Cloud-based Learning Environments: Investigating Learning
Activities Experiences from Motivation, Usability and Emotional
Perspective
Rocael Hernández Rizzardini
1
, Hector Amado-Salvatierra
1
and Christian Guetl
2,3
1
GES department, Galileo University, Guatemala, Guatemala
2
IICM, TU-Graz, Graz, Austria
3
Curtin Business School, Curtin University, Perth, Australia
Keywords: Cloud-based Learning Environments, Cloud-based Tools, e-Learning, Evaluation, Usability, Accessibility.
Abstract: Cloud education environments consider all the cloud services, such as Web 2.0 applications, content, or
infrastructure services. These services form an e-learning ecosystem which can be built upon the learning
objectives and the preferences of the learner group. A great variety of existing cloud services might be re-
purposed for educational activities and it can be taken advantage from already widely used services without
steep learning curves on their adoption. In this article is presented the design, deployment and evaluation of
learning activities using cloud applications and services. The experiences presented here are from Galileo
University in Guatemala with students from three different countries in Central America and Spain. This
study reports findings from motivational attitudes, emotional aspects and usability perception. Selected
cloud-based tools were used for the different learning activities in three courses in various application
domains. These activities include collaboration, knowledge representation, storytelling activities and social
networking. Experimentation results obtained aim to demonstrate that students are eager to use and have
new and more interactive ways of learning, which challenges their creativity and group organization skills,
while professors have a growing interest on using new tools and resources that are easy to use, mix and
reuse. Thus, future research should focus on incentives for motivating participation as well as on providing
systems with high usability, accessibility and interoperability that are capable of doing learning
orchestration.
1 INTRODUCTION
Trends for modern Virtual Learning Environments
(VLE) indicate a movement from a monolithic
paradigm to a distributed paradigm. Dagger et. al.
(2007) and Chao-Chunk and Skwu-Ching (2011)
call it the next generation of e-Learning
environments. It is clear that Virtual Learning
Environments need to be more scalable and improve
the real innovation they bring to education through
flexibility, due the increasing requirements that
higher institutions have. Actual work in Cloud
Computing has a focus on infrastructure layer rather
than application layer as shown in the work of Al-
Zoube et. al. (2010) and Chandran and Kempegowda
(2010). Still VLE is in many cases a simple
conversion of classroom-based content to an
electronic format, retaining its traditional
knowledge-centric structure as stated by Teo et. al.
(2006).
There is great potential in the use of multiple
cloud-based tools for learning activities and to create
a different learning environment, with new diversity
of tools driving to possibly enrich learning
experiences. There is a quest to create a Cloud
Education Environment, where a vast amount of
possible tools and services can be used, connected
and in the future orchestrated for learning and
teaching (Mikroyannidis, 2012).
Cloud computing application technologies are a
major technological trend that is shifting business
models and application paradigms; the cloud can
provide on-demand services through applications
served over the Internet for multiple set of devices in
a dynamic and very scalable environment (Sedayao,
2008). Thus, the significance of the technology for
709
Hernández Rizzardini R., Amado-Salvatierra H. and Guetl C. (2013).
Cloud-based Learning Environments: Investigating Learning Activities Experiences from Motivation, Usability and Emotional Perspective.
In Proceedings of the 5th International Conference on Computer Supported Education, pages 709-716
DOI: 10.5220/0004451807090716
Copyright
c
SciTePress
this study lies not only in cloud computing, but in
the application that reside in the cloud that can be
used for learning purposes, although as it will be
presented, many of them have not been intended for
learning in the first place, the applications presented
in this experience are actually used for learning.
Cloud-based tools have the potential to interoperate
with other systems; therefore it is possible to
systematically orchestrate a learning activity through
multiple cloud-based tools. The cloud-based tools
are normally seen as traditional and standalone web
2.0 tools, but now it can create integrated learning
experiences. This paper does not focus on the cloud-
computing infrastructure but rather on the findings
of using the existing cloud-based tools for learning.
Likewise social networking technologies provide
easy pathways for sharing these kinds of cloud
applications, related data, activities and for
socializing while at the same time enhancing the
collaborative experiences (Mazman and Kocak,
2010).
This paper is organized as follows: first we will
describe the test-beds used for this experience, the
learning activities designed and the learning
scenarios. Thereafter we will give a detailed
description of the instruments used, the methodology
description and results of our study, in which
students were asked to perform learning activities
individually and in groups using different type of
Cloud-based tools. Finally we will discuss our
findings, conclusions and some ideas of future
research.
