A STUDY ON THE USAGE OF MOBILE DEVICES IN

COLLABORATIVE ENVIRONMENTS VS DESKTOPS

An Approach based on Flow Experience

Steven Abrantes

Institute Polytechnic of Viseu, Viseu, Portugal

Luis Borges Gouveia

Faculty of Science and Technology, University Fernando Pessoa, Porto, Portugal

Keywords: Flow experience, Mobile devices, Comparing mobile with desktop.

Abstract: In order to evaluate the use of mobile devices (laptops) and desktops and the potential of mobile devices in

collaborative environments vs desktops, it was performed an experiment involving one hundred and twelve

students of higher education. This study has the main objective to validate if the students that use laptops or

desktops are in the flow experience and which of them are more in the flow experience. This study is based

on the flow experience introduced by Csikszentmihalyi (1975). The main purpose of this study is to

establish whether the user is in the flow experience when using Google Groups when using laptops or

desktops. In the context of this study, information has been gathered through a survey, applying the five

dimensions of the flow state. The sample used consisted on one hundred and twelve students. At the end of

the study, after analyzing the gathered information, it was possible to conclude that students have

experienced the flow state and it had a positive effect on their learning experiences both by students using

laptops or desktops, but having the students that used the laptops a more positive effect in the flow

experience than the students that used desktops.

1 INTRODUCTION

Technological applications and the way they are

used has advanced in such a way that the

manipulation of learning objects is no longer limited

to a desktop, but extended to the use of mobile

devices (PDA, mobile phone, Smartphone, Laptops,

and Tablet PC) to provide a greater range of

application and obtain the benefits that mobile

computing offers in the education sector. This

results in the establishment of a new area of activity,

related with the use of mobile technologies in

learning, named m-learning.

This educational model based on the use of

mobile devices, has been developed over the past

few years, resulting in several research projects and

some commercial products. Current and past

promises of more learning outcomes are needed to

be evaluated.

2 M-LEARNING AND MOBILE

DEVICES

Quin cited by (Corbeil and Valdes-Corbei, 2007)

states that m-learning is the interaction of mobile

computing (small applications, portable, and

wireless communication devices) with e-learning

(learning facilitated and supported through

information and communication technologies).

We can see an widespread use of mobile devices

in our modern world: mobile phones, PDA’s, MP3

players, portable gaming devices, Tablet PCs and

laptops, which predominate in our everyday lives.

From children to older people, they are

increasingly linked with each other, communicating

through communication technologies, something

that didn’t happen a few years ago.

There are a number of mobile devices that can be

considered for an m-learning environment (Corbeil

and Valdes-Corbei, 2007): iPod , MP3 Players,

199

Abrantes S. and Borges Gouveia L. (2010).

A STUDY ON THE USAGE OF MOBILE DEVICES IN COLLABORATIVE ENVIRONMENTS VS DESKTOPS - An Approach based on Flow Experience.

In Proceedings of the International Conference on e-Business, pages 199-202

DOI: 10.5220/0002951801990202

 SciTePress

PDA, USB drive, E-Book Readers, Smart Phone,

Ultra-Mobile PC (UMPC) and Laptop/Tablet PC.

These mobile devices have some advantages and

disadvantages (Corbeil and Valdes-Corbeil, 2007).

One of the biggest advantages of mobile devices,

when compared with desktops, is its ubiquity. With

mobile devices people can connect to many kinds of

information where they want and whenever they

want.

3 THE FLOW EXPERIENCE

An aspect related with the interaction of the users

with collaborative environments has to do with the

flow experience introduced by Csikszentmihalyi

(1975). The flow experience means the sensation

that people feel when they are completely involved

in what they are doing, that is, people like the

experience and want repeat it (Csikszentmihalyi,

1982). This means that for students to be involved

with collaborative environments, it is necessary that

they presence the flow state.

The theory of the flow allows us to measure the

interaction of users with computer systems,

verifying if these are more or less playfulness

(Trevino and Webster, 1992).

