PBLOntology: A Domain Ontology with Context Elements for

Problem-based Learning

Adriana Silva Souza

, Adolfo Duran

and Vaninha Almeida

Bahia Federal Institute of Education, Science and Technology, Porto Seguro, Bahia, Brazil

Information Technology Superintendence, Federal University of Bahia, Salvador, Bahia, Brazil

Department of Computer Science, Federal University of Bahia, Salvador, Bahia, Brazil

Keywords: Problem-based Learning, Ontology, Context.

Abstract: In education, ontologies have been proved useful for structuring intelligent tutors, collaborative learning,

creation of learning models, semantic search for recommendation of learning material, personification and

adaption of educational content based on the student’s context. Problem-Based Learning (PBL) is a

pedagogical methodology that is regarded as an alternative to traditional learning for skills development.

However, the use of web-based technologies to support learning in the PBL methodology is still recent. A

systematic review was conducted and it has shown the lack of formal representation of the PBL concepts

based on ontology language. Thus, this paper proposes a reference ontology for PBL called PBLOntology,

which uses context elements of the methodology. For conception of the ontology, a research was conducted

in a computer-engineering course that adopts the PBL methodology. To assess the PBLOntology, we

defined relevant criteria regarded as fundamental for ontologies: testing activities and evaluation with

experts. Although most of the experts stated that the definitions satisfied or partially satisfied, their feedback

allowed us adjust some definitions, improving the ontology.

1 INTRODUCTION

In the era of information, it is imperative that

students develop mechanisms to build their own

knowledge in an autonomous way, by developing

multiple abilities and skills (Álvarez et. al, 2005). A

pedagogical methodology suitable to this scenario is

the Problem-Based Learning (PBL). It aims to

encourage students to develop critical thinking,

problem solving skills, self-learning, collaboration

and communication skills, among others, by means

of problem solving, which may not have a unique

solution and are often complex (Ribeiro, 2005).

The Semantic Web has enabled the development

of personalized learning environments and new

forms of collaborative and interactive learning,

contributing to a more active and dynamic process

of teaching and learning (Kasimati and Zamani,

2011). In this scenario, ontologies have been

proposed for learning environments in order to

promote semantic interoperability, sharing, and

learning customization (Gaeta et. al, 2009).

The student learning behavior can change

according to the environment in which he/she

interacts. This learning context includes for instance,

the style and speed of learning, the time available,

the location, personal interests, among others that

can contribute to semantically enrich the process of

teaching and learning (Medeiros et. al, 2010).

The student context is useful to define the

student profile, recommend learning objects,

personalize and customize content. Context-sensitive

learning environments have also applied ontologies

to model context (Barbosa, 2009; Maran and

Bernardi, 2014).

The use of web-based technologies to support

learning in the PBL methodology is still recent

(Brush, 2013; Sobocan, 2017). Souza et. al (2014)

conducted a systematic review in order to search for

evidences of semantic web technologies for PBL. It

was not found in the literature a formal

representation of the PBL concepts based on

ontology language, which would result a common

and shared understanding, available for reuse.

The development of an ontology for PBL process

could be useful for: (i) interoperability among

systems using PBL; (ii) developing of intelligent

systems and agents to assist the tutoring stage of the

methodology; (iii) to assist the recommendation and

adaptation of content at the research phase of the

376

Souza, A., Duran, A. and Almeida, V.

PBLOntology: A Domain Ontology with Context Elements for Problem-based Learning.

DOI: 10.5220/0006804903760383

In Proceedings of the 20th International Conference on Enterprise Information Systems (ICEIS 2018), pages 376-383

ISBN: 978-989-758-298-1

process PBL; (iv) to assess the accomplishment of

the PBL process in distance education systems; (v)

inferences and analysis on the development of skills

and abilities proposed by the methodology.