2 THE EXPERIMENT
2.1 The Galileo University Test-bed
In this section we present a cloud-based learning
experience in Latin-American countries following
other successful learning experiences by Dagger et
al. (2007) and Chao-Chunk and Skwu-Ching (2011).
The learning experience happens in the Institute Von
Neumann (IVN) of Galileo University, Guatemala.
IVN is an online higher education institute. It
delivers online educational programs across the
country and those programs are open for other
countries.
The student population at IVN is mostly part-
time students; this is something quite common in the
entire University students. The courses are similar to
any other University course; most of the students do
their learning during the evening or in weekends
because of work.
It is a complete online learning degree, the topic
of the course is an e-Learning certification that
consists in several modules that specializes the
students into e-Learning from an instructional design
reference. The course does not have formal
synchronous sessions, although the use of chat with
professor and other peers is possible. Also the
students are expected to work 10 hours/week on
their studies, learning activities and collaborative
activities. The courses within the e-Learning
certification are designed in learning units that
usually last for 1 week each unit having a diversity
of online material such as video, audio, animations,
interactive content, forums, assignments and a wide
diversity of learning activities specially designed for
enhancing learning acquisition. The course uses the
institutional LMS that currently is .LRN LMS
(www.dotlrn.org), although some module are
alternative provided in Moodle LMS
(www.moodle.org). The students have the advice
and help from professional instructional designers to
build their online course. The Certification is
targeted to university professors, e-Learning
consultants, instructors that want to enhance their
knowledge about teaching with technology.
The presented learning experience has two
groups of more than 60 students, most of them
university professors, from different countries:
Guatemala, Honduras, El Salvador and Spain. The
courses titles are: course 2: Introduction to e-
Learning; course 3: e-Moderation and course 4:
Online activities design.
The first group (A) with 36 students from
Guatemala and Spain was evaluated with activities
prepared within courses 2 and 3. The second group
(B) with 30 students with students from universities
in Guatemala, Honduras and El Salvador was
evaluated with activities prepared within courses 3
and 4, thus the course 3: “e-Moderation” as common
course for all groups is used for comparative
analysis.
In this experience, students were assigned to
cloud-based learning activities for the first time,
most of them were not very familiar with related
technologies, but they had a preliminary course that
introduced them into the use of the institutional
LMS and related technologies.
The course professor introduced the cloud-based
learning activities as innovative and powerful tools
for learning, with the objective to elaborate all the
CSEDU2013-5thInternationalConferenceonComputerSupportedEducation
710
benefits that can create mind-set change, guiding the
students through the benefits that these type of
activities will have in their learning process (Chao-
Chun and Shwu-Ching 2011), something that proved
to be very helpful to avoid resistance and possible
fear to new and seen as complex tools. We collected
information form students in a pre-test and post-test
through an online survey from an exploratory
approach. Each group did two four-week courses,
between the courses there was a one-week off that
we used to do telephone interviews and gather
further information about the experience.
2.2 Learning Activities and Scenarios
We designed learning activities based on
instructional objectives, using as a base the past
standard non-cloud-based activities from previous
editions of the courses, and transforming them to
leverage the potential of the cloud ecosystem. The
designed and tested activities are presented, it is
important to mention that each activity was carefully
designed using a custom made instructional design
template that contains all activity related information
such as: learning objectives, instructions,
classification using Bloom’s revised taxonomy
(Anderson and Krathwohl 2001) and grading. Each
single step on the activity has a clear and explicit
grading. With a clear design of the activity, the
professor and instructional designer proceed to
select the most suitable tool based on previous
knowledge and experience with the tool, in the
presented experience most of the proposed tool has
been already used for other learning activities in
other courses, the three courses were:
Course 2 “Introduction to e-Learning”, had the
following learning activities:
Activity 2.1: Students had to do a research of a
given topic, and then write collaboratively an essay
in groups of four students each. This activity was
prepared with a control group setting for
comparison, where we divided the whole group
(A) of students in three segments with nine groups
(three groups per segment), first two segments
using cloud-based learning activities and the third
one using traditional desktop applications. The
first two segments were asked to use cloud
services: Google Docs (Google Docs-Page 2012)
and Wiki Spaces (Wiki Spaces-Page 2012) and the
other segment of three groups used traditional
word processor. Then students were invited to
represent the information with a time-line tool, the
cloud-based time-line tools used were Dipity
(Dipity-Page 2012) and Timetoast (Figure 2)
(Timetoast-Page 2012) and the traditional tool was
Power Point for segment three. Finally students
had to comment and discuss other groups’ results
in the LMS online discussion forums. A summary
of the tools used by groups are presented in Table
1.