The flow experience is used in this paper to

characterize the interaction between the human and

the new technologies (Trevino and Webster, 1992).

When one is in the presence of the flow experience,

this will bring to the users, a sense of pleasure of

what he is doing. This satisfaction will encourage

the user to repeat the task again (Webster et al.,

1993).

Csikszentmihalyi says that a person who is in the

presence of the flow state has the following

characteristics(Csikszentmihalyi,1975,

Csikszentmihalyi, 1990):

 Clear goals and immediate feedback;

 Equilibrium between the level of challenge

and personal skill;

 Merging of action and awareness;

 Focused concentration;

 Sense of potential control;

 Loss of self-consciousness;

 Time distortion;

 Autotelic or self-rewarding experience.

For a person to be in the presence of the flow

experience it is necessary a balance between the

level of challenge and personal skill

(Csikszentmihalyi, 1982) (Figure 1).

Figure 1: Flow Experience (Csikszentmihalyi, 1982).

The sensation of an excellent experience in the

accomplishment of any day by day task is our reason

of living. If we do not feel this excellent experience

with our everyday tasks, we will question our self, if

it is worth living (Csikszentmihalyi, 1982).

Previous researches have used the flow experience

to measure playfulness, involvement, satisfaction

and other states with the involvement in

computational environments (Chen et al., 2000,

Ghani and Deshpande, 1994, Novak and Hoffman,

1997, Novak et al., 2000, Trevino and Webster,

1992)

Trevino and Webster (1992) defines four

dimensions for the flow experience:

 Control;

 Attention Focus;

 Curiosity;

 Intrinsic Interest.

There is one more dimension, sense of time, that is

also important to measure the flow state (McKenna

and Lee, 2005) .

People who interact with computers, with an

entertainment spirit, transmit a much more positive

experience, of those, who are in the computer for

obligation (Webster et al., 1993).

4 THE STUDY

To evaluate the flow experience and to verify its

occurrence in collaborative tools, an experience was

carried through involving one hundred and twelve

students from a university school. The main tool

used was Google Groups, for this experience. This

paper presents the carried through experience, the

data obtained, as well as the statistical procedures

applied.

After the accomplishment of the project given by

the teacher, in which they used Google Groups, the

students answered the questions of a survey.

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200

The survey was passed through the Internet with

the help of "LimeSurvey”. The data collection was

performed in the first week of November of 2009.

The Instruments used were Google Groups,

Google Docs and Facebook and a survey consisting

on some questions, in order to verify, in the end of

the study, if the students were in the presence of the

flow state. This survey will use the four dimensions:

control, attention focus, curiosity and the intrinsic

interest (Webster et al., 1993), as well as the

dimension sense of time (McKenna and Lee, 2005).

Beside these questions, this survey also contains

other generic questions. All the related questions

from this survey were built on a Likert scale of five

points, since one (I totally disagree) up to five (I

totally agree). Two questions for each dimension

were elaborated.

4.1 Analysis

This study was composed of 78.57% males and

84,82% had ages between sixteen and twenty four

years. Most of the students have already used

discussion forums in a fairly way.

The majority of the respondents used the laptop

(72.32%) to access the tools of the project, followed

by the desktop (27,68%).

We verified that Cronbach’s alpha is always

superior to 0.7, being able to conclude that the data

is related to one same dimension, that is, the

questions of the survey for the use of Google

Groups, allowed us to determine if the individual

finds himself in the presence of the flow experience,

for students using a laptop or a desktop.

To determine how the variables are correlated with

each of the different devices used (laptop and

desktop), a correlation matrix was created for both

types of the devices, where the correlation

coefficient, R, is presented, that is a measure of the

linear association between two variables. We can

conclude from the correlation analysis that the

correlation between the variables, for laptops, has a

greater number of variables positively correlated

than the desktop.

After the studies mentioned previously, we used

the factor analysis in order to reduce the number of

variables, both for laptops and desktops.

