Teaching Topics in Human-Computer Interaction: A Practical

Experience with a Focus on Experimental Research

Gabriela Corbari dos Santos

, Deivid Eive dos S. Silva

and Natasha M. Costa Valentim

Department of Informatics, UFPR, Federal University of Paran

a, Curitiba, PR, Brazil

gabrielacorbari@ufpr.br, {dessilva, natasha}@inf.ufpr.br

Keywords:

Primary Studies, Secondary Studies, Topics in HCI.

Abstract:

This paper presents the results and lessons learned from the course Topics in Human-Computer Interaction

(HCI) with a focus on experimental research. The course provides students with hands-on experience in plan-

ning, executing, and analyzing both primary studies (such as controlled experiments) and secondary studies

(such as systematic mapping studies) to develop essential research skills in the HCI ﬁeld. The course included

ﬁve undergraduate students, one external student, two postgraduate assistants, and one professor. Based on the

analyzed results, the main difﬁculties encountered by students in completing the practical works (PWs) were

identiﬁed, along with an assessment of their completeness and progression in each PW.

1 INTRODUCTION

Learning about experimental research is fundamental

for enabling future researchers and professionals to

plan, execute, and analyze studies—key components

of the scientiﬁc discovery process (Lazar et al., 2017).

Kitchenham et al. (2022) classify these studies into

two categories: primary and secondary. Primary stud-

ies involve empirical investigations that address spe-

ciﬁc research questions, while secondary studies syn-

thesize and analyze evidence from multiple primary

studies related to the same research question.

In this context, peer collaboration plays a cru-

cial role in knowledge construction, as it allows stu-

dents to share experiences, discuss challenges, and

develop joint solutions (Kaptelinin and Nardi, 2009).

The exchange of experiences among peers enriches

the learning process, providing diverse perspectives

and fostering an active and engaging educational en-

vironment. These practices are essential for prepar-

ing professionals to tackle the dynamic and complex

challenges of the Human-Computer Interaction (HCI)

ﬁeld.

The primary objective of this work was to enable

students to plan, execute, and analyze primary and

secondary studies on Topics in HCI through practical

assignments (PWs). The course was designed to de-

https://orcid.org/0000-0003-0864-1534

https://orcid.org/0000-0003-1066-0750

https://orcid.org/0000-0002-6027-3452

velop students’ critical thinking and analytical skills,

both of which are fundamental to scientiﬁc research.

The course methodology involved four PWs, each

focusing on a speciﬁc stage of the research process:

(1) planning, executing, and presenting a Systematic

Mapping Study (SMS), (2) planning, executing, and

presenting a pilot study, (3) conducting a quantita-

tive analysis of a primary study, and (4) conducting

a qualitative analysis of a primary study. Each PW

followed a structured sequence of steps with speciﬁc

instructions and appropriate tools, and students were

required to submit detailed reports upon completion.

The assignments were completed both individually

and in pairs.

To assess the experience, perceptions from stu-

dents, assistants, and instructors were gathered

through questionnaires and direct observations. Com-

parisons were also made between the PWs to identify

and analyze the difﬁculties faced by students. The

ﬁndings revealed that students struggled with under-

standing open and axial coding processes in qualita-

tive analysis. Additionally, one student who worked

in pairs found the experience to be more productive,

emphasizing collaboration as a key factor in making

the course more beneﬁcial.

In summary, this work contributes to the ﬁelds of

Informatics in Education and HCI by equipping stu-

dents with essential research skills through a practi-

cal and collaborative approach. This is crucial for ad-

dressing real-world challenges in both academia and

industry. Furthermore, the study reinforces the impor-

776

Santos, G. C., Silva, D. E. S. and Valentim, N. M. C.

Teaching Topics in Human-Computer Interaction: A Practical Experience with a Focus on Experimental Research.