Activity 2.2: Students (individually) had to do a
research and present knowledge gained through
mind map tools, the cloud application for this
activity was MindMeister (MindMeister-Page
2012) and Cacoo (Cacoo-Page 2012) (Figure 2).
Finally they were invited to discuss about other
peer contributions on the LMS discussion forum.
A comparison setting is presented in Table 2.
Table 1: Comparison setting for Activity 2.1.
Segment
Tools used for the learning
activity
1 (3 groups) Google Docs and Dipity
2 (3 groups) Wiki Spaces and Timetoast
3 (3 groups) Word Processor and PowerPoint
Table 2: Comparison setting for Activity 2.2.
No. of Students
Tools used for the learning activity
10 Cacoo
10 Mindmeister
16 PowerPoint
Figure 1: Screenshot of Timetoast time-line example.
Figure 2: Screenshot of Cacoo mind map example.
Cloud-basedLearningEnvironments:InvestigatingLearningActivitiesExperiencesfromMotivation,Usabilityand
EmotionalPerspective
711
Course 3: “e-Moderation”, had the following
activities:
Activity 3.1: Students had to synthesize
information learned in the course and publish it
using the cloud-tool Issuu (Issuu-Page 2012). Then
discuss on LMS forums.
Activity 3.2: Students had to do a research, create a
storytelling script and present it using one of the
following cloud-based tools: GoAnimate
(GoAnimate-Page 2012) (Figure 3), Xtranormal
(Xtranormal-Page 2012), Pixton (Pixton-Page
2012). Publish it in the social network Facebook
and comment other peers’ contributions.
Course 4: “Online activities design”, had the
following learning activities:
Activity 4.1: the group (B) of students had to build
collaboratively bookmarks based on a research
assignment using a base taxonomy provided by the
professor to classify the links provided by the
students. The Delicious bookmarking site
(Delicious-Page 2012) was used for the activity.
Activity 4.2: Students had to create online
satisfaction survey for courses, synthesize a
method and requirements for these types of
surveys using a mind-mapping tool and publish a
sample survey using Google forms (Google Docs-
Page 2012).
Activity 4.3: The learning activity focused on
modelling a process for creating visually attractive
digital posters with educational intentions, first by
using a mind-mapping to elaborate the concepts,
and then reflect them in an cloud-based tool called
Gloster (Gloster-Page 2012). In all activities,
students were required to learn about the tool in
order to perform their assignments.
Figure 3: Screenshot of Go-Animate storytelling example.
2.3 Research Methodology
We used standardized instruments by Fishbein and
Ajzen (1975) and Davis (1989) to measure this
experience; we also use the System Usability Scale
SUS by Brooke (1996) and the Computer Emotions
Scale (CES by Kay & Loverock, 2008). Through
online tests sent to the students with a pre-test and
post-test it were measured emotional aspects,
usability perception and performance, opinions and
motivation about the tools and cloud-based learning
activities. Pre and post-test were evaluated with
instructional designers, professors and students, to
observe and verify its validity for students; some
enhancements were introduced after a first review.
The initial test included a section of learning
preferences and previous online learning
experiences, a survey about the cloud-based tools
that were to be used for the experience and their
personal perceptions, then a motivation section and
finally an emotional aspects gathering section. The
post-test included personal evaluation of learning
effort using the cloud-based tools for the assigned
activities, personal opinions of the experience,
motivational aspects, usability and emotional
aspects, and open questions about the experience.
Since each class of students did two courses, the pre-
test was done before starting the first course, then
between first and second course, an random
telephone interview was conducted, and finally after
finishing the second course the post-test was sent to
students.
The CES instrument developed to measure emotions
related to learning new computer software, by Kay
and Loverock (2008), was quite instrumental for this
study and includes the following emotions: satisfied,
anxious, irritable, excited, dispirited, helpless,
frustrated, curious, nervous, disheartened, angry and
insecure. The questions were like “When I used the
cloud-based tool (and the names of the tools were
used) during the learning activity assignment (and
each of the assignment’s name were cited), I felt ...”