This paper proposes a reference ontology for

PBL called PBLOntology, product of a shared and

consensual knowledge, bringing contextual elements

of the methodology into this ontology. For its

conception, we conducted a case study based on

observations, questionnaires and interviews within

the course of Computer Engineering in the State

University of Feira de Santana (UEFS), Brazil.

The PBLOntology was instantiated using actual

data. Its concepts were assessed in two ways:

through testing and by the evaluation with domain

experts. Essentially this ontology consists of a

computational artifact that can be shared, reused and

enriched both by researchers and professionals

willing to develop semantic-based applications for

PBL.

The remainder of the paper is structured as

follows: Section 2 presents the PBL methodology;

Section 3 briefly describes some related works;

Section 4 presents the PBLOntology and the

development steps; Section 5 discusses the

evaluation process and results; finally, Section 6

draws some conclusions and points out future works.

2 THE PBL METHODOLOGY

The PBL methodology emerged in the late 1960s in

the medicine program at McMaster University in

Canada, due to dissatisfaction and boredom of

students exposed to a large volume of knowledge

perceived as irrelevant to medical practice (Barrow,

1996). In Brazil, PBL has been adopted by medical

courses and has been also employed in many other

areas of higher education, such as pedagogy,

business administration, and engineering (Ribeiro,

2005).

A popular reference for PBL systematization is

the "seven steps" framework, proposed by the

Maastricht University (Deelman and Hoeberigs,

2009): (1) presentation of the problem and

enlightenment of unknown terms; (2) identification

of the problem posed by the statement; (3) problem

discussion and formulation of hypotheses to solve it;

(4) summarization of hypotheses; (5) formulation of

learning objectives. Based on prior knowledge, the

subjects to be studied for solving the problem are

identified; (6) self-study of the issues raised in the

previous step; (7) return to tutorial group to discuss

again the issue in the light of new knowledge

acquired in the self-study phase.

Figure 1: Conceptual Framework of the PBL

Methodology.

The PBL session begins with the presentation of

a problem to the group members, in which is raised

the problem scenario. After that, students perform

the collaborative whiteboard discussion. At this

stage, students identify ideas and facts, formulate

hypotheses, and define issues and learning goals.

After the whiteboard discussion, students perform

self-study to investigate the literature looking for

solutions to the issues identified in the previous step.

In the next step, students meet again in a tutorial

session to perform a new collaborative whiteboard

discussion, applying the new knowledge. New ideas,

facts, questions and goals can be identified within a

cycle of interactions until the problem resolution.

The Problem Solving stage consists of the

submission of a solution by means of the delivery of

a software, document, presentation, among other

deliverables. At the end of each problem, the

evaluation process is performed. Thus, the students

have the opportunity to reflect on the knowledge

built and to assess the problem, the tutor, the peers,

and themselves.

For the methodology to be effective, it is

necessary an active participation of the tutor

responsible for the group. The tutor acts on three

stages of the process: (i) Tutoring – monitors the

group throughout the PBL process, (ii) Diagnostic

evaluation – identifies students or tutorial group

weakness during the session and (iii) Formative

Assessment - evaluates the students development of

skills and competencies during the PBL process,

such as collaboration, communication, writing,

leadership, self-study, among others.

PBLOntology: A Domain Ontology with Context Elements for Problem-based Learning

377

3 RELATED WORKS

Jacinto and Oliveira (2008) present an architecture

based on ontologies, where each component of the

architecture is structured by an ontology, helping the

understanding of the concepts of each component

and consequently the promotion of interoperability

between models of architecture.

Fontes et. al (2011) propose a domain ontology

for PBL to facilitate an effective access to

information about the area. It states that an

important aspect to be considered in PBL is the lack

of standardization and uniformity of the concepts

related to PBL, hampering the common and shared

understanding of the domain.