DOI: 10.5220/0013340300003932

Paper published under CC license (CC BY-NC-ND 4.0)

In Proceedings of the 17th International Conference on Computer Supported Education (CSEDU 2025) - Volume 2, pages 776-783

ISBN: 978-989-758-746-7; ISSN: 2184-5026

tance of educational practices that promote collabora-

tion and active learning through specialized tools and

resources.

This paper is structured as follows: Section

2 presents related work, Section 3 describes the

methodology, Section 4 details the results, Section 5

discusses the lessons learned, Section 6 provides fur-

ther discussion, and Section 7 concludes with ﬁnal

considerations and future directions.

2 RELATED WORKS

This section presents examples of work that sought

to facilitate the dissemination of content and pro-

mote learning experiences through different educa-

tional approaches, such as constructionism and the

ﬂipped classroom. These studies used interactive re-

sources in face-to-face and online contexts intending

to enrich the teaching and learning processes.

Perin et al. (2021) reported on the experience of

using tools to support practical work in the Experi-

mental HCI course. The course offered remotely was

attended by undergraduate and postgraduate students

in computing, and the inverted classroom dynamic

was applied, in which students had access to the con-

tent before classes. A questionnaire was used to col-

lect the students’ perception of the tools, revealing

that some difﬁculties could be overcome by reading

support materials, further study of the tools, and con-

tact with tutors, teachers, and assistants.

Givan and Savage (2019) presented a construc-

tionist approach to working on learning experiences

in virtual worlds. 24 students from a postgraduate

course in Technology and Learning took part. Over

four weeks, the students, most of whom had no pre-

vious experience in programming or using the Second

Life platform, were grouped in pairs to take part in the

activity. The experience was part of a course module

that sought to integrate theory and practice. The ac-

tivity included orientation phases, workshops, and an

open assessment task, in which the students collabo-

rated to create interactive installations in the virtual

world. The installations were built on speciﬁc plat-

forms, with spaces visible to each other to promote

collaboration and socialization. At the end, the stu-

dents presented their projects and reﬂections, high-

lighting both the learning of programming and the

practical application of the concepts.

Martinelli and Zaina (2021) presented an ap-

proach based on a virtual ﬂipped classroom for teach-

ing HCI. The approach adds elements to both in-class

and out-of-class moments. 33 undergraduate and ten

postgraduate HCI students took part. Before the class,

the students interacted with the HCI course material

independently. Each week, the students focused on

learning a unit. During class, the students took part in

a synchronous meeting in an online room. After the

lesson, the students were organized in different on-

line rooms to carry out the practical exercise in small

groups. The authors collected data twice. The ﬁrst

was after the 5th week of classes, using a question-

naire about their experience with the different formats

of materials and activities in the classroom, using the

Self-Assessment Manikin (SAM) (Lang, 1980). The

second was through interviews with each group at the

end of the course.

As in the reports by Martinelli and Zaina (2021)

and Perin et al. (2021), the methodology used in

this work also uses ﬂipped classroom dynamics and

support tools to promote active learning. However,

it distinguishes itself by focusing on students’ ob-

servations and perceptions throughout different PW,

ranging from SMSs to primary studies and quantita-

tive analyses. Unlike Givan and Savage’s (2019) ap-

proach, which emphasizes virtual worlds, it integrated

both virtual and traditional tools, combining face-

to-face experiences and activities carried out outside

the classroom. While Martinelli and Zaina (2021)

explored the teaching of HCI, this methodology of-

fered students greater ﬂexibility in choosing tools and

methods for the experimentation process. The com-

bination of techniques and the careful assessment of

each PW reinforce students’ technical skills, prepar-

ing them to face real challenges in HCI research with

a cohesive and systematic integration of theory and

practice.

3 METHODOLOGY

3.1 Population and Sample

Regarding the population and sample, the perceptions

of the students, assistants, and teachers about the Top-

ics in the HCI course were analyzed. Five under-

graduate students took the course from the Federal

University of Paran

a (UFPR) and one external stu-

dent. The course also included two assistants who

are PhD students in Computer Science from the Post-

graduate Program in Informatics at UFPR (Figure1).

The course began on February 28, 2024, and ended

on August 9, 2024. The course has four hours per

week and a workload of 60 hours. Topics in HCI aim

to train students to be able to plan, execute, and ana-

lyze primary and secondary studies. Four PWs were

carried out to achieve this objective. Each PW has

its speciﬁcations and items to be carried out, so the

Teaching Topics in Human-Computer Interaction: A Practical Experience with a Focus on Experimental Research

777

assessment of the results delivered by the students is

based on these speciﬁcations. The teacher advised the

undergraduate students that they could work in pairs

or individually as they wished.

Figure 1: Population and sample.

3.2 Context

For the context, the four PWs are presented the Fig-

ure 2. PW1 consisted of planning, executing, and pre-

senting an SMS. To carry out the SMS, the students

were instructed to use the Porifera

(Campos et al.,

2022) tool (detailed in Subsection 3.3). For the plan-

ning stage, the teacher determined that the SMS pro-

tocol needed to meet a number of requirements: the

context to identify and describe the need for the SMS,

the objective of the SMS using the Goal-Question-

Metric (GQM) (Kitchenham and Charters, 2007), de-

ﬁne the main question and secondary questions, de-

ﬁne the search string, choose the data sources, de-

scribed the criteria adopted for selecting the data

sources and the restrictions associated with the study,

described the languages of the publications and jus-

tiﬁed the choice, deﬁned the selection criteria (inclu-

sion and exclusion) for the articles, and also deﬁned

the procedures adopted for selecting articles (1st and

2nd ﬁlter for selecting articles). For the researchers

involved, in Porifera, the students added the teacher as

a collaborator. For the pilot, they tested and retested

the search string to reﬁne it, always observing the re-

sults achieved in the digital libraries.

In order to carry out the SMS, some items had to

be met, such as: altering and/or adding some selection

criteria (inclusion and exclusion), deﬁning a data ex-

traction form, choosing one of the digital libraries de-

ﬁned in the protocol, and carrying out the search with

the string, considering the ﬁrst 30 articles returned by

the digital library and exporting them in Bibtex for-

mat so that they could then be imported into Porifera.

They carried out the 1st ﬁlter (reading the title and

https://porifera.app.br/

abstract) of the 30 articles in Porifera, then informed

the teacher so that she could also carry out her evalu-

ation and thus be able to generate consensus. They

carried out the 2nd ﬁlter (complete reading) of the

articles that had passed the 1st ﬁlter on Porifera and

then informed the teacher so that she could carry out

her assessment and thus generate a consensus. The

information from the 1st and 2nd ﬁlters should be de-

scribed in the report, as well as which articles passed

or failed and by which inclusion and exclusion crite-

ria. They interpreted the agreement and reliability in-

dices (Kappa) in Porifera. Finally, they extracted data

from at least one article that passed the 2nd ﬁlter and

described it in the report. For the SMS presentation,

the students had to develop slides and share them with

their classmates.

PW2 consisted of planning, executing, and pre-

senting a pilot study. The planning of the pilot study

had to take into account some items, including: deﬁn-

ing the objective of the study by the GQM (Kitchen-

ham and Charters, 2007), formulating null and al-

ternative hypotheses, selecting the dependent and/or

independent variables and how they were collected

and/or calculated, specifying the design of the study

for between group or within group (Lazar et al., 2017),

selecting the participants and the environment/place

where the study should be carried out, deﬁning the

instruments and preparing them, as well as devel-

oping instructions and deﬁning measurement proce-

dures. They also assessed threats to validity.