Answers used a four point Likert scale from (1) none
of the time to (4) All of the time.
The System Usability Scale (SUS) instrument by
Brooke (1996) contains 10 items regarding the
usability of cloud-based tools used for learning
activities. the answers were given on the 5-point
Likert scale, so that students could state their level
of agreement or disagreement. High mean values
indicate positive attitudes and tool evaluations.
The 10 items that composed the SUS questions
are:
1. I would use this tool regularly
2. I found it unnecessarily complex
CSEDU2013-5thInternationalConferenceonComputerSupportedEducation
712
3. It was easy to use
4. I would need help to use it
5. The various part of the tool worked well together
6. Too much inconsistency
7. I think others would find it easy to use
8. I found it very cumbersome to use
9. I felt very confident using the tool
10. I needed to understand how it worked in order to
get going.
According to Brooke (1996), SUS has proved to
be a valuable and reliable evaluation tool. It
correlates well with other subjective measures of
usability (eg. the general usability subscale of the
SUMI Software Usability Measurement Inventory).
Some of the main standards related to the
accessibility that can be applied in cloud-based
learning environments are presented in Amado et. al.
(2012). It is important to notice that tools and
learning activities prepared with cloud-based
learning environments should follow international
standards (e.g. W3C WCAG2.0, W3C WAI-ARIA)
to allow accessibility and usability to all the
students, including people with disabilities. The
research methodology includes the evaluation of
accessibility issues related to the cloud-based
learning activities.
Finally, telephone interviews were done with
some students and professors randomly selected and
only the ones that gave consent to participate on it.
Interviewers were instructed to ask about personal
opinions regarding the cloud-based tools and the
related learning activities, the conversations were
audio recorded and transcripts were written.
Using these instruments, the study is presented as
an exploratory approach with the aim to demonstrate
that students are eager to use and have new and
more interactive ways of learning.
3 RESULTS AND DISCUSSION
OF THE EXPERIENCE
From a total of 66 students from both groups, 45 of
the students gave their consent to participate in the
study by filling out at least one out of the two
presented questionnaires. Participation were equally
distributed with 48% of female and 52% of male
participants, (age average M=37, σ=14).
Participants were asked in the post-test and
telephone interviews about the experience. Some of
the more interesting positive and negative
impressions are presented with the emotional aspects
evaluation:
Positive impressions:
“I liked to know new activities and tools in the
web for more interaction with the student”
“I learned about many great tools that will help me
with my teaching activities, the experience showed
me that the activities can be very interactive and
innovative”
“The use of new tools for learning was fun and can
be applied with creativity to teach scientific
content.”
“What I liked is that I started using the tools in my
current courses.”
“I liked that the activities awaken creativity and
obtained interesting results and products.”
“The activities promote meaningful learning,
learning by doing so you will not forget, allows
flexibility in learning and I feel very satisfying to
achieve something new and different.”
“The tools used for the activities are pretty
dynamic and will make courses more interactive.”
Negative impressions:
“I needed more time to get to know the tools and
how to use it
“The work load was increased for activities within
the new tools with an overhead with learning the
tools”
“I needed a lot of more time to achieve the results
with tools like Gloster, and I felt frustrated”
“The instructions were not clear”
“With some of the tools you need to purchase a
membership to upgrade and enable some
functionality”
“Some of the tools are not accessible and you can’t
use it in all operating systems, e.g. Flash based
tools”
Some of the main results of the post-test were:
95% of the participants liked the idea to use
innovative learning online tools to represent new
knowledge.
35% of the participants think that it was difficult to
complete the learning activities
50% of the participants think that they would need
more information and instructions to complete the
learning activities.
Only 10% of the participants expressed the
learning activities were boring.
70% of the participants considered that the time for
the activity was appropriate.
80% of the participants were positive about the
Cloud-basedLearningEnvironments:InvestigatingLearningActivitiesExperiencesfromMotivation,Usabilityand
EmotionalPerspective
713
expression that sharing results within groups
and comments about other participants helps to
learn new concepts related to the activity.
The learning experience presents the impressions
from participants, which indicates evidence of the
interest in learning activities highlighting the
interaction, innovation, flexibility and creativity,
capabilities that these cloud-based tools seem to
easily enable for the participants. The results
obtained appear to demonstrate that students are
eager to use and have new and more interactive
ways of learning, which challenges their creativity
and group organization skills.
