Understanding the Student Experience Better: Analyzing Remote

Learning Tools Through Engagement, Participation, and Liveness

Concepts

Genildo Gomes

1 a

, Paulo Silva

1 b

, S

amila Magalh

aes

2 c

, Leandro Galv

1 d

Tanara Lauschner

1 e

, Igor Steinmacher

3 f

, Tayana Conte

1 g

and Bruno Gadelha

1 h

Institute of Computing, Federal University of Amazonas, Manaus, AM, Brazil

Department of Design and Graphic Expression, Federal University of Amazonas, Manaus, AM, Brazil

School of Informatics, Computing, and Cyber Systems, Nothern Arizona University, Flagstaff AZ, U.S.A.

{genildo.gomes, pvdsf, galvao, tanara, tayana, bruno}@icomp.ufam.edu.br,

Keywords:

Remote Learning, Educational Technologies, Student Engagement, Interactive Tools, Participation, Liveness,

Online Education, Digital Engagement.

Abstract:

Technologies have changed how students engage and participate during remote classes, whether by encour-

aging interaction via chat on platforms such as Google Meet or by using voting features such as Poll. Our

research aims to better understand the role of these tools in the educational context and how their interac-

tive features inﬂuence student experience through the lens of engagement, participation, and liveness. In this

sense, we address the following question: How can educational technologies be classiﬁed by the Engagement,

Participation, and Liveness lens? To explore the relationship between the lens and the interactive features

of Mentimeter, Google Meet, and Google Presentations, we conducted a study with three independent eval-

uations, measuring agreement using Cohen’s Kappa coefﬁcient. Our results suggest that these interactive

features can be used as a lens to understand different types of experiences and how they can be applied to

promote various dynamics, such as competitive and collaborative activities. Our results expand the professor’s

perspective on the student experience, providing ways for professors to understand the emotional and student

behavioral reactions from using interactive tools in remote learning environments.

1 INTRODUCTION

Remote teaching is a strategy for delivering edu-

cational content and facilitating communication be-

tween students and teachers without requiring phys-

ical presence (Umar, 2023). In this context, teach-

ers face challenges when conducting their courses,

such as a lack of social interactions, technical limita-

tions, motivation, and lack of active student engage-

ment (Ahshan, 2021). Engaging students is essential

for teachers to accomplish their learning objectives.

https://orcid.org/0000-0002-2901-3994

https://orcid.org/0000-0003-2403-0370

https://orcid.org/0009-0006-1441-8514

https://orcid.org/0000-0003-2970-2084

https://orcid.org/0000-0001-7104-9432

https://orcid.org/0000-0002-0612-5790

https://orcid.org/0000-0001-6436-3773

https://orcid.org/0000-0001-7007-5209

Technologies that support the creation of inter-

active presentations and lessons, like Nearpod

, for

example, facilitate more interactive and participa-

tory learning experiences in the remote context (Pu-

tra et al., 2021). Still, virtual whiteboards support

students’ engagement when they are trying to under-

stand abstract concepts (Reguera and Lopez, 2021).

Even simpler interactive features such as Google

Meet Breakout Room inﬂuence how students learn

and interact in remote online sessions (Ahshan, 2022).

The use of technologies in remote learning has made

it possible to explore different factors in the student

experience, such as positive and negative responses

to using technologies (Aguiar et al., 2022), how col-

laboration involves student engagement (Gopinathan

et al., 2022), even interactivity and solitude (Kohnke

and Foung, 2023).

https://nearpod.com/

958

Gomes, G., Silva, P., Magalhães, S., Galvão, L., Lauschner, T., Steinmacher, I., Conte, T. and Gadelha, B.

Understanding the Student Experience Better: Analyzing Remote Learning Tools Through Engagement, Participation, and Liveness Concepts.

DOI: 10.5220/0013481200003932

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 958-965

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

These factors help educators and researchers an-

alyze how technologies inﬂuence student behavior

and reactions, allowing them to redesign learning en-

vironments to enhance engagement and interactions

(Gopinathan et al., 2022). However, there is no ap-

proach to combining different factors that help teach-

ers and researchers understand student experiences

using remote teaching tools.