To carry out the pilot study, the student invited

at least two people to take part in their pilot study

and carry it out. In the report, they described the

personal characteristics and experiences of the pilot

participants. They described how the preparation for

the pilot was carried out, detailing the training and

instructions to the participants. They also described

how the experimental procedures were carried out in

the pilot. For the presentation of the pilot study, the

students had to develop slides and share them with

their classmates.

PW3 consisted of a quantitative analysis of a pri-

mary study. In this PW, students had to identify a

scientiﬁc article close to their research topic, which

described a statistical analysis of a study, and which

contained quantitative data to reproduce the statisti-

cal tests described in the article. They had to study

the statistical tests of the study identiﬁed in the arti-

cle and reproduce them using statistical software such

as SPSS

or R

(detailed in Subsection 3.3). Finally,

they developed a report containing the reproduction

of these tests, describing each step carried out during

https://www.ibm.com/br-pt/spss

https://www.r-project.org/

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778

Figure 2: Context.

the tests in the statistical software and showing the

results achieved.

PW4 consisted of developing and presenting a

qualitative analysis of a study. Students could choose

qualitative data obtained from a study related to the

research. This could be qualitative data from their pi-

lot study (PW2) if they had sufﬁcient data or from

a study reported in the literature that had access to

raw data. If they didn’t have any of these options,

they could collect qualitative data through an inter-

view, questionnaire, or observation on something re-

lated to the research topic. Next, the students had

to analyze and code the qualitative data, identifying,

naming, and recording recurring content in the com-

plete data set (open coding). Afterward, they exam-

ined the result they had in hand and found more ab-

stract categories into which the codes (classes of ev-

idence) from the previous stage were grouped (axial

coding). They also found signiﬁcant relationships be-

tween the categories. The students were generally in-

structed to proceed as they felt most productive, but

always maintaining systematicity and rigor in their

analysis. Finally, the students wrote a report describ-

ing (a) the analysis process, (b) the results, and (c)

the conclusions drawn from their work. Atlas.ti

was

a suggested software for coding and categorizing the

data (detailed in Subsection 3.3). The students devel-

oped slides and shared them with their classmates to

present the qualitative analysis.

In addition to this work, the students were respon-

sible for doing further reading and giving presenta-

tions on it. The readings included: the report by

Kitchenham and Charters (2007) on systematic liter-

ature review, chapter 5 on Survey, chapter 7 on Case

Study, chapter 5 on Statistical Analysis, and chapter

11 on Qualitative Analysis from the book by Lazar

et al. (2017). To ensure that everyone was involved

https://atlasti.com/

and ready to participate actively in the discussions,

a draw was held in each class to determine the pre-

senter, and students who had already presented were

not included in the subsequent draw. This format al-

lowed students to read beforehand and be prepared to

discuss the content, promoting mutual understanding

and collaborative learning, which are fundamental as-

pects of the success of the ﬂipped classroom. Each

student had between 20 and 30 minutes for their pre-

sentation.

3.3 Suggested Tools for PWs

To carry out PW1, the students were instructed to use

the Porifera (Campos et al., 2022) tool. Porifera is

a web application available at porifera.app.br. It is

aimed at researchers who will carry out SMS or Sys-

tematic Literature Reviews. Campos et al. (2022)

point out that Porifera has some advantages, such as

the inclusion of the Kappa coefﬁcient calculation (Co-

hen, 1960). Kappa is a Concordance Test that as-

sesses interobserver or intraobserver reliability (re-

producibility) for nominal categorical variables (Co-

hen, 1960).

The tool supports SMS planning as well as ex-

ecution. In the planning deﬁnition, the researcher

can indicate the objectives, search strategies, search

sources, and criteria for selecting primary studies. For

the objective, the tool suggests adding it based on

the GQM and also adding the main research ques-

tion. For the search strategies, the tool suggests using

PICOC (Population, Intervention, Comparison, Out-

come, and Context) to help form the string. As for

research sources, the tool allows you to add the dig-

ital libraries that will be used. Finally, the selection

criteria (inclusion criteria and exclusion criteria) will

be used in the article selection process, where the tool

supports adding them and consulting them when nec-

essary.

Teaching Topics in Human-Computer Interaction: A Practical Experience with a Focus on Experimental Research

779

To import the digital library ﬁles into the tool,

Campos et al. (2022) recommend using the Bibtex

format. Another advantage of the tool is that during

the import process, it displays records with incom-

plete data that need to be checked and, if necessary,

adjusted.

The SMS is run based on the imported ﬁles, i.e.

on the list of publications. The selection of articles

is organized into two phases (two ﬁlters), indicated

in the tool as “First” and “Second”. Thus, the re-

searcher will select a criterion and optionally add a

comment on their evaluation. When there is agree-

ment between the evaluation criteria, the tool will

prompt the researcher to conﬁrm this. If there is a

disagreement between the researchers, the tool will

show the disagreement between the evaluations. The

authors also considered that it is not possible to view

the reviews of other researchers before carrying out

your own review. Therefore, the researchers will dis-

cuss and ﬁnally come to a consensus. According to

the authors, this is another distinguishing feature of

the tool, where it allows the stability and evaluations

of each researcher to be carried out.

During the selection process, Porifera displays a

dashboard to keep track of information about each se-

lection phase. It also displays the concordance index

and reliability index, as shown in Figure 3.

Figure 3: Porifera software (in Portuguese).

For the PW3, it was suggested that two tools be

used for the study’s statistical tests: SPSS, available at

https://www.ibm.com/br-pt/spss and/or R, available

at https://www.r-project.org/.

The Statistical Package for the Social Sciences

(SPSS) is a statistical software program that allows

you to analyze data, create graphs and reports, and

perform statistical tests. One of the advantages of us-

ing SPSS is that it allows you to import and export

data from other programs, and can merge ﬁles with

different subjects and variables. It was developed in

the 1960s and is currently maintained by IBM and is

known as IBM SPSS Statistics (Verma, 2012).

The disadvantage of using SPSS is that it can

be challenging for beginners, as you need computer

skills to manage it fully (Verma, 2012). We have

added an example of the interface found in this soft-

ware (Figure 4).

The R software is a free software environment for

statistical computing and graphics (Figure 5) (Cham-

bers, 2008). One of its distinguishing features is that

Figure 4: SPSS software.

it compiles and runs on various platforms such as

UNIX, Windows, and MacOS. The software supports

various statistical techniques such as linear and non-

linear modeling, classical statistical tests, time series

analysis, classiﬁcation, clustering, and graphics, and

is highly extensible (Chambers, 2008).

One advantage of using the software is the ease

with which well-designed publication-quality graph-

ics can be produced, including mathematical symbols

and formulas where necessary (Chambers, 2008).

Figure 5: R software.

And for PW4, the Atlas.ti tool available at https:

//atlasti.com/ was suggested (Figure 6). Atlas.ti is a

qualitative data analysis software that can be used to

search and analyze abundant textual, graphic, audio,

and video data.

The tool helps organize and manage data system-

atically and creatively, helping to optimize the ana-

lytical process. One of Atlas.ti’s differentials are that

it has features such as advanced coding, multimedia

analysis, visualization, and real-time collaboration.

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780

Figure 6: Atlas.ti software (in Portuguese).

4 RESULTS: PERCEPTIONS AND

MEASURES TAKEN

4.1 Main Difﬁculties of Understanding

Regarding the main difﬁculties observed during the

development of the PWs, it is important to highlight

that in PW1, students faced challenges in using the

GQM method, particularly with the phrase “for the

purpose of”. To address this issue, the teacher pro-

vided in-class examples to help clarify the students’

understanding and reinforce the correct application of

GQM. Another difﬁculty arose when students were

required to use the PICOC framework to develop the

search string. To assist with this, the teacher used the

students’ own topics to demonstrate how to formu-

late a proper search string, familiarizing them with

the PICOC approach and its relevance to the task.

Additionally, some students struggled with un-

derstanding the purpose of conducting a Systematic

Mapping Study (SMS) and the justiﬁcation for its im-

portance. To help address this, the teacher introduced

relevant article examples, guiding students to reﬂect

on the signiﬁcance of the SMS in the context of their

research topics. In PW4, the main difﬁculties were as-

sociated with the qualitative analysis process. During

the presentation on qualitative coding, some students

had trouble grasping the concepts of open and axial

coding. To aid their comprehension, the teacher con-

ducted a hands-on coding exercise on the whiteboard,

encouraging all students to participate. This interac-

tive approach helped improve their understanding of

the coding process.

Another difﬁculty reported by students was in us-

ing the suggested tool for qualitative analysis, Atlas.ti.

One student had trouble ﬁnding the option for axial

coding within the software. To cope with this, she

resorted to using alternative methods. For example,

another student found it easier to use spreadsheets

for both open and axial coding instead of the Atlas.ti

tool, as they felt more comfortable with this approach.

These challenges underscore the importance of offer-

ing additional practice, demonstrations, and ﬂexibil-

ity in tool usage to ensure that students can effec-

tively engage with the methodologies and tools being

taught.

4.2 Completeness and Evolution of the

Students in Each PW

Regarding the completeness and evolution of the stu-

dents in each Practical Work (PW), an analysis was

conducted of both the pair (PA) and the four students

who completed the PWs individually (P1, P2, P3, and

P4).

In PW1, several items were either not described

or described incompletely in the reports. These in-

cluded: the need for the SMS topic (PA, P2), the

study’s aim according to the GQM framework (PA,

P1, P4), the search string according to the PICOC

framework (PA, P1, P3, P4), the selection of data

sources (P1), the justiﬁcation for choosing these

sources (P3, P4), the description of restrictions asso-

ciated with the study (PA, P2, P3, P4), the selection of

languages (P2), the selection procedures and criteria

(P1, P2, P3, P4), the execution of the pilot study (P1,

P2), modiﬁcations and/or additions to selection crite-

ria (P1), deﬁning the data extraction form (PA, P1, P3,

P4), running the search with the string (P1), selecting

the 30 articles to export in Bibtex format and import-

ing them into Porifera (P1), running the ﬁrst ﬁlter (P1,

P2, P4), running the second ﬁlter (P1, P2, P4), in-

terpreting the concordance and reliability indices (P1,

P3, P4), and extracting an article that passed the sec-

ond ﬁlter (PA, P1, P3, P4).

In PW2, the following items were either missing

or incompletely described: the objective of the study

according to the GQM framework (P3, P4), the for-

mulation of null and alternative hypotheses (P3, P4),

the selection of dependent and independent variables

(P3), how these variables will be collected and/or cal-

culated (PA, P1), the speciﬁcation of the study design

(P1, P4), the deﬁnition of the instruments (P1, P3),

the assessment of threats to validity (P4), and the de-

scription of personal characteristics of the pilot study

participants (P1). For PW3, all the students who com-

pleted the PW did so fully, but P2 and P4 did not

carry out this PW. In PW4, only P1 completed the task

but did not present his study, while the other students

completed it as expected.

These results show that in the ﬁrst two PWs, the

pair of students failed to complete certain items—six

items in PW1 and one item in PW2. However, for

the other PWs, the students completed all the required

tasks. This led to some conjectures: the pair may

have faced challenges in communication and collab-

oration, which were addressed during the course to

Teaching Topics in Human-Computer Interaction: A Practical Experience with a Focus on Experimental Research

781

ensure that the subsequent PWs met all the expected

requirements. Another possibility is that the ﬁrst PWs

(1 and 2) were more complex and required more time

to complete, which may have contributed to the stu-

dents’ struggles. As the number of items increased in

each PW, the students dedicated more time and effort

to ensure completion.

On the other hand, when analyzing the students

who completed the PWs individually, it is evident

that they faced more challenges in completing the

tasks. It was only in PW3 and PW4 that these students

were able to complete nearly all the required items.

This suggests that, as undergraduates, the individual

students may have struggled more due to the heavy

workload of the PWs. In contrast, the pair of students

found it easier to manage the workload and complete

most of the tasks. Therefore, for future iterations of

the course, it is recommended that students be encour-

aged to complete the PWs in pairs, which would likely

enhance their ability to manage the workload effec-

tively and complete tasks more efﬁciently.

Finally, one student who worked in pairs shared

his experience, stating: “I found it more productive

because when I had doubts, I would ask my partner,

and he would either have the answer or help me ﬁgure

it out. This collaboration made the subject more use-

ful”. The student also emphasized the importance of

the practices carried out in the course, saying:‘ ‘This

subject is something that I believe should be manda-

tory in the program because reading and understand-

ing articles, conducting tests, and understanding sta-

tistical and qualitative analysis are essential skills in

academia.”

5 LESSONS LEARNED

The results presented in Section 4 highlight key

lessons from the experience with the Topics in HCI

course. Firstly, the course’s importance was reaf-

ﬁrmed by positive student feedback, emphasizing the

relevance of the PWs in developing essential skills.

Conducting the PWs in pairs proved beneﬁcial for

undergraduate students, as it facilitated knowledge

exchange and encouraged discussions that deepened

their understanding of the topics. Allowing students

to choose between working in pairs or individually

was valuable, but it also underscored the need for

greater guidance for those who opted to complete the

PWs individually.

Another signiﬁcant challenge was the students’

difﬁculty in using GQM to deﬁne research objectives

and PICOC to construct the search string in PW1. To

address this, the instructor implemented a practical

exercise with examples from different topics. This

experience underscored the importance of providing

detailed instructions and additional practice. A rec-

ommended approach involves presenting each con-

cept individually on the whiteboard, followed by in-

teractive activities with post-it notes to reinforce un-

derstanding.

In PW4, students also faced difﬁculties with open

and axial coding. To improve comprehension, the

instructor used a practical approach, illustrating the

coding process on the whiteboard. This method

proved effective and highlighted the necessity of di-

versifying teaching strategies. While slide presen-

tations and digital tools were useful, interactive and

hands-on teaching methods provided a more profound

grasp of the concepts.

Regarding the use of Atlas.ti for qualitative anal-

ysis, students encountered various challenges. Some

struggled to utilize all the tool’s features, while others

chose alternatives such as spreadsheets or visual aids

like color-coding to differentiate themes. These ob-

servations reinforce the importance of offering ﬂexi-

bility in the selection of methods and tools for com-

pleting PWs. The key takeaway is that while speciﬁc

tools can be valuable, ensuring ﬂexibility in analysis

tools is essential to accommodate different learning

preferences and enable all students to complete their

tasks successfully.

Finally, this study provides insights into the In-

formatics in Education community by emphasizing

the need to adapt teaching methodologies to stu-

dents’ diverse needs. The analysis of challenges and

the strategies implemented can serve as a foundation

for improving courses that involve practical learning

and scientiﬁc inquiry, offering guidance for educators

seeking to enhance their pedagogical approaches.

6 CONCLUSIONS AND FUTURE

WORK

The Topics in HCI course aimed to train students in

conducting both primary and secondary studies. Ana-

lyzing the results of the four Practical Works (PWs)

allowed us to identify critical challenges and key

lessons learned.

The ﬁndings reveal that students encountered dif-

ferent difﬁculties in each PW. In PW1, challenges

arose in applying the GQM approach and formulat-

ing the search string, which required practical inter-

ventions and additional examples from the instructor.

In PW4, students struggled with qualitative coding,

particularly in using the Atlas.ti tool and performing

open and axial coding. Practical interventions, such

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as whiteboard exercises and classroom discussions,

enhanced students’ understanding.

Student progress analysis indicated that working

in pairs was more beneﬁcial for undergraduates, as

it fostered greater productivity and collaboration. In

contrast, students who completed the PWs individu-

ally encountered more difﬁculties, leading to incom-

plete work in some cases. This result underscores the

importance of encouraging pair work as an effective

strategy for improving student performance.

A key limitation observed was the difﬁculty in us-

ing the proposed tools and methodologies, such as At-

las.ti and GQM, which remained signiﬁcant obstacles

for some students. These difﬁculties may have im-

pacted their performance and comprehension of the

PWs. To address this, we recommend incorporating

additional hands-on exercises and targeted demon-

strations of the tools and methodologies used. Fur-

thermore, providing extra support for qualitative anal-

ysis tools and fostering a more structured collabora-

tive environment could enhance both teaching effec-

tiveness and student learning in future course itera-

tions.

Building on the lessons learned, a future direc-

tion involves deﬁning a set of guidelines based on

these insights to assist educators in structuring sim-

ilar courses. These guidelines would provide practi-

cal recommendations on instructional strategies, tool

integration, and collaborative learning approaches,

helping instructors navigate common challenges and

optimize student engagement and learning outcomes.

ACKNOWLEDGEMENTS

We would also like to thank the Coordination of Su-

perior Level Staff Improvement (CAPES) for their ﬁ-

nancial support—Finance Code 001 and the Coordi-

nation for the Improvement of Higher Education Per-

sonnel (CAPES)—Program of Academic Excellence

(PROEX).

REFERENCES

Campos, T., Damasceno, E., and Valentim, N. M. (2022).

Proposta e avaliac¸

ao de um si colaborativo para apoio

a revis

oes sistem

aticas e estudos de mapeamento. In

Anais do XVIII Simp

osio Brasileiro de Sistemas de

Informac¸

ao (SBSI).

Chambers, J. M. (2008). Software for data analysis: pro-

gramming with R. Springer.

Cohen, J. (1960). A coefﬁcient of agreement for nominal

scales. Educational and psychological measurement,

20(1):37–46.

Girvan, C. and Savage, T. (2019). Virtual worlds: A new

environment for constructionist learning. Computers

in Human Behavior, 99:396–414.

Kaptelinin, V. and Nardi, B. A. (2009). Acting with tech-

nology: Activity theory and interaction design. MIT

press.

Kitchenham, B. and Charters, S. (2007). Guidelines for per-

forming systematic literature reviews in software engi-

neering. Citeseer.

Kitchenham, B., Madeyski, L., and Budgen, D. (2022).

Segress: Software engineering guidelines for report-

ing secondary studies. IEEE Transactions on Software

Engineering, 49(3):1273–1298.

Lang, P. (1980). Behavioral treatment and bio-behavioral

assessment: Computer applications. Technology in

mental health care delivery systems, pages 119–137.

Lazar, J., Feng, J. H., and Hochheiser, H. (2017). Re-

search methods in human-computer interaction. Mor-

gan Kaufmann.

Martinelli, S. R. and Zaina, L. A. (2021). Learning hci from

a virtual ﬂipped classroom: improving the students’

experience in times of covid-19. In Proceedings of

the xx brazilian symposium on human factors in com-

puting systems, pages 1–11.

Perin, A., Paim, P., and Valentim, N. (2021). Experi

encia

sobre o uso de ferramentas de apoio

a pesquisa exper-

imental em uma disciplina de ihc. In Anais do XXXII

Simp

osio Brasileiro de Inform

atica na Educac¸

ao,

pages 1297–1307, Porto Alegre, RS, Brasil. SBC.

Verma, J. P. (2012). Data analysis in management with

SPSS software. Springer Science & Business Media.

Teaching Topics in Human-Computer Interaction: A Practical Experience with a Focus on Experimental Research

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