The following subsections will present related
results from an Emotional, Motivation and Usability
perspective.
3.1 Emotional Aspects
From an emotional aspect perspective, the
instrument was based on the Computer Emotion
Scale (4pt. scale) developed by Kay and Loverock
(2008) to measure emotions related to learning new
computer software/learning tools in general, then the
post-test measured the emotions after using the tool
proposed for the learning activities with the
comparison in Table 3.
Research by Kay and Loverock (2008) in CES
showed 12 items describing four emotions:
Happiness (When I used the tool, I felt
satisfied/excited/curious.?);
Sadness (When I used the tool, I felt
disheartened/dispirited.?);
Anxiety (When I used the tool, I felt
anxious/insecure/helpless/nervous.?);
Anger (When I used the tool, I felt
irritable/frustrated/angry.?).
The summary with the four variables of the CES
scale for groups A and B is presented in Table 4.
The evaluation of emotional aspects from the
participants shows little difference in the results
between pre-test and post-test measures. In this
sense cloud-learning activities and instructor’s
motivation should focus on improve results looking
for students with high level of emotions related to
Happiness (e.g. satisfied, excited) and reduce
emotions related to Anger or Anxiety (e.g.
frustrated, helpless). Results with a 4pt. scale show a
positive reaction to “Happiness” and levels of
“Sadness”, “Anxiety” and “Anger” to improve while
working with cloud-based tools used for learning
activities.
Table 3: Computer Emotional Scale Comparison.
Emotion Pre-test results Post-test results
Satisfied 2.50 (σ = 0.65) 2.48 (σ = 0.65)
Anxious 1.42 (σ = 0.97) 1.24 (σ = 0.78)
Irritable 0.28 (σ = 0.45) 0.44 (σ = 0.51)
Excited 2.33 (σ = 0.72) 2.16 (σ = 0.85)
Dispirited 0.31 (σ = 0.47) 0.28 (σ = 0.46)
Helpless 0.47 (σ = 0.56) 0.52 (σ = 0.65)
Frustrated 0.39 (σ = 0.55) 0.32 (σ = 0.56)
Curious 2.33 (σ = 0.68) 2.12 (σ = 0.83)
Nervous 0.47 (σ = 0.56) 0.60 (σ = 0.65)
Disheartened 0.32 (σ = 0.42) 0.35 (σ = 0.46)
Angry 0.19 (σ = 0.40) 0.32 (σ = 0.48)
Insecure 0.47 (σ = 0.70) 0.40 (σ = 0.58)
Table 4: Summary CES-Scale Comparison.
Emotion
(4pt. scale)
Pre-test
results
Post-test
results
Reliability
Happiness 2.39 2.25 r = 0.75
Sadness 0.30 0.28 r = 0.57
Anxiety 0.71 0.69 r = 0.71
Anger 0.29 0.36 r = 0.78
3.2 Motivational Aspects
Deci et. al. (1991) promotes self-determination and
motivation that leads to the types of learning
outcomes that are beneficial to the student.
According to Deci et. al. (1991), intrinsically
motivated students engage in the learning process
without the necessity of reward or constraints.
Extrinsic motivation, on the other hand, provides
student with engagement in the learning process as a
means to an end, such as feedback or a grade. For
this study and adapted scale based on the work of
Tseng and Tsai (2010) was used. The scale by Tseng
and Tsai (2010) is used to measure motivations in
online peer assessment learning environments. For
this study, the instrument measures general attitudes
with two subscales for extrinsic and intrinsic
motivation. Intrinsic motivation is composed of
seven items and extrinsic motivation is composed of
four items. A single result is composed for each
subscale from the participant answers. Results from
the instrument and comparison between the two
groups (A, B) using course 3 (e-Moderation), are
presented in Tables 5 & 6. Results show a positive
measure of individual intrinsic motivation and a
regular measure of extrinsic motivation from the
point of view of the student related to the perceived
motivation from peers.
CSEDU2013-5thInternationalConferenceonComputerSupportedEducation
714
Table 5: Summary from intrinsic motivation for both
groups, means and t-Test results.
Group M Σ F T Df
A 76.87 14.43 0.43 -1.58 43
B 84.16 16.13
Table 6: Summary from extrinsic motivation for both
groups, means and t-Test results.