Gomes et al. (2023) introduced a taxonomy to

classify and explain audience experience in various

events, including scientiﬁc and educational settings

like conferences and lectures. This experience, when

mediated by technology, can be analyzed through

three key dimensions: engagement, liveness, and par-

ticipation. These perspectives offer a theoretical foun-

dation for understanding interaction in diverse con-

texts, from entertainment and sports to education.

These perspectives can be applied to remote learn-

ing, where technological tools enhance student en-

gagement, encourage collaboration, and support ac-

tive participation in educational activities.

Considering the ways that technologies may inﬂu-

ence student experience in remote learning, we aim

to answer the following question: How can educa-

tional technologies be classiﬁed by the Engagement,

Participation, and Liveness lens? This classiﬁcation

is essential to understand one or more aspects of the

student experience. We understand the student expe-

rience as the emotional, cognitive, behavioral, and so-

cial experience through interacting with products, ser-

vices, or systems in the educational context (Matus

et al., 2021). In this sense, we observed the interac-

tive features used in remote settings through the lens

of engagement, participation, and liveness presented

by Gomes et al. (2023).

To answer this question, we analyzed 3 tools –

Mentimeter, Google Meet and Google Presentations–

used in remote learning. As a result, we suggest that

these interactive features of each tool can be used as

a lens to understand different types of experiences

and how they can be applied to promote various dy-

namics, such as competitive and collaborative activi-

ties. We also proposed a recommendation system to

support the teachers in ﬁnding technologies based on

student experience, helping them to promote engage-

ment, participation, and liveness in the classroom.

2 THEORETICAL FRAMEWORK

In this section, we discuss the main concepts related

to remote learning and how technological tools en-

hance dynamic and collaborative student-teacher in-

teractions.

2.1 Remote Learning and Typology of

Digital Learning Tools

Remote learning can be deﬁned as a set of pedagog-

ical practices mediated by digital platforms (Rova-

dosky and Agostini, 2021). Tools like Microsoft

Teams, Google Classroom, Google Meet, and Zoom

play a fundamental role in providing both syn-

chronous and asynchronous interaction, allowing the

continuation of the teaching-learning process, espe-

cially during the pandemic. These platforms be-

came vital to maintaining educational activities in

the global emergency caused by the COVID-19 pan-

demic, enabling teachers and students to stay con-

nected even from a distance. Although remote teach-

ing has gained prominence during the pandemic,

teachers continue approaching it as a strategy for on-

line courses (O’Connor et al., 2023).

Given this scenario, it becomes important to un-

derstand how interactions in the remote environment

shape the learning process. Sims (1999) emphasizes

that interactivity plays an essential role in the educa-

tional environment, allowing students to have control

over the learning process, as well as enabling adap-

tations according to their needs. Digital tools enable

different forms of communication and collaboration,

promoting new interaction dynamics between teach-

ers and students.

In this sense, Bower (2016) classiﬁes Web 2.0

technologies for education into 37 types across 14

clusters. These tools support both real-time and asyn-

chronous discussions, as well as content creation and

sharing. Examples like Google Docs, Jamboard, and

Kahoot show how they enhance collaboration and

interaction. In remote teaching, these technologies

are especially useful for boosting student engagement

and improving communication between teachers and

students.

This paper delves into the analysis of three spe-

ciﬁc technologies—Google Meet, Mentimeter, and

Google Presentations—all classiﬁed according to

Bower’s typology and effectively employed in remote

teaching.

2.2 A Taxonomy to Understand

Audience Experience

The taxonomy proposed by Gomes et al. (2023) was

conceived to understand audience experience using

technologies in different events, such as entertain-

ment, cultural, sport, and educational events. The tax-

onomy offers a perspective for analyzing technologi-

cal interactions in events through three main lenses:

Engagement, Participation, and Liveness.

Understanding the Student Experience Better: Analyzing Remote Learning Tools Through Engagement, Participation, and Liveness

Concepts

959

Engagement. Engagement is an essential dimen-

sion in technological interactions, involving cogni-

tive, emotional, and behavioral aspects. These aspects

include motivation, attention, and user interactivity.