Our work differs from the related works in the

following aspects: (1) our ontology considers the

context of the PBL sessions in the formalization

process; (2) the ontology presented in Fontes et. al

(2011) can not be reused because the author has not

shared the ontology in any repository and

unfortunately it is no longer available, whereas our

proposed ontology is available in a repository for

reuse; (3) the ontology shown in Jacinto and

Oliveira (2008) is not specific for PBL, besides the

PBL formalized process does not conform to the

classical references of the methodology: the 7 steps

(Deelman and Hoeberigs, 2009) and the PBL cycle

proposed in Hmelo-Silver (2004); and (4) these

previous ontologies have not been evaluated.

Table 1: Comparison between PBLOntology and the

ontologies that formalize the PBL process.

Ontology

Jacinto e

Oliveira

(2008)

Fontes et

al. (2011)

PBL

Ontology

Consider the

PBL Cycle

Consider

Reuse

Evaluation

Integrated

within an

Application

4 THE PBLOntology

PBLOntology is available for download in Ontohub

(http://ontohub.org/repositories/pblontology), a web-

based repository for ontologies based on open source

software. The Protégé was chosen to develop the

PBLOntology because it is an open source code tool

and it provides a powerful editor of ontologies

including semantic web standard languages. We use

the language OWL (Web Ontology Language) due to

the fact that it is a robust language, recommended by

the W3C (World Wide Web Consortium) as a

standard for representing ontologies. The rule

language defined for the axioms creation is the

SWRL, it allows the combination of the developed

axioms with OWL. The query language is SPARQL,

because it is also supported by Protégé and

recommended by the W3C. The chosen inference

engine is the Pellet for supports SWRL rules and it

has a consistency check mechanism of ontology and

good performance. The 101 Method (Noy and

MCguiness, 2001) was adopted because it explicitly

describes the steps comprising the development of

an ontology.

To support the development of the PBLontology,

it was performed a field research in the Computing

Engineering course of the State University of Feira

de Santana. The field research consisted of

observations, questionnaires and interviews, during

the tutorial sections and it has been performed in a

period of six months.

4.1 The PBLOntology Development

Steps

A systematic mapping conducted to verify if there

was some ontology that could be reused. It has

shown a lack of formal representation of the PBL

concepts based on ontology language (Souza et. al,

2014).

The development of the PBLOntology

comprises of two phases: first we formalized the

knowledge of the essential elements that should be

considered in PBL. The second phase focused on the

formalization of contextual elements that emerged

on the collaborative discussions of tutorial sessions.

The PBLOntology is structured as follows: (i) a

classes and subclasses hierarchy representing the

PBL taxonomy; (ii) Object properties that qualify or

relate classes/individuals; (iii) data type properties,

representing the attributes of the classes; (iv)

instances, representing individuals of the classes; (v)

SWRL axioms, which are rules to represent the

knowledge domain; and; (vi) SPARQL queries.

During the PBLOntology development, 28

competency questions (CQ) were created. These

questions indicate what our ontology must be able to

answer and they are important to help testing the

ontology, evaluating the constraints, semantic rules,

and checking its consistency and competence. The

following are some of our competency questions:

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CQ1: Which students of a group have not been

coordinators?

CQ2: What are the learning questions of a

session?

CQ3: What is the problem solving ability of a

student?

CQ4: What were the strategies created by the

tutor in a tutorial session?

The above competency questions can be useful

in many scenarios: the CQ1, for instance, can help

the coordinator indicating which student would be

the next coordinator. In a distance learning course

that uses PBL, the system itself can suggest a

coordinator. The CQ4 can help beginner tutors in the

creation of strategies according situations other

tutors had experienced.

4.2 Classes

To represent the PBL process twelve main classes

were defined (ActionPlan, Evaluation, Fact, Idea,

LearningIssue, Person, Problem, Process, SelfStudy,

TutorialGroup, TutorialSession and WhiteBoard)

and one main class (Context) to represent context of

the collaborative discussions during sessions. Figure

2 shows the main classes of the PBLOntology.

Figure 2. Main classes of the PBLOntology.

