An Application of a Gamification to Knowledge Management

Teaching: A Qualitative Evaluation

Antonilson da Silva Alcantara

and Sandro Ronaldo Bezerra Oliveira

Graduate Program in Computer Science, Institute of Exact and Natural Sciences,

Federal University of Pará, Belém, Pará, Brazil

Keywords: Gamification, Qualitative Analysis, Affective Computing, Information Technology.

Abstract: The education area has been encouraging the adoption of innovative practices and methodologies for the

teaching and learning process. Teaching in Information Technology (IT) courses brings several challenges.

Thus, the objective of this work is to present a qualitative analysis of the application of a gamification,

adapted for the remote modality, applied in the context of a software quality laboratory about knowledge

management. A brief description of the gamified approach is made, followed by the application plan of this

proposal. Then, a brief report about the analyzed case study is presented. Soon after, the qualitative evalua-

tion is detailed as well as its results. Finally, conclusions and future work are presented.

https://orcid.org/0000-0001-8024-0220

https://orcid.org/0000-0002-8929-5145

1 INTRODUCTION

The education area has been encouraging the use of

new practices and methods that contribute to the

teaching-learning process. There is a need to innovate

teaching processes, aiming to encourage students to

participate more actively (Cardoso et al., 2018).

In this way, it is necessary to identify strategies

and methodologies to support the student motivation

process in a simple and effective way (Lopes et al.,

2021). The use of gamification technique

demonstrates a potential to stimulate people's

commitment and motivation (Lopes et al., 2021).

Gonçalves et al. (2015) state that it is extremely

important to plan the gamification process, in the

educational context, that considers the objectives to

be achieved, the contents that will be taught and the

evaluation strategies with the expected results.

Thus, the need to innovate teaching processes is

evident, with the use of new practices and methods,

in order to encourage the student to participate more

directly (Goulart, 2019).

Recent studies reveal the need for research on

collaborative learning involving affective computing

(Reis et al., 2018).

According to Oliveira et al. (2019),

understanding affective computing and its

application in academic contexts is a challenge.

There are several ways to extract affective

information from: vision-based information, brain

signals, physiological measurements, and others

(Batista, 2019). Another way of capturing is the

collection of affective information based on

discourse analysis, enabling analysis through both

speech and writing (Batista, 2019).

Based on this, this work aims to present a

qualitative analysis of the application of a

gamification, adapted to the remote modality,

applied in the context of a software quality

laboratory about knowledge management.

In addition to this introductory section, this paper

is structured as follows: Section 2 presents the

research methodology, Section 3 presents the

gamification for knowledge management teaching,

Section 4 presents the application plan of this

gamification, Section 5 presents the case study report,

Section 6 presents the qualitative evaluation, and

Section 7 presents the conclusions and future work.

2 RESEARCH METHODOLOGY

This work was developed from the following steps:

(i) definition of research objectives and their

Alcantara, A. and Oliveira, S.

An Application of a Gamiﬁcation to Knowledge Management Teaching: A Qualitative Evaluation.

DOI: 10.5220/0011058000003182

In Proceedings of the 14th International Conference on Computer Supported Education (CSEDU 2022) - Volume 2, pages 489-497

ISBN: 978-989-758-562-3; ISSN: 2184-5026

489

respective indicators, (ii) definition of the target

audience, where the context of application of this

proposal was selected, (iii) definition of the

application model, where the periodicity and

meeting models were defined, (iv) adequacy of the

environment and instruments used for the virtual

model and (v) analysis of the profile of the

participants of the dynamics. These steps are

detailed in Section 5.

According to the Silva and Menezes (2001), there

are different ways of classifying a research. Thus, the

scientific method applied is the inductive method, as

it is characterized as a particular case study with the

objective of elaborating a generalization.

From the Point of View of Nature it is classified

as a Applied research, involving concepts and facts

already explored, in addition to having as objective

the advancement of science in the knowledge

management of the Information Technology area.

From the Point of View of the Problem

Approach, the research is classified as Qualitative,

as it deals with data that change according to the

context and, thus, creates a dynamism, requiring an

inductive analysis to better understand its meanings.