The conceptual framework of engagement is divided

into three units of analysis: viewer, crowd, and audi-

ence.

Viewer comprises an individual perspective of the

spectator, and encompasses concepts such as immer-

sion, sociality, solitude, interactivity, and immediacy.

Crowd comprises a perspective of a large number of

people together, such as in music festivals or foot-

ball matches. The crowd perspective is related to the

concept of collective effervescence, a dynamic where

large groups share emotions and collective engage-

ment in real-time. Audience refers to spectators or

listeners in an event that does not necessarily repre-

sent a crowd. The audience perspective comprises the

audience’s emotional response, focusing on concepts

such as arousal and valence (positivity or negativity

of emotions) while using technologies.

Participation. Participation unit analysis comprises

the characteristics and consequences of participation

using technologies, and is related to both active and

passive behaviors. This dimension is structured from

four perspectives: Time, Space, Qualities, and Moti-

vation.

Time is divided into reﬂective and immediate. The

reﬂective facet reﬂects on the impact of the experi-

ence after the performance when the viewer processes

the experience and reﬂects on their feelings and learn-

ings. Space refers to the characteristics of the space

where the audience interacts and participates, associ-

ated with the perspective. Qualities refer to emerg-

ing attributes or characteristics of how participants

engage in interactive performance, they are classiﬁed

into constitutive, epistemic, and critical. Motivation

is related to the audience’s intention to participate,

exploring how collaboration and competition can be

used to enhance participation. Motivation, in the con-

text of interactive events, is linked to the desire to ac-

tively participate and experience new things.

Liveness. This dimension captures the sense of pres-

ence and spontaneity in an event, emphasizing the

feeling of “being live”. This dimension is supported

by the concepts of Flow and Presence.

Flow describes the state of total concentration in

an activity, where the individual feels deeply engaged

and connected to what they are doing. In the con-

text of technological interaction, this state is achieved

when elements such as engagement, concentration,

learning, challenge, and a shared atmosphere create

an experience that resonates personally with the par-

ticipant, generating an intense and ﬂuid connection

with the activity at hand.

Presence represents how effectively an event cap-

tures spectators’ attention and the intensity of their

engagement. The presence is related to co-presence,

social presence, sense of unity, and sense of belong-

ing.

3 RELATED WORK

Several technologies are evaluated considering the

student experience through engagement and partic-

ipation, such as Video Conference or Gamebased

tools. Najjar et al. (2022) investigate what game-like

features can be used to engage and motivate students

in an online learning environment. Their ﬁndings sug-

gest an increased level of interactivity, collaboration,

and satisfaction through the game features, enhancing

the student learning experience. Similarly, Nadeem

et al. (2023) examine the effect of game-based learn-

ing on student engagement and motivation levels. The

ﬁndings reveal the positive and negative impacts on

student engagement emotions due to the competitive

features.

In the literature, researchers use these tools to en-

hance learning during the course, aiming to improve

student engagement. For example, Ahshan (2021)

investigates strategies for active student engagement

in remote teaching and learning during the COVID-

19 Pandemic. The authors present a framework in-

tegrating technology, pedagogy, and active learning

to boost student engagement in remote teaching, uti-

lizing tools like PowerPoint, Google Meet, and Men-

timeter.

While previous studies aimed to understand or im-

prove the student experience in remote teaching, they

did not examine the individual impact of interactive

features. Although some authors explored isolated

concepts, there is no structured approach to compre-

hensively analyze student experience. Our work seeks

to bridge this gap by providing a framework to as-

sess student experience and engagement through the

lenses of engagement, participation, and liveness.

4 METHOD

To address the research question “How can educa-

tional technologies be classiﬁed by the Engagement,

Participation, and Liveness lens? ”, we analyzed how

the concepts of engagement, participation, and live-

ness are incorporated into the interactive features of

remote learning tools.

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960

The analysis was structured into four main steps.

In the ﬁrst step, we executed an exploratory litera-

ture review, aiming to identify which technologies are

used in educational remote settings. During the lit-

erature review, we identiﬁed a study (Ahshan, 2021)

proposing a framework to promote student engage-

ment for remote teaching. The study mentions 15

technologies that users could use by the framework

to promote student engagement during remote class,

such as Mentimeter, Google Slides, and Google Meet.