The Process class consists of the following

stages: presentation of the problem; discussion of the

problem by the group in the tutorial session;

individual study phase that occurs after the tutorial

sessions; and the evaluation phase. According to the

PBL phases, the Process class was defined as a

disjoint union of Evaluation, Problem, SelfStudy,

TutorialGroup and TutorialSession classes.

The Problem class represents the problem

addressed within the PBL process. This problem

must be a real or potentially real situation. It is

intended to cover a particular content, aiming at the

construction of knowledge and the development of

skills and competencies.

The Evaluation class represents the assessment

of both the student and the methodology. It

considers the following aspects: compliance with the

targets; attendance; collaboration and behavior.

These represent the properties of the class. It also

includes assessing the assignments of the

coordinator, whiteboard secretary, meeting

secretary, and the evaluation concerning the delivery

of the final product as well as the final report of the

problem resolution.

The TutorialSession class represents the meeting

with the group of students mediated by the tutor. It is

intended to discuss the proposed problem, record the

discussion progress on the whiteboard while the

problem is being approached.

The WhiteBoard class represents the whiteboard

where students record discussions about the problem

during tutorial session. A whiteboard is, therefore,

an aggregation of concepts ideas, facts, goals and

learning issues. This class is a disjoint union of the

following classes: Idea, Fact, LearningIssue and

ActionPlan.

The SelfStudy class represents the individual

study phase on the PBL process. Here students

research the contents to respond to the learning

issues and the achievement of the established

objectives.

The TutorialGroup class represents the PBL

tutorial group, which consists of a tutor and students.

The Tutor class and the Student class are disjoint.

The Context class comprehends two main

subclasses: GroupContext and SessionContext. The

GroupContext class represents the group level and

the people who form the group. To define the group's

context we have considered the group structure

representing the maximum and minimum number of

students, and if the group had to be split into other

groups or if it had to join another group. The context

of people who are part of the tutorial group was also

considered: i. e., skills of students in the group, areas

of computing interest, previous experience in PBL,

and reprobation or desertion of the student. The

SessionContext class captures the context of tutorial

sessions. This class considers the temporal context

of the tutorial sessions, such as start time, end time,

days of the week, the order of the session, the

strategies to enable a productive tutorial session, and

the interaction context yielded by the group of the

tutorial session.

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379

We consider as interaction context the student

actions during a tutorial sessions, such as: the

collaboration with the discussion, the achievement

of the goals, the sharing of new knowledge, the

questions formulated during the tutorial session, and

the clarification of doubts raised by other students.

The tutor interaction was also considered: the

assistance in defining the whiteboard questions, the

questions raised by the tutor, the clarification of

pertinent questions, the assistance in defining the

whiteboard functions, and the encouragement of

student participation.

4.3 Properties

Aiming to represent relationships between

individuals of classes, 37 Object Properties were

defined in the first phase, whereas 23 Object

Properties were established in the second phase.

Table 2 shows two Object Properties defined in the

PBLOntology.

Table 2: Object Properties.

Properties

Domain

Range

Inverse

hasPerson

TutorialGroup

Person

hasFact

WhiteBoard

Fact

isFactPartOf

The hasPerson property represents the

relationship between the individuals of the

TutorialGroup and the Person classes that are part

of a tutorial group. The TutorialGroup class was,

therefore, established as the domain of this property,

and as the range the Person class. The hasFact

property is the inverse of isFactPartOf property and

represents the relationship between individuals of

the class WhiteBoard and Fact defined in a tutorial

session. The domain of this property is the

WhiteBoard class and the range is the Fact class.

To the representation of DataType Properties, 26

properties were established in the first stage of the

PBLOntology development, and 29 properties in the

second. As an example, Table 3 shows two Datatype

Properties defined in the PBLOntology.

Table 3: Datatype Properties.