Group M Σ F T Df
A 64.97 17.43 0.33 -1.82 42
B 74.97 18.93
The comparison of Table 5&6, shows an interesting
higher value for intrinsic compared with extrinsic
motivation when being part of cloud based learning
activities.
3.3 Usability Aspects
Students were asked about SUS instrument items
regarding usability, in general within the tools used
(GoAnimate, Dipity, Timetoast, Gloster,
Mindmeister, Cacoo, etc.). Respondents were asked
to record their immediate response to each item.
Results from the instrument are presented in Table 7
& 8.
Table 7: Summary from SUS instrument for both groups
in the experience, reliability and Levene’s test results.
Group R F Sign
A 0.91 2.61 0.11
B 0.70
Table 8: Summary from SUS instrument for both groups,
means and T-Test results.
Group M Σ T df
A 65.50 19.51 -2.5 43
B 77.60 13.45
The results for the usability perception for all the
participants are summarized in Figure 4.
The SUS mean combined score for both groups
is 72.22. The minimum score is 27 (achieved only 1
time) the maximum score is 100. This is a
considerable result that denotes how easily the
students have interacted with the cloud-based tools
used for learning purpose. The objective of the use
of this instrument was to explore about the usability
of the proposed cloud-based tools with an acceptable
reliability and mean values with great opportunities
to be improved.
Figure. 4. SUS – Usability of cloud-based learning tools.
(Horizontal: participants that fill the instrument, Vertical:
Usability score for each participant, the Horizontal line is
the SUS mean combined score 72.22).
4 CONCLUSIONS
The results present a low emotional barrier on using
a Cloud-Education Environment, which corresponds
with the 95% of participants indicating that they like
the idea of using this environment. There are high
motivation results from the instruments used, and
the SUS scale indicates that from the student’s
perception the cloud-based tools are highly usable.
The results obtained from the motivational
perspective appear to demonstrate a high value of
intrinsic motivation for students while being part of
cloud-based learning activities: this result is an
important requirement to engage the student in the
learning process without the necessity of reward or
constraints.
Analysis from professor’s perspective suggest
that while doing and planning learning activities, the
professor have a growing interest on using new tools
and resources that are easy to use, mix and reuse.
The Cloud Education Environment has a
promising future and further experimentation is
necessary. Still there are many open areas, such as
providing integrated systems with high usability,
accessibility and interoperability with the aim to
create a Cloud Education Environment that can be
orchestrated by professors.
ACKNOWLEDGEMENTS
We are grateful with Universidad Galileo and GES
Department for their great support in conducting this
study. This work is supported partially by the
Cloud-basedLearningEnvironments:InvestigatingLearningActivitiesExperiencesfromMotivation,Usabilityand
EmotionalPerspective
715
European Commission through ALFA III – ESVI-
AL project “Educación Superior Virtual Inclusiva -
América Latina”.
REFERENCES
Al-Zoube M, et. al. (2010) “Cloud Computing Based E-
Learning System”, Int. J. of Distance Education
Technologies.Vol. 8, Issue 2, ISSN: 1539-3100
Amado-Salvatierra HR, Hernández R & Hilera JR (2012).
Implementation of accessibility standards in the
process of course design in virtual learning
environments. Procedia Computer Science 14, 363-
370
Anderson, L. W., & Krathwohl, D. R. (Eds.). (2001). A
taxonomy for learning, teaching and assessing: A
revision of Bloom's Taxonomy of educational
outcomes: Complete edition, New York : Longman
Brooke, J. (1996). SUS: A “quick and dirty” usability
scale. In Usability evaluation in industry. London:
Taylor & Francis.
Chao-Chun K and Shwu-Ching S. (2011), Explore the
Next Generation of Cloud-Based E-Learning
Environment, LNCS 2011, Volume 6872/2011, 107-
114
Chandran D and Kempegowda S. (2010) “Hybrid E-
Learning Platform based on Cloud Architecture
Model: A Proposal, Proceeding IEEE ICSIP 2010, pp
534-537
Dagger, D. et. al. (2007) Service-Oriented E-Learning
Platforms From Monolithic Systems to Flexible
Services. Internet Computing IEEE, Vol. 11, Iss. 3, pp.
28-35
Davis, F. D. (1989). Perceived usefulness, perceived ease
of use, and user acceptance of information technology.
MIS Quarterly, 13(3), 319-340.
Deci L, Vallerand R, Pelletier L, Ryan R. (19