We used these technologies as a base.

In the second step, we used Bower (2016)’s ty-

pology to classify the 15 technologies, aiming to un-

derstand the differences between these technologies.

Bower (2016) provides a set of 14 categories to clas-

sify different learning tools, e.g., Mentimeter and Ka-

hoot are classiﬁed as “Evaluation tools” for promot-

ing online quiz-based dynamics. We performed a

classiﬁcation by aligning the category descriptions

with the objectives of each of the 15 technologies.

The Table 1 present the technologies classiﬁed.

Table 1: Table of technologies classiﬁed based on the typol-

ogy of Bower (2016).

Tool Classiﬁcation

Moodle

Learning Management Systems cannot

be classiﬁed in the typology as they are

essentially a package of tools that can

cover all other categories.

Mentimeter Assessment tools

Kahoot Assessment tools

Slido Assessment tools

Prezi Multimodal production tools

Google Slides Multimodal production tools

Keynote Multimodal production tools

Google Meet Synchronous collaboration tools

ZOOM Synchronous collaboration tools

BigBlueButton Synchronous collaboration tools

Webex Meetings Synchronous collaboration tools

GoToMeeting Synchronous collaboration tools

Jamboard

Text-based tools

Image-based tools

Google Meet

Breakout Room (GMBR) Synchronous collaboration tools

Google Chat Synchronous collaboration tools

After classifying technologies according to Bower

(2016)’s typology, in the third step, we selected one

tool from each category according to theGomes et al.

(2023) taxonomy lens. The sample comprises 4 tools

that offer interactive features: Mentimeter (Assess-

ment tools), Google Slides (Multimodal production

tools) and Google Meet (Synchronous collaboration

tools), and Jamboard (Text-based tools and Image-

based tools). These tools were selected based on the

authors’ familiarity with them and their extensive ex-

ploration in the existing literature. However, due to

product discontinuation issues, we did not analyze

the Jamboard tool

. Therefore, we analyzed 3 tools:

Mentimeter, Google Meet, and Google Presentations.

The interactive features are the tools features that of-

fer support to engagement and participation. We ex-

plain the third step in detail in Section 4.1.

In the fourth step, we developed STARS (Student

Technology Advanced Recommendation System), a

recommendation system prototype to support profes-

sors in deciding how to promote engagement and par-

ticipation in remote classes. STARS comprises the

analysis results obtained in the third step to recom-

mend technologies based on Gomes et al. (2023) tax-

onomy concepts. In Section 5.1, we present more

about STARS.

Table 2: Interactive features analyzed based on educational

technologies.

Tool Interactive Features

Mentimeter Live Polling

Word Cloud

Quiz

Q&A

Presentations

Google Slides Presentations

Google

Meet

Virtual backgrounds and visual effects

Screen sharing with other participants

Chat

Emoji Reactions

Turn video on/off

Turn microphone on/off

4.1 An Analysis of Engagement

Characteristics in Remote Teaching

In this section, we explain in detail the analysis of the

interactive features through Gomes et al. (2023) tax-

onomy. This analysis aimed to understand the role of

these tools in the educational context and how their in-

teractive features inﬂuence student engagement, par-

ticipation, and liveness. Table 2 presents the selected

tools and the interactive features classiﬁed.

To understand how to promote engagement, par-

ticipation, and liveness in remote learning environ-

ments, we analyzed the interactive features of the

tools using the Gomes et al. (2023) taxonomy. The in-

teractive features were extracted from the exploration

of the tools carried out by one of the researchers,

and the main resources of each tool were identi-

ﬁed. For each interactive feature, we pointed out

the concepts related to each taxonomy lens and an

explanation of how the interactive feature inﬂuences

the occurrence of the factor. This process involved

two researchers independently identifying the taxon-

https://support.google.com/jamboard/answer/

14084927?hl=en

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Concepts

961

omy concepts present in each tool. For each interac-

tive feature, the researchers justiﬁed their perceptions

without access to the others’ justiﬁcations, ensuring

impartiality in the analysis. In addition to the justiﬁ-

cation, the researchers assigned a value from 0 to 2 for

each evaluated concept, using the following scale: 0,

the interactive feature doesn’t support the concept; 1,

the interactive feature slightly supports the concepts;

2, The interactive feature fully supports the concepts.

