illustrate this diversity and therefore the

difﬁculty that there may be in uniformly representing

them.

Some schemes are intended to be available one

day a year, operating similarly to face-to-face guid-

ance days. For example, the digital device Virbela

was used for the CapSup 4.0 day (part of the Print-

emps de l’orientation) on 16 March 2021 (Gribouval

et al., 2021). The CapSup day is an event that re-

groups higher education courses. It aims to introduce

high school students to the various courses available

in higher education and provide guidance counseling.

Virbela platform (https://www.virbela.com) is an im-

mersive 3D world, each user is represented by a char-

acter. The user can move his character in the virtual

world.

Other devices have elements available that

vary throughout the year, such as Parcoursup

(https://www.parcoursup.fr). To access it, you have

to be a high school student, and depending on the

trimester of the year and therefore the orientation

stage, the content varies to follow the high school stu-

dent from his or her reﬂection to the validation of his

or her higher education choices. For example, be-

tween 20 January and 20 March, high school students

in their ﬁnal year had to register on the platform and

add their post-bac training wishes.

A larger number of devices are accessible all the

time so that students can go to them at any time of the

year when they feel the need. Within this set of con-

tinuously accessible facilities, not all offer the same

services. Some have focused on providing a wide

range of information and offer numerous pages on

careers, student life, and the various diplomas, as is

Ontology-based Representation of Digital Devices Used in Educational Guidance

201

the case with the Onisep site (https://www.onisep.fr).

Another existing possibility is that of systems focus-

ing on one type of information. This is the case of

the Wilbi mobile application (https://wilbi-app.com),

which deals only with careers, and is designed to re-

semble the mobile applications that high school stu-

dents are usually used to using. It is profession-

als themselves who ﬁlm small parts of their day to

present their job. Some devices offer little infor-

mation content but aim to help high school students

get to know themselves better through tests. This

is the case, for example, with the Hello Charly ap-

plication (https://hello-charly.com/), which is a robot

that asks multiple questions during a conversation and

then proposes ideas for jobs that match the student’s

proﬁle.

The ontology proposed in the following section al-

lows these devices to be represented through instanti-

ations of the ontology.

4 ONTOLOGY-BASED

PROPOSAL REPRESENTATION

Various methodologies exist for developing an ontol-

ogy, several of which are presented in (Cristani and

Cuel, 2005). We have chosen to use an evolving pro-

totype model because this type of model is adapted

to a dynamic or difﬁcult-to-understand environment.

The second type of model is the stepwise model for

problems where the objective and requirements are

clear. The model chosen is ”Ontology Development

101” (Noy et al., 2001) as it is cited in a various re-

search documents and presents a detailed deﬁnition to

each step.

4.1 Ontology Development

The ﬁrst step in building the ontology is to deter-

mine the domain and scope. Our ontology should al-

low us to characterize digital devices related to school

guidance and to understand how we relate to digital

devices and school guidance. The ontology is con-

structed in such a way that it can answer the following

questions:

• What are the different functions of digital devices

for guidance?

• What are the different types of digital devices for

guidance?

• What are the relationships between the tools of

digital devices and guidance stakeholders?

The second step in this construction is to list exist-

ing ontologies that can be used for our problem. We

started by doing a broad search of existing ontologies

in the ﬁeld, including those dealing with the guidance.

As these ontologies do not consider digital devices,

we looked for ontologies dealing with digital devices

in the ﬁeld of the training process. The ontologies

presented in the section 2 do not include a description

of digital devices.

The ”Web content accessibility guidelines” (Cald-

well et al., 2008), although not a taxonomy or ontol-

ogy, lists the important elements present in a digital

device. It is a guide to making web content more ac-

cessible to people with disabilities such as blindness

or deafness.

These references help to create a list of important

terms of the ontology and to create a hierarchy be-

tween them. This is the 3rd and 4th step in the con-

struction of the ontology. To create a fairly exhaustive

list of terms, the functionalities of several guidance

systems are observed (Table 1). We have chosen these

devices because they are among the most frequently

used devices and represent a variety of devices (they

do not all have the same objectives, the same sup-

ports). In the functionalities, we can ﬁnd tests sug-

gesting jobs according to one’s favorite ﬁelds, and

communication tools allowing to ask questions to stu-

dents.The observation of existing devices when cre-

ating the ontology avoids problems of inconsistency,

allows for self-explanatory and easy-understandable

models (Peroni, 2016).

Table 1: Table of digital guidance devices observed.