The research is also classified as Exploratory,

since it is intended to understand its origins and

characteristics, generating mastery over the problem,

making it possible to elaborate a possible solution.

Finally, from the point of view of Technical

Procedures, this research is classified as

Bibliographic, as it is based on articles published in

conferences and journals, as well as books by

reference authors in the researched area, and Case

Study, because it performs the application of a

gamification in a context to evaluate its results

3 GAMIFICATION FOR

KNOWLEDGE MANAGEMENT

TEACHING

The gamification to support the teaching and

learning of Knowledge Management assets and

process, described by Alcantara and Oliveira (2021),

is composed of a workflow, consisting of seven

steps. Figure 1 presents the flow of gamification.

The dynamic starts with the Beginning step,

which is the initial phase of the game. Here the

objective is to make the participants have an

overview of the dynamics. Thus, a simulated round

is carried out at this step, through the presentation of

activities, work products, scores, and rules for

participants to get used to the gamification.

The next step is called Knowledge Factory (KF),

which is composed of the sub-steps: (i) Generate

Knowledge and / or Comment Cards (GC), (ii)

Evaluate Cards (EC) and (iii) Identify the Target

Audience (IT). In this step, the objective is to lead

participants to have their own experiences in relation

to the process of creating knowledge items. Thus,

participants are encouraged to participate in the

process of creating knowledge, evaluating

knowledge and identifying the target audience.

Figure 1: Knowledge Management Gamification Flow.

The next step is called Duel and aims to

stimulate the student through competition so that he

dedicates himself and develops in the knowledge

creation steps. To this end, a comparison is made of

the scores given by the participants and the expert

for the same knowledge item, with the participant

who replicated the score given by the expert being

considered the winner.

The expert is one of the existing profiles in the

dynamics, being responsible for evaluating all the

knowledge generated. To act in this profile it is

necessary that the participant has a strong

knowledge of the subject adopted to generate

knowledge during the dynamics.

The next step is called Pack Card and

Communicate Target Audience, and aims to select the

knowledge items approved in the expert's evaluation.

Thus, in addition to rewarding the respective authors,

this approved knowledge is organized so that it is

accessible to the public of interest.

The Knowledge Repository step aims to provide

participants with conditions for socialization, as a

way of disseminating knowledge. Participants have

the opportunity to consult the approved knowledge

and request information from their respective

authors about the knowledge items.

CSEDU 2022 - 14th International Conference on Computer Supported Education

490

The next step is called Ranking, whose objective

is to present the performance of the participants,

being, therefore, considered a feedback step.

Finally, the last step is called Self-Evaluation.

The objective is to direct the participant to carry out

an evaluation of their performance at the end of each

round and, based on that, set personal goals for the

next round.

4 THE APPLICATION PLAN

The application of this gamified proposal was

planned with the objective of supporting a dynamic

whose objective was to implement the Customer and

Market (CM) dimension of the MOSE (Guiding

Model for Business Success) model, in the context

of a software quality laboratory. The planning of this

gamification is presented in the next subsections.

4.1 The Participants

The participants in the knowledge management

gamification were the students/researchers of the

software quality laboratory, who also participated in

the dynamics that aimed to implement the Customer

and Market (CM) dimension of the MOSE model, in

the context of that laboratory.

The objective of applying knowledge

management gamification with this target audience

was to stimulate socialization and knowledge

management at the end of the implementation of the

CM dimension of the MOSE model.

The participants were master's and doctoral

students, whose research lines were in the Software

Engineering (SE), with professional experience in

the Information Technology. In total there were nine

(9) participants, being: one female and eight males.

Table 1 presents the profile of each participant.

Table 1: Participants Profile.

Student

Degree

Research

Line

Professional

Activity

Time

(years)

P1 Doctorate SE Researche

P2 Doctorate Education

in SE

Researcher 6

P3 Doctorate SE Researche

P4 Doctorate SE Analist of

systems

P5 Maste

SE Researche

1,5

P6 Maste

SE Researche

P7 Doctorate SE Professor 10

P8 Maste

SE Technician 2

P9 Maste

SE Researche

There are four profiles in the dynamics: (i)

Master, responsible for timing each activity and

signaling when to proceed to the next step in the

flow, where one (1) participant acted in this profile,

(ii) Judge, responsible for the Gamification

Worksheet, recording the scores obtained by each

Player throughout the steps and, at the end,

presenting the Ranking of the participants, where

one (1) participant acted in this profile, (iii)

Specialist, expert in the knowledge area being

studied, its function is to help solve doubts, evaluate

and score Cards created by Players, suggest

challenges, and indicate Cards that will be stored in

the knowledge bank and disseminated in the group,

where one (1) participant acted in this profile, and

(iv) Player, participant in gamification and main

actors in the knowledge creation process, where six

(6) participants acted in this profile.