The extraction of the factors is given by considering

the percentage of variance explained by the factors

(Table 1 and Table2).

Table 1: Number of factors to be retained (laptop).

laptop

Component

Initial Eigenvalues

Total

% of

Variance

Cumulative

1 2,371 47,422 47,422

2 ,881 17,625 65,047

3 ,707 14,136 79,184

4 ,631 12,613 91,797

5 ,410 8,203 100,000

Table 2: Number of factors to be retained (desktop).

desktop

Component

Initial Eigenvalues

Total

% of

Variance

Cumulative

1 2,374 47,475 47,475

2 1,053 21,053 68,528

3 ,704 14,077 82,604

4 ,565 11,301 93,905

5 ,305 6,095 100,000

To set the number of components to be retained,

we choose, by default, those that have eigenvalues

greater than one. If the total variance explained by

the factors retained is less than 60%, then, at least,

one more factor should always be selected. Thus, for

this case study, two factors were retained in each

type of device. For the laptop, it appears that the first

factor explains 47.422% of the total variation and

the second 17.625%, both explaining 65.047% of the

total variation that exists in the five original

variables. For the desktop, the first factor explains

47.475% and the second 21.053%, explaining both,

68.528% of the total variation.

The matrix of components after rotation

(Varimax method) aims to exaggerate the value of

the coefficients that relates each variable to the

factors retained, so that each variable can be

associated with only one factor. The higher the value

of the coefficient that relates one variable to a

component, the greater is the relationship between

them. From this study we have concluded the

following for the case of the laptops: Factor group 1:

(Intrinsic Interest, Control and Curiosity); Factor

group 2: (Attention Focus and Sense of time)

And for the case of the desktops:

Factor group 1: (Attention Focus, Sense of time,

Intrinsic Interest and Curiosity) Factor group 2:

(Control).

A STUDY ON THE USAGE OF MOBILE DEVICES IN COLLABORATIVE ENVIRONMENTS VS DESKTOPS - An

Approach based on Flow Experience

201

5 CONCLUSIONS

In order to evaluate the use of mobile devices and

desktops and the potential of mobile devices in

collaborative environments versus desktops, it was

performed an experiment involving students of

higher education. This study has the main objective

to validate if the students that use laptops (mobile

device) or desktops are in the flow experience and

which of them are more in the flow experience.

The analysis of data allows us to conclude that the

majority of the students were males, had ages

between sixteen and twenty four years and that most

of the students have already used discussion forums.

When going further to the analysis of the data, we

verified that the variables described all the same

characteristic (threw the determination of the

Cronbhach’s alpha), that is, the variables describe

the flow experience.

We can conclude from the correlation analysis that

the correlation between the variables, for laptops,

has a greater number of variables positively

correlated than the desktop.

From the factor analysis it was possible to isolate

two factors that explain the majority of the total

variation. Such factors had been Factor group 1:

(Intrinsic Interest, Control and Curiosity), Factor

group 2: (Attention Focus and Sense of time) for the

laptops and Factor group 1: (Attention Focus, Sense

of time, Intrinsic Interest and Curiosity) Factor

group 2: (Control) for the desktops.

In order to determine the presence of the flow

experience for each type of device, it was verified

that, on average, the students were above value three

(Likert scale of five points), that is, the majority of

the students, in each of the different devices (laptop

and desktop) used, are in the presence of the flow

experience, for the five variables mentioned for this

study (attention focus, curiosity, control, intrinsic

interest and sense of time). We can also see, that the

average of the five variables associated with the

flow experience, for students who used the laptops,

were greater than those using the desktop to access

the tools of the project development.

From this study we can conclude that the flow

experience exists for people that use Google Groups,

both for people that used the laptop or even the

desktop, but having a more positively effect for

users of the laptop. Considering that people use

mobile device for m-learning and desktops for e-

learning, we can conclude that people that use m-

learning have a more positive effect on learning than

the people that use e-learning.

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