Name of the

digital device

Device link

Onisep https://www.onisep.fr

Pixis https://pixis.co

Quel m

etier https://www.quelmetier.fr

Bloom’r https://www.bloomr.org

eration15-25 https://www.generation1525.fr

Recto Versoi https://www.recto-versoi.com

Jobirl https://www.jobirl.com

Study Advisor https://www.studyadvisor.fr

Wilbi https://wilbi-app.com

We chose to create the ontology using Prot

(https://protege.stanford.edu).

4.2 General Overview of the Ontology

The instantiations of the ontology should highlight the

differences between the digital devices.

The main class ”DigitalDevice” is instantiated for

all the digital devices studied. The instance name cor-

responds to the device name. We consider digital de-

vices as having some tools, at least one subject, one

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Figure 1: Extract from the representation of the proposed ontology.

user interface, exactly four impacts (behavior, knowl-

edge, experience, attitude), and one support (e.g. a

mobile application).

Others ontology classes should consist of their

main characteristics.

An important point of distinction is the content(s) ad-

dressed by the device. Thus, the content class identi-

ﬁes the topics that each digital device deals with. Its

sub-classes are the possible subjects treated, for ex-

ample, information on jobs, on student life, ...

The tool class is also one of the main classes as

it contains the tools that can be present in digital de-

vices. The tools can be exchange tools, directories, or

tests.

It is the ”hasInformationContent” (respectively

”hasTool”) relationships that link the ”DigitalDe-

vice” class with the ”InformationContent” (respec-

tively ”Tool”) class.

An overview of the classes and properties from the

proposed ontology is shown in Figure 1. This ﬁgure

is an excerpt of a larger ontology that can be found

in our code (https://github.com/MarieGribouval/

OntologyDigitalDeviceForGuidance).

During the ﬁrst instantiation of the ontology for

a given device, we realised that the process of creat-

ing an instance for each page and each page subject

was too time consuming. Indeed, for the Onisep site,

792 instances would have had to be created to repre-

sent each job description in addition to all the other

domains covered by the site. This ﬁrst instantiation

led to a fairly signiﬁcant modiﬁcation of the ontol-

ogy. Boolean data properties were added in order to

simplify the instantiation process of each device (for

example, the instances of the Tool class require or do

not require authentication).

Moreover, the stages of the orientation process

that we initially thought to include were not included

in the end because when using the ontology in a con-

crete case the context of use of each student is very

variable, the device can generally be used by a stu-

dent at any time.

The complete set of concepts and their deﬁnitions

is presented in Table 2, including the hierarchy be-

tween the classes. To describe and link these con-

cepts, some relations are proposed. The ontology con-

sists of 23 concepts, 9 object properties and 9 data

properties.

The object properties are shown in Table 3,

the object properties not shown are the inverse

object properties, for example, the inverse prop-

erty of ”hasElementaryComponent” is ”ifElemen-

taryComponentOf”.

Table 3 presents the data properties. These four

data properties are of boolean type, i.e. they have the

value ”true” or ”false”.

When instantiating the ontology for each digital

device, we also use the inference engines available in

Prot

e. The inferences allow us to check that the in-

stantiation constructed is consistent (e.g. that a class

is not put with a data property that does not match)

and also to facilitate development by inferring im-

plicit knowledge.

Ontology-based Representation of Digital Devices Used in Educational Guidance

203

Table 2: Table of ontology concepts and their associated deﬁnitions.

Concept Deﬁnition

Digital Device Digital object with user interface(s), information, support and

possibly tools

Digital Device Support The digital device can be a mobile application, a computer ap-

plication or a website

Elementary Component Represents all audio, external, and internal hyperlinks, images,

texts, and videos

Impact A very strong impression or effect left on someone as a result of

an action or event

Information Content The subject of all or part of the digital device

About the Device Informa-

tion

Description of the purpose of the device, and its members

Employment Internship In-

formation

Job offers or internships, or advice on them (e.g. writing a cover

letter)

Guidance Information Information on path chosen as part of their studies

High School Information Information about secondary school (from the second to the ﬁnal

year).

Job Information Information about regular and paid professional activity

Post Secondary Education

Information

Information related to higher education

Training Institution

Information

Information on post-baccalaureate institutions

Training Diploma

Information

Information related to post-baccalaureate training or act confer-

ring and attesting a title, a rank

Psychology Personality In-

formation

Information related to one’s personal internal functioning (e.g.

how to know what one’s aspirations are).