4.2 Application Period

The period of application of the dynamics occurred

in the interval between 09/09/2021 to 10/07/2021,

on Thursdays, from 16:00h to 18:00h. Table 2

presents the schedule with dates and iterations that

took place for the conclusion of the Journey.

Table 2: Application Schedule.

Date Activities Duration

09/09/21

Dynamics

resentation

4:00 pm to 5:20 pm

Simulated Roun

5:20

m to 6:00

09/16/21 Iteration 1 4:00

m to 6:00

09/23/21 Iteration 2 4:00 pm to 6:00 pm

09/30/21 Iteration 3 4:00 pm to 6:00 pm

10/07/21

Rating and

Feedbac

4:00 pm to 6:00 pm

4.3 Gamification Instruments and

Support Tools

The case study took place remotely in line with the

health restrictions imposed due to the covid-19

pandemic. Thus, all the instruments of this gamified

proposal, originally planned for physical use, were

adapted for use in the virtual modality.

Different tools were used to apply this case study

remotely, they were: Google Meet to hold the

necessary meetings to carry out the activities

proposed in the gamification scenario, Google

Calendar to manage the dates and times of meetings

necessary to carry out activities during the

Gamification journey, Google Drive to make work

products available collaboratively, Google

An Application of a Gamiﬁcation to Knowledge Management Teaching: A Qualitative Evaluation

491

Documents used in the adaptation of the individual

monitoring form and the self-evaluation form, both

for remote use, Google Sheets used in adapting the

gamification spreadsheet for remote use, Google

Drawings used in adapting Knowledge Cards for

remote use, Google Jamboard used in adapting the

Knowledge Framework for remote use and E-mail to

send information to those involved.

These tools were chosen because they are: free,

generating no burden for participants, for being

known by the participants and, as most of them are

available in the Google Drive environment, facili-

tating navigation between the different instruments.

4.4 Adopted Evaluation Criteria

The purpose of applying this case study is to

evaluate how the methodology adapted by Alcantara

and Oliveira (2021) is aligned with training in the

Information Technology, in the remote modality.

To this end, some Research Questions (RQ) were

defined, with their respective indicators that serve as

a guide in the process of evaluating the results, as

shown below.

RQ1 says Do the instruments and activities

developed fulfill the purpose of stimulating the

knowledge management process? The objective of

this question is to evaluate the suitability of

gamification as a tool to support the teaching and

learning process of knowledge management.

QP2 says about Did the participants show

satisfaction during the application of gamified

dynamics? With this question, the objective is to

evaluate the satisfaction of the participants at the end

of the application of gamification.

The collection of qualitative data to evaluate the

dynamics occurred: during the application of the

case study, through the field Iteration Evaluative

Report. These data will be evaluated through

Affective Analysis through the text, with the

objective of identifying the emotions aroused in the

Players during the experience of the application of

gamification; and, through a SWOT (strenghts,

weaknesses, opportunities and threats) analysis

performed during the final iteration of Evaluation

and Feedback.

5 THE CASE STUDY REPORT

This work aimed to support a dynamic, which took

place remotely, which aimed to implement the

Customer and Market (CM) dimension of the MOSE

model in the context of a Software Quality

Laboratory at a Brazilian federal public University.

As it is a laboratory with a diversity of

researchers in different areas of Software

Engineering, it was identified the need to apply

knowledge management at the end of the case study,

so that all cataloged and learned information was

directed and made available to its referred target

audience.

The labor market has undergone major

transformations that drive companies to adapt their

organizational structures and production processes

(SOFTEX, 2016). Thus, it is necessary to evaluate,

over time, the knowledge items in order to evaluate

their application, usefulness and compliance with

what was initially proposed.

Based on this, it was necessary to apply

knowledge management (through this gamified

proposal), in order to catalog, identify, reevaluate

and make the knowledge items available to their

respective target audiences and, later, enable their

management in terms of application, validity and

meeting the objectives in the context of the software

quality laboratory.

In addition, another characteristic that

corroborated the application of this case study was

the fact that in the research group there was a

rotation of members, at different levels of research

(undergraduate, master's, doctoral students, and

professors), being, therefore, it is necessary to

maintain a repository of knowledge with the

solutions developed and the lessons learned by the

group.

Another factor that corroborated the need to use

knowledge management gamification was the need

to classify the solutions and knowledge produced, in

order to maintain a database, sorted by type of

knowledge and classified by target audience. This

facilitates both consultation and assignment of tasks

and responsibilities.

Finally, the Software Quality Laboratory is made

up of participants with different profiles and levels

of responsibilities, thus making it necessary to

identify knowledge based on the responsibilities and

attributions of each member.

Based on the above, and knowing the

effectiveness of this proposal in similar contexts (as

presented in (Alcantara et al., 2019; Alcantara and

Oliveira, 2019), we identified the opportunity to

evaluate how the methodology adapted by Alcantara

and Oliveira (2021) is aligned with training in the

Information Technology area, in the remote

modality.

CSEDU 2022 - 14th International Conference on Computer Supported Education

492

6 QUALITATIVE EVALUATION

Qualitative data were collected in two ways: during

the application of the knowledge management

gamification dynamics, through the participants'

evaluative reports, in the self-evaluation step, where

these data were analyzed through the application of

Affective Text Analysis, and, at the end of the

dynamic, in a participatory evaluation and feedback

meeting, focus group, where the SWOT matrix was

used.

6.1 SWOT Analysis

Qualitative results were collected from interviews in

the Feedback meeting with all Gamification

participants. We analyzed, through the SWOT

matrix, the proposal of Gamification to support the

teaching and learning process of knowledge

management, the instruments adopted, the self-

evaluation process, and the adequacy of this

gamified proposal for the remote modality.

According to Santos et al. (2010), the SWOT

tool is used in the analysis of scenario or

environment to define the strategic positioning of an

organization.

Regarding the Gamification proposal, the

following were presented as Strengths: (i)

competitiveness in the dynamics, generating a

healthy dispute between the participants, (ii)

possibility of self-analysis, where the participant

can perceive their performance and evolution within

the dynamics, (iii) definition of times to manage

activities, which helps members to participate in all

activities in an orderly manner, (iv) possibility of

debates, which is perceived in the knowledge

repository step, where participants can present their

produced knowledge and interact with other

participants about the knowledge item, and (v)

participation of a specialist in the evaluation

process, which allows a more reliable evaluative

parameter.

As Opportunities, the possibility of developing a

system to automate several tasks present in the

gamification proposal was highlighted.

Then, in the Instruments adopted criterion, the

following were highlighted as Strengths: (i) the fact

that the gamification worksheet encourages the

student to develop, since it makes it possible to

follow the scores as the worksheet is filled and (ii)

use of the ranking, for monitoring by the student.

Still in this criterion, Weaknesses were

highlighted: (i) the gamification worksheet needs

to be better organized, so that the fields are easier

to read, (ii) many instruments, which end up

hampering the participant's performance, and (iii)

detailed description of the gamification

worksheet, since current descriptions are confusing.

As opportunities, still in this criterion, it was

highlighted: developing a system to handle the

different instruments and centralize the many work

products in a single file.

As for the criterion of the Self-Evaluation

process, the following were highlighted as Strenghts:

(i) it contributes positively to the objective of the

dynamics, generating a perception of the importance

of the evaluation, (ii) it enables the collection of

important performance data, which can be

measured throughout the steps, and (iii) it is

important for all participants, as they directly

impact the participants' performance.

As Weaknesses, even in this criterion, were

highlighted: (i) the self-evaluation task is

confusing, generating many doubts during its

execution, (ii) need for detailing the scores, to

guide the mapping in the self-evaluation form, (iii) it

needs traceability and automation, to fill in the

points in the respective fields automatically at each

step, impacting the evaluation process, and (iv) the

adoption of scores in a cumulative way, causes

difficulty in filling in scores in each iteration.

As an Opportunity, it was suggested to automate

the recording of scores, speeding up the completion

of the worksheet, leaving the participant only

designated to develop their opinions and goals in the

self-evaluation worksheet.

Finally, in the Adequacy criterion for the remote

modality, the adaptation of the gamification

worksheet for remote use was highlighted as a

strength, helping participants to monitor the

evolution of performance.

As for Weaknesses in this criterion, the

following were highlighted: (i) the alternation

between several files and spreadsheets, since the

instruments were adapted for use in different tools,

(ii) absence of a single document, which

encompassed all instruments in the same tool, and

(iii) late feedback, caused by the need to enter

scores manually.

As an Opportunity, the need to create a system

for automating activities and controlling dynamics

was identified.

6.2 Affective Computing

Affective computing is defined as computing that

relates to, arises from or is influenced by emotions

and other affective phenomena (Pudane et al. 2018).

An Application of a Gamiﬁcation to Knowledge Management Teaching: A Qualitative Evaluation

493

Emotions, according to Damásio (2006), are a set of

bodily manifestations aroused after receiving a

certain stimulus.

Thus, emotions are perceived by the words used

in a given context, or even through the variations of

the frequencies felt in certain parts of the speech

(Batista, 2019).

In order to carry out the affective analysis

through text, the text pre-processing steps were

followed, an after that by a summary of the results.

In the text pre-processing step, the following

activities were carried out: reading and text

processing, class assignment, pre-processing and

transformation;

Thus, in the reading and text processing activity,

the reading and analysis of the texts informed by the

participants in the self-evaluation steps was carried

out. A pre-formatting was carried out to organize the

texts and classify the answers, removing non-

essential characters or words, valuing the content

informed by them.

Then, the weights corresponding to each emotion

were defined. This definition is necessary so that the

different feelings can be cataloged and logically

organized so that a general report of the predominant

feelings aroused in the dynamics can be generated.

Thus, the weights defined were: 3 for positive

feelings, 2 for neutral feelings and 1 for negative

feelings.

In the pre-processing step, answers were

analyzed and feelings were identified, where the

respective weights were assigned.

Then, in the transformation step the data were

organized by weights in a spreadsheet to be worked

on in the analysis process. Table 3 presents a sample

of these data.

Table 3: Sample of feelings identified in the text with their

respective weights.

Feelings Weights

Goals were not achieved 1

My performance was reasonable 2

My performance was a little slow 2

I see it was quite beneficial 3

I managed to assimilate some knowledge 3

It made possible to achieve the defined goals 3

The dynamics became more intuitive 3

I didn't reach any of my goals 1

I only produced two cards 1

Finally, the results were summarized through the

described analyses. Thus, in total, 50 feelings were

identified, which correspond to the three iterations

where the self-evaluation step took place, to which

they received their respective weights.

The data collected in the first iteration resulted in

17 feelings which were categorized according to

their respective weights. Figure 2 presents the result

of this summary.

Figure 2: Summarization of feelings from the first itera-

tion.

The first iteration took place at the meeting

following the presentation of the dynamics and the

simulated round. It is worth noting that in the self-

evaluation step of this iteration, there was still no

stipulated target. The evaluation was conditioned to

the participant's own perception of their performance

and, based on this, they could set a personal goal for

the next iteration.

Thus, 47% of the feelings identified fit into the

positive emotion, demonstrating user satisfaction,

both in terms of dynamics and their performance.

The neutral emotion represented, in this iteration,

41% of the identified feelings. In this first iteration,

doubts were still frequent, which showed a little

insecurity on the part of those involved regarding

their performance in the dynamics.

Finally, 12% of the feelings identified fell within

the negative emotion. Here participants mainly

reported cognitive difficulties (difficulties

concentrating, slow thinking, and lack of creativity).

Figure 3: Summarization of feelings from the second

iteration.

CSEDU 2022 - 14th International Conference on Computer Supported Education

494

The goals defined by the participants in this

iteration served as indicators in the self-evaluation

step in the second iteration. Figure 3 presents a

summary of this evaluation.

In the second iteration, 18 feelings were

identified in the participants' evaluative reports.

Unlike the previous evaluation, this time it was

possible to evaluate the achievement of the

previously stipulated personal goals.

Thus, in this iteration, 6% of the identified

feelings fit the positive emotion and were related to

satisfaction with the fluidity of the dynamics.

In the neutral emotion, 5% of the feelings

identified in the participants' evaluative texts were

framed. These reports of feelings alluded to the

awareness that the stipulated goals were tangible.

Finally, 89% of the feelings identified in the

participants' evaluative texts fit into the negative

emotion. Mainly, difficulties in achieving the

stipulated goals were reported. Dissatisfaction was

also mentioned with the times of the dynamics, both

the feedback and the ones destined to carry out the

steps.

At the end of the Self-Evaluation step, in this

second iteration, the participants defined personal

goals for the next iteration. Figure 4 presents the

result of this summary.

Figure 4: Summarization of feelings from the third itera-

tion.

In the third iteration, 15 reports of feelings were

identified in the evaluative texts informed by the

participants. For this iteration, participants had the

opportunity to define personal goals using the results

of the second iteration as a parameter.

In this way, 73% of the feelings identified in the

participants' evaluative reports fit into the positive

emotion. The main reports of feelings alluded to the

achievement of the stipulated goals. The perception

of gamified dynamics as intuitive, easy and simple

to understand was also mentioned in the reports.

The feelings identified in the evaluative texts of

the participants who fit the neutral emotion

correspond to 7%. Mainly, the proximity of reaching

the stipulated goals were reported.

Finally, 20% of the feelings identified in the

evaluative reports fell within the negative emotion.

The reports of feelings classified in this emotion

alluded to the failure to reach some of the defined

goals. Cognitive difficulties (lack of creativity) were

also reported.

Overall, the sentiments identified were

homogeneous over the iterations. Figure 5 presents a

summary of feelings throughout the application of

gamification.

Figure 5: Summarizing feelings in gamification.

Thus, 40% of the feelings identified throughout

the evaluative reports fit into the positive emotion,

peaking in the third iteration with the achievement

of goals, which were readjusted by the participants

in the previous iteration.

The feelings that fit the neutral emotion

correspond to 18% throughout the application of

gamification, having its apex in the first iteration

where, in the evaluation of the evaluative reports, a

small insecurity in the participants was perceived.

Finally, the feelings that fall under the negative

emotion, throughout the application of the case

study, correspond to 42%, having their apex in the

second iteration with the non-achievement of the

goals, given that they were initially defined without

the existence of a previous parameter.

Figure 6: Word cloud chart.

An Application of a Gamiﬁcation to Knowledge Management Teaching: A Qualitative Evaluation

495

Thus, Figure 6 presents the word cloud chart that

aims to present the terms according to their degree

of occurrence in the participants' evaluative reports,

evidencing the feelings most cited by the

participants.

7 CONCLUSION

This paper presented the results of a qualitative

analysis of a case study that aimed to analyze the

suitability of a gamification to support the teaching

and learning of the knowledge management assets

and process, aligned with training in the Information

Technology area, in remote mode.

The results obtained from the SWOT analysis

with the participants make it possible to answer the

RQ1: Do the instruments and activities developed

fulfill the purpose of stimulating the knowledge

management process? We conclude that yes, since

the use of this gamification proposal allowed

participants to produce and socialize different

knowledge, positively impacting this process, as

could be seen by the SWOT analysis. However, it is

necessary to readjust several points regarding the

adaptation of the instruments to the remote modality.

In addition, for greater efficiency, it is necessary to

implement a collaborative tool to automate the

administrative routines of the dynamics.

In the same way, the results obtained with the

affective analysis made possible the answer of RQ2:

Did the participants show satisfaction during the

application of the gamified dynamics? We conclude

that yes, since the analysis pointed to an evolution of

the feelings reported during the gamification

iterations, corroborating the achievement of a better

performance in the dynamics. In addition,

participants could perceive the need to readjust

personal goals so that they become tangible and

satisfying.

As future works, the authors suggest: the

implementation of a serious game based on this

gamified proposal and the application in a group of

the Information Technology course, in the remote

modality, to verify its adequacy and efficiency in the

knowledge management process.

REFERENCES

Alcantara, A. S., Oliveira, S. R. B., Rodrigues, E. A.,

Junior, R. V., Silva, J. C., Cardoso, W. R. (2019).

Gamification and Evaluation of the Application of

Knowledge Management in a Computer Science

Class: An Experimental Study. In: XVIII Simpósio

Brasileiro de Jogos e Entretenimento Digital -

SBGAMES. Brazil.

Alcantara, A. S., Oliveira, S. R. B. (2019). Gamification

and Evaluation of the Knowledge Management Appli-

cation in a Software Quality Lab: An Experimental

Study. 14th International Conference on Software

Technologies - ICSOFT. Czech Republic.

Alcantara, A. S., Oliveira, S. R. B. (2021). A gamification

to support teaching-learning of knowledge manage-

ment in information technology: a plan based on fea-

tures of pedagogical approaches. 51th Annual Fron-

tiers In Education – Fie’21. USA.

Batista, A. F. S. (2019). EMOVERE: How we can use

emotions and affective computing in game design?

Dissertação de Mestrado em Design de Comunicação

e Novos Media. Faculdade de Belas Artes,

Universidade de Lisboa, Lisbon, Portugal.

Cardoso, W. R, Monteiro, R. S., Silva, A. M. M.,

Alcantara, A. S, Oliveira, S. R. B., Junior, R. V.,

Paiva, L. O. A. (2018). Quiz Teaches: A Tool to Sup-

port Basic Education Teaching (Elementary School

II). XVII Simpósio Brasileiro de Jogos e

Entretenimento Digital. Paraná, Brazil.

Damásio, A. (2006). Descartes' error: emotion reason and

the human brain. London: Vintage.

Gonçalves, L. L., Giacomazzo, G. F., Rodrigues, F.,

Macaia, C. B. S. (2016). Gamification in Education: a

conceptual model to support planning in a pedagogical

proposal. XXVII Simpósio Brasileiro de Informática

na Educação. Minas Gerais, Brazil.

Goulart, A. R. (2019). The Bankruptcy of the Current

Model of Higher Education in Information Technolo-

gy (IT). Dissertação de Mestrado em Ciências.

Faculdade de Economia, Administração e

Contabilidade de Ribeirão Preto, Universidade de São

Paulo.

Lopes, W., Fernandes, I., Augusto, P., Madeira, C. A. G.

(2021). Gamification strategy applied to emergency

remote teaching in times of COVID-19. XX SBGames.

Rio Grande do Sul, Brazil.

Oliveira, L. C., Oliveira, C. M., Oliveira, L. C., Pimentel,

A. R. (2019). Challenges in Distance Learning: Com-

putational Solutions for Collaborative Learning with

Affective Computing. VIII Workshop de Desafios da

Computação aplicada à Educação (DesafIE). Brazil.

Pudane, M., Petrovica, S., Lavendelis, E., Anohina-

Naumeca, A. (2018). Challenges in the Development

of Affective Collaborative Learning Environment with

Artificial Peers. Applied Computer Systems, 23(2),

101-108.

Reis, R. C. D., Isotani, S., Rodriguez, C. L., Lyra, K. T.,

Jaques, P. A., Bittencourt, I. I. (2018). Affective states

in computer-supported collaborative learning: Study-

ing the past to drive the future. Computers & Educati-

on, 120, 29-50.

Santos, M. de A., Grechi, J. G., Bermejo, P. H. de S.

(2010). Evaluating the Impact of SCRUM on Software

Development Using SWOT Analysis. XXX ENEGEP.

São Paulo, Brazil.

CSEDU 2022 - 14th International Conference on Computer Supported Education

496

Silva, E. L., Menezes, M. E. (2001). Research Methodolo-

gy And Dissertation Preparation. 3. Ed. Rev. Atual. –

Florianópolis: Laboratório De Ensino A Distância Da

Ufsc.

SOFTEX. (2016). MPS.BR - Brazilian Software Process

Improvement. Guia Geral. Versão 1.1, Brazil.

An Application of a Gamiﬁcation to Knowledge Management Teaching: A Qualitative Evaluation

497