In the end, the researchers discussed until they

reached a consensus. A third researcher played a me-

diator role in discussions, ensuring that perceptions

were aligned and that the analyzed concepts were in-

terpreted coherently in the context of the tools. The

third researcher also conducted an independent eval-

uation through the classiﬁcation. As both researchers

classiﬁed them independently, it was necessary to

verify the degree of agreement of this classiﬁcation.

In this sense, we used Cohen’s Kappa coefﬁcient of

agreement.

Cohen’s Kappa is a coefﬁcient to measure the de-

gree of agreement between two judges when catego-

rizing items into nominal categories (Cohen, 1960).

The value of Cohen’s kappa ranges from -1 to +1.

The closer it gets to +1 indicates perfect agreement

degree between the raters, and the closer it gets to -

1 indicates that the agreement degree does not match

between the judges.

We executed three rounds of analysis followed

by a Kappa calculation. In the ﬁrst round, we com-

pared the Mentimeter-Quiz classiﬁcation between the

researcher’s agreement, which resulted in 0.41 (Mod-

erate). The researchers discussed the classiﬁed di-

vergence points to get a shared sense of the clas-

siﬁcations. In the second round, we compared

the Mentimeter-Live Polling and Google Slides-

Presentations, which resulted in 0.62 (Good) and

0.43 (Moderate) agreement, respectively. The re-

searchers discussed the divergence points again and

executed a new round. The third round was con-

ducted to analyze Mentimeter-Q&A, and Mentimeter-

World Cloud, which resulted in Kappa of 0.75 (Good)

and 0.76 (Good), respectively. These results indi-

cate that the interpretation between the classiﬁca-

tions was aligned (Landis and Koch, 1977). After

this, we reviewed all the interactive feature classiﬁ-

cations, reviewed the assigned scale, and rewrote the

justiﬁcation-based researcher’s agreement.

This collaborative approach ensured that the anal-

ysis of the interactive features of these tools was ro-

bust and accurately reﬂected each one’s potential to

promote engagement, participation, and liveness in

remote teaching.

5 RESULTS

In this section, we report the result of the analysis of

interactive features of 3 tools—Google Meet, Men-

timeter, and Google Presentations— according to the

Gomes et al. (2023)’s taxonomy lens. In Table 3, we

present the results.The “X” represents when a feature

was classiﬁed by some concept in the taxonomy.

By analyzing Table 3, one can notice that these

interactive features are more closely tied to interac-

tion and the exchange of information among students

and professors, given that most interactive features are

predominantly associated with Immersion, Interactiv-

ity, Social Presence, and Co-Presence. Other con-

cepts, such as Collective Effervescence and Compe-

tition, were less evident. Collective Effervescence

could be identiﬁed through a high volume of mes-

sages exchanged in the chat, while Competition was

more noticeable when the Quiz feature was used to

test student’s knowledge.

We noticed that some interactive features focus

more on enhancing User Experience (UX) rather than

directly boosting engagement or student participation.

For example, in Google Meet, Virtual Backgrounds

and visual effects primarily improve UX by creating

a more relaxed and friendly environment, rather than

signiﬁcantly increasing interaction or connection be-

tween participants.

Next, due to the paper length limitation we detail

the classiﬁcation of Quiz interactive feature of Men-

timeter. The full results with the justiﬁcation of each

taxonomy concept are available in the supplementary

material

. We chose the Quiz to present in the paper

because it was one of the interactive resources that in-

volved most of the taxonomy concepts.

Considering the Engagement lens, the Quiz was

classiﬁed by the perspectives of the Audience and

Viewer. From the Audience’s perspective, the con-

cepts of Arousal could be perceived when the quiz

results are presented, while Valence is perceived by

the attention and student willingness during the Quiz,

impacting the emotions that may arise due to the quiz

results. From a Viewer’s perspective, we classiﬁed it

as Immersion, Interactivity, and Immediacy. The Quiz

can intensify the state of Immersion in the class, creat-

ing an interactive experience that could inﬂuence the

energy and excitement of the viewer to win the Quiz.