Student Life Information Information about student life (e.g. about student accommoda-

tion)

Interlocutor Entity or individual with whom the user can exchange (i.e. trans-

mitting something and receiving something - where the thing

transmitted can be audio, video, text, images -)

Test Subject The result of the test can give information on the user’s interests,

jobs that correspond to them, or their personality

Type Directory The directory can be used to list schools, students, training

courses, high school students, professions, guidance profession-

als, or professionals for a particular profession

Tool A set of tools that the user can have at his disposal in a digital

device

Directory Tool storing information (people, institution, job, training). The

information can be obtained through ﬁlters and a search bar

Exchange Tool A tool for exchanging (i.e. transmitting something and receiving

something - where the thing transmitted can be audio, video,

text, images -)

Test A form that the user can complete and which returns a result

User Interface Allows you to describe whether it is a ”classic” interface per

page or an immersive world

4.3 Ontology Evaluation

We evaluate the ontology according OOPS!

(https://oops.linkeddata.es/). The OOPS! tool

can also identify errors in an ontology. It detects

structural errors (the syntax and formal semantics),

functional errors (considers the intended use and

functionality of the proposed ontology), and usability

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204

Table 3: Table of object and data properties used.

Object properties Deﬁnition

hasDigitalDeviceSupport Relation denoting that an entity has a digital device support

hasElementaryComponent Relation denoting that an entity has an elementary component

hasImpact Relation denoting that an entity has an impact

hasInformationContent Relation denoting that an entity has content

hasInterlocutor Relation denoting that an entity allows communication with an inter-

locutor

hasTestSubject Relation denoting that an entity has a test subject

hasTool Relation denoting that an entity has a tool.

hasTypeDirectory Relation denoting that an entity has a type directory

hasUserInterface Relation denoting that an entity has a user interface

Data properties Deﬁnition

allowsImmediacy Relation denoting that an entity for immediacy or not

containsFaq Relation denoting that an entity has a set of frequently asked questions

containsTestimonial Relation denoting that an entity owns a testimonial or not

hasImpactAttitude Relation denoting that an entity has an impact on attitude and gives the

value of that impact

hasImpactBehaviour Relation denoting that an entity has an impact on behaviour and gives

the value of that impact

hasImpactExperience Relation denoting that an entity has an impact on experience and gives

the value of that impact

hasImpactKnwoledge Relation denoting that an entity has an impact on knwoledge and gives

the value of that impact

hasVideo Relation denoting that an entity owns a video or not

requiresAuthentication Relation denoting that an entity requires an authentiﬁcation or not

proﬁling errors (communication context of an ontol-

ogy) (Poveda-Villal

on et al., 2014). Using OOPS!

on our ontology gives the result in Figure 2. The 43

minor errors are due to the lack of annotation for

classes and data properties. The major error is caused

by the lack of a license speciﬁcation, this does not

impact the current operation of the ontology. We will

have to ﬁx it when we make the ontology available.

Figure 2: Screenshot of the results of the OOPS evaluation

of our proposed ontology.

5 CONCLUSION AND FUTURE

WORK

The ontology proposed here allows us to characterize

digital devices related to school guidance by describ-

ing them according to their tools, content, the sup-

port used, and elementary components. To do that,

an instantiation of the ontology is performed for each

device to be studied. Instantiation from an initial on-

tology allows each device to be represented uniformly

and thus makes a formal comparison between devices

possible. The use of an ontology to represent digital

devices allows reasoning during instantiation and thus

verifying the consistency of the instantiation as it is a

manually performed task. Moreover, ontologies allow

the possibility of adding other concepts or relations if

in time other very different devices emerge.

In the future, we would like to obtain the impact

of digital devices on high school students. This mea-

sure is the key point of this research. We will need

a prediction algorithm to determine the impact. In-

deed, calculating the impact of a device will require

the intervention of an expert or the use of an evalua-

tion method because calculating an impact is a com-

Ontology-based Representation of Digital Devices Used in Educational Guidance

205

plex process that will require multiple knowledge.

The instantiations of the ontology will provide one

part of the uniform description of the devices. The

second part of this description will consider the us-

ability of devices. Usability is the effectiveness, efﬁ-

ciency, and satisfaction with which the user achieves

his or her goals using the digital device (Mustafa and

Al-Zoua’bi, 2008). Usability data will collect using a

questionnaire.

Thanks to this ontology-based characterization and

usability data, which will provide a uniform descrip-

tion of the devices, will allow us to calculate the simi-

larity between different digital devices. The similarity

calculation will be used when predicting the impact.

The similarity measure will be used in a case-based

reasoning algorithm by calculating the similarity be-

tween the device whose impact is to be predicted and

devices whose impact is known. Each device will be

represented by a uniform description which is an in-

stantiation of the ontology and usability dataset and

by an impact value. The case-based reasoning will al-

low for expanding a knowledge base (i.e. the set of

pairs (ontology instantiation and usability data, im-

pact)). This knowledge base enrichment will be of

interest in our problem because we will have a small

amount of impact data initially and it will increase the

quality of impact prediction for new digital devices.

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