Properties

Domain

Range

learningQuestion

LearningIssue

string

actionStrategy

Strategy

string

The DataType Properties learningQuestion

represents a learning question defined on the

whiteboard during a tutorial session. The domain of

this property is the LearningIssue class and the

range is string. The DataType Properties

actionStrategy property represents actions related to

the strategies, in other words, what the tutor needs to

do during the tutorial session for its proper

functioning. The domain of this property is the class

Strategy and the range is the string type.

4.4 Restrictors and Axioms

The semantics of the terms belonging to the

ontology proposed in the first phase was defined

with twelve restrictions. Those restrictions involve

existential, universal,quantifiers and cardinality.

The restriction defined in the Process class,

shown in Figure 3, establishes that the individuals of

the Process class are formed by the union of the

classes Evaluation, Problem, SelfStudy,

TutorialGroup and TutorialSession. Besides, it states

that this union is a sufficient and necessary condition

to establish the Process class as an aggregation.

Figure 3: Restriction that determines the formation of the

Process class.

We have specified five axioms in the language

SWRL (Semantic Web Rule Language). The axiom

shown in Figure 4 is designed to make inferences

about the PBL experience of a student. The rule

states that if there is a person within a tutorial group,

within a PBL process, then this person has a context

The context holds the PBL experience of a person.

This axiom can be useful to recommend students as

a tutor based on their PBL experience.

Figure 4: SWRL axiom that infers PBL experience of a

student.

4.5 Instances

We have created a consistent database populated

with actual instances suitable to support the

development of future research. These instances

Were collected during the field research. In the first

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stage, 266 individuals were instantiated and among

the classes defined in ontologies. In the second

stage, over 97 individuals were instantiated.

Figure 5 presents one instances of the Fact class

where we can observe some data type properties

(PrirKnowledge) instantiated in that class and an

inferred object property (isFactPartOf).

Figure 5: Instance defined in PBLOntology.

5 ONTOLOGY EVALUATION

In the literature, there are two evaluation methods

for ontologies: test activities and evaluation with

specialists (Santos, 2013; Silva, 2013). According to

Vrandecic (2009) it is important to define some

criteria to evaluate ontologies. Based on Vrandecic

(2009), we defined the following criteria for

evaluation of the PBLOntology: accuracy,

adaptability, clarity, completeness and competence,

consistency and coherence, and conciseness.

To evaluate the consistency, coherence and

competence criteria, we carried out testing activities

in both ontology development stages. These tests

consisted of running the reasoner Pellet of protégé

and observing the inferences made in the ontology,

checking its behavior, consistency and formalization

coherence.

The competency assessment was performed by

the SPARQL queries that were created to answer

competence questions.

For CQ1: Which students of a group have not

been coordinators? The SPARQL query is presented

below.

SELECT ?Group ?Student WHERE{

?Grouppbl:hasPerson ?Student.

MINUS{?Sessionpbl:hasCoordinatorSess

ion

?Student}} ORDER BY (?Group)

(?Student)

For CQ4: What were the strategies created by the

tutor in a tutorial session? The SPARQL query is

presented below.

SELECT ?TutorialSession ?Event ?Action

WHERE{?SessionContextpbl:isSessionConte

xt ?TutorialSession.

?SessionContextpbl:hasStrategyContext

?Strategy.

?Strategypbl:eventStrategy

?Event.?Strategypbl:actionStrategy

?Action } ORDER BY (?TutorialSession)

SPARQL queries were designed to verify if the

ontology was able to respond each of the defined

competence questions.. The competence questions

can support the systematization of the methodology

and help in decision-making. The PBLOntology

answered satisfactorily all defined competence

questions, hence, it meets the competence criteria

within the defined scope.

To verify if the ontology correctly captures and

represents aspects of the real world, a questionnaire

with 24 questions was developed. It was answered

by 4 experts, who are lecturers with PBL experience

in the course of Computer Engineering at the State

University of Feira de Santana. The questions aimed

to evaluate concepts and class names (conciseness

and clarity), relationships and constraints defined in

the ontology (accuracy), coverage and completeness.