Interactivity is perceived when the student attempts

to solve the question by interacting with interactive

resources actively. The Immediacy is related to when

the results are published in real-time for all students,

inﬂuencing their expectations when they know their

positions in the ﬁnal scoreboard.

https://doi.org/10.6084/m9.ﬁgshare.28225790

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962

Table 3: Taxonomy concepts classiﬁcation results through tools.

Regarding the Participation Lens, we analyzed

Time, Qualities, and Motivation. The Quiz falls under

Immediate Time since results appear in real-time. In

Qualities, the Epistemic aspect emerges as students

reﬂect on their knowledge compared to peers, while

the Critical aspect depends on the quiz content, fos-

tering deeper thinking. For Motivation, we classiﬁed

it as Competitive since scores drive students to reach

top positions.

Under the Liveness Lens, we examined Flow and

Presence. Students may experience Flow by focus-

ing intensely on answering questions within the time

limit. Presence includes Social Presence, as students

see peers’ participation and results, and Co-Presence,

the Quiz fosters a shared space between students and

the professor.

From the other technologies’ perspective, such as

Google Meet, the changes in the virtual background

and visual effects could change the way the students

see other students in the class; the immersion occur-

rence can be inﬂuenced by the background changes of

all the participants who participate and have the cam-

era on. In this way, providing a sense of connection

between the students who use this resource.

5.1 STARS

To aid teachers in choosing which technology to use

in class, we developed STARS, a technology recom-

mendation system to facilitate the selection of solu-

tions tailored to the student experience. STARS rec-

ommends technologies based on the results presented

in Section 5.

The recommendation process operates in two

ways. The ﬁrst process involves a series of

seven questions structured according to the Gomes

et al. (2023) Taxonomy. Each question has a pre-

determined option based on taxonomy concepts. Each

answer aligns with one or more of these concepts, and

the recommendation is determined by the frequency

of answers that align with speciﬁc tools. In other

words, STARS suggestion will be the one with the

highest number of matches based on the provided re-

sponses. All the questions used to recommend can

be seen in the supplementary material

. Figure 1

presents the process through the question of reaching

the recommendation.

Figure 1: STARS question screens process (In Portuguese).

The second process is designed to offer a more

practical option for teachers already familiar with the

system and its concepts. In this process, the recom-

mendation is made through direct concept selection,

with the system displaying relevant tools in real-time

when a concept is chosen. As teachers combine dif-

ferent concepts, the system generates compatible op-

tions to identify the solution based on their selected

combination.

6 DISCUSSION

In this paper, we address the following question “How

can educational technologies be classiﬁed by the En-

gagement, Participation, and Liveness lens?”

We answer this question by analyzing interactive

features through Gomes et al. (2023)’s taxonomy and

https://doi.org/10.6084/m9.ﬁgshare.28225790

Understanding the Student Experience Better: Analyzing Remote Learning Tools Through Engagement, Participation, and Liveness

Concepts

963

proposing a tool to recommend interactive tools based

on concepts to enhance student experience in remote

teaching. We adopted this taxonomy as it covers key

concepts of audience engagement and participation,

considering that a class can be viewed as an educa-

tional event.

The interactive features classiﬁcation through the

taxonomy supports teachers in enhancing student en-

gagement and participation in remote contexts. For

example, teachers would decide which strategy to fol-

low based on how that interactive feature could inﬂu-

ence the student experience or what they want to in-

duce. Active student engagement would be perceived

by the use of features such as voting and chat (Tu-

laskar and Turunen, 2022). In the Epistemic concept,

the values of participation are tied to gaining a deeper

understanding of oneself and others present during the

performance (Cerratto-Pargman et al., 2014). In other

contexts, such as cooperative events, warm-up ques-

tions are used to let the audience know to ﬁnd out who

the people present are like by using interactive fea-

tures (Salovaara et al., 2021). The use of chat could

be a way to manifest information about the student or

the others who participate in the experience.

Our analysis suggests that interactive features can

promote various factors, such as competition and col-

laboration. For instance, Mentimeter’s Word Cloud

allows teachers to pose open questions, encouraging

students to share ideas in real time, fostering collab-

oration and inspiration. Meanwhile, the Quiz feature

can create a competitive environment, motivating stu-

dents to aim for top scores, especially when rewards

are involved. However, the impact depends on how

teachers utilize these tools. While educators already

use technology to boost engagement and participa-

tion, there is no structured approach to selecting tools

based on the engagement, participation, and liveness

lens.

In the literature, Ahshan (2021) developed a

framework that ensures active student engagement

during remote teaching. The authors investigate the

strategies using tools like Google Meet, Jamboard,

Google Chat, Breakout Room, Mentimeter, Moodle,

and electronic writing devices. However, the authors

do not consider how it impacts the student experience.

Different tools can affect student engagement and par-

ticipation in different ways. Our analysis highlights

these ways from different perspectives. Our analy-

sis can help researchers to study precisely these tools,

helping to explore how such tools can affect the stu-

dent experience. For example, Ahshan (2021) points

out that Google Meet chat is an option for online in-

teraction between students and professors. However,

it is not explored how these interactions can provide

different affective emotions and sentiments from ex-

perience. The analysis through the taxonomy could

be used as a lens to understand different kinds of audi-

ence experiences, as proposed by Gomes et al. (2023).

We propose a tool—STARS—to recommend interac-

tive features based on taxonomy concepts, explaining

how these interactive features could trigger the taxon-

omy concepts.

7 THREATS TO VALIDITY

Based on our analysis, there are threats and limits to

our results that need to be considered. To reach our

goals, we obtained a set of 15 tools used to promote

engagement in remote classes. Our results are lim-

ited by our selection of tools, which may be unrep-

resentative. However, the selected tools are diversi-

ﬁed by categories, each representing a group of tools

with similar characteristics. We classiﬁed these tools

based on a typology already known from the litera-

ture. We also classiﬁed the interactive features man-

ually, which may be subject to different interpreta-

tions. In this sense, we validated our analysis with

expert research through the Cohen Kappa, evaluating

the agreement of the concepts with the use of technol-

ogy in the educational context.

While our classiﬁcation is based on the re-

searchers’ expertise, no evaluation with students has

been conducted to validate the researchers’ percep-

tions regarding the classiﬁcation of interactive fea-

tures. However, evidence from the literature supports

integrating our analysis into the interactive features of

remote learning tools.

8 CONCLUSION

In this paper, we analyzed Google Meet, Mentime-

ter and Google presentations to understand how the

concepts of engagement, participation, and liveness

are incorporated into the interactive features of remote

learning tools to affect the student experience.

Our initial results highlight an approach to ana-

lyze interactive features using Gomes et al. (2023)

taxonomy and how it can stimulate emotional and be-

havioral reactions due to the use of such interactive

features. Gomes et al. (2023) taxonomy can support

observing the student experience through the use of

technologies.

In the future, we plan to integrate LLM with the

taxonomy and our technology dataset to recommend

tools, providing insights on their implementation and

CSEDU 2025 - 17th International Conference on Computer Supported Education

964

potential impact on student experience. Addition-

ally, we aim to conduct a UX evaluation and usability

test with STARS to identify key interface issues. Fi-

nally, we will carry out a study with teachers to assess

STARS’ effectiveness in recommending technologies

for remote learning.

ACKNOWLEDGEMENTS

The present work is the result of the Research

and Development (R&D) project 001/2020, signed

with Federal University of Amazonas and FAEPI,

Brazil, which has funding from Samsung, using re-

sources from the Informatics Law for the West-

ern Amazon (Federal Law nº 8.387/1991), and its

disclosure is in accordance with article 39 of De-

cree No. 10.521/2020. Also supported by FA-

PEAM/PDPG/CAPES, CAPES - Financing Code

001, CNPq process 314797/2023-8, CNPq process

443934/2023-1, CNPq process 445029/2024-2, and

Amazonas State Research Support Foundation - FA-

PEAM - through POSGRAD 24-25.

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Understanding the Student Experience Better: Analyzing Remote Learning Tools Through Engagement, Participation, and Liveness

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