Figure 6 presents the evaluation of the concepts and

class names.

Figure 6: Evaluation of the concepts and class names.

Analyzing the experts’ opinions, 59% of the

answers stated that the concepts and names of the

classes defined in the ontology are satisfactory, 30%

partially satisfy and 11% do not satisfy. We also

asked the experts to inform the most appropriate

concept and name, when the answers were not

totally satisfactory and this feedback was used to

improve the ontology.

Regarding the evaluation of accuracy, in two

questions the experts suggested changes in the

ontology relationships and constraints, these changes

were implemented. When assessing the coverage

and completeness, it was not possible to draw any

PBLOntology: A Domain Ontology with Context Elements for Problem-based Learning

381

conclusions, since 50% evaluated the ontology as

complete and 50% reported a lack of concepts.

The evaluation of the adaptability criterion was

subjective, accomplished through the extension of

the domain ontology incorporating context elements

that had emerged during the tutorial sessions.

Table 4 presents a general overview of the

questions and the evaluated criteria.

Table 4: Analysis and assessment of result.

Evaluation

Approach

Results

Conclusion

Testing

activities

Correction of

inference errors and

inconsistencies.

It complies with

the coherence

and consistency

criteria.

The executed

queries brought the

expected replies.

It satisfies the

competence

criteria.

Evaluation

with

experts

Concepts and names

of classes: most

questions satisfied

or partially satisfied,

and suggestions

were accepted.

It meets the

clarity criteria.

Coverage: 50% said

yes and 50% said

no.

It is not possible

to ensure that

the

completeness

criteria is

satisfied.

Relationship and

restrictions: the

majority is correct.

It complies with

the accuracy

criteria.

Ontology

expansion

It was possible to

expand the domain

ontology including

contextual elements

observed during

tutorial sessions

It satisfies the

adaptability

criteria.

The assessment allowed us to make

improvements to the ontology according to the

defined evaluation criteria. A small number of

inconclusive issues would have been further

clarified had more experts participated in the

evaluation.

6 CONCLUSION AND FUTURE

WORS

This paper presented an ontology for Problem-Based

Learning that provides a semantic formalization of

the PBL process, as well as the contextual elements

of collaborative discussions that appeared on tutorial

sessions.

To mitigate potential problems, two approaches

were defined for the evaluation: testing activities and

expert evaluation. That approach towards the

assessment of the results allowed us to improve the

ontology. Thus, we provide strong evidence to

conclude that PBLOntology meets the defined

evaluation criteria satisfactorily, and displays

pertinent applicability to the field of Computer

Science.

The proposed ontology advances on current work

by providing a formalization of the PBL domain

based on ontology. It also establishes an innovative

contribution by identifying contextual elements for

the collaborative tutorial sessions.

Researchers and those who work with ontologies

and development of semantic applications for the

PBL domain can benefit from PBLOntology. This

ontology can serve as a basis for the knowledge of

the domain; It can also graphically illustrate the

concepts and relationships of the PBL and therefore

enable the understanding of the methodology for

beginners in the subject. Besides, it can be reused for

the creation of other ontologies or applications.

Another advantage of PBLOntology is that it has a

database with more than 300 instantiated

individuals, which can facilitate the testing of new

applications that use the ontology.

Although the ontology can be reused, shared and

expanded, contributing to research and studies in the

area, PBLOntology has some limitations: it was

evaluated only in a computation course, the scope of

contextual elements was very reduced and the

amount of specialists was not enough to evaluate

coverage and completeness of the ontology. Future

works should address these limitations.

ACKNOWLEDGEMENTS

Authors thank the expert professors and

undergraduate students of Computer Engineering at

The State University of Feira de Santana (UEFS) for

their collaboration in the experiments of this

research and Bahia Federal Institute of Education,

Science and Technology (IFBA) for granting a

scholarship to exclusive dedication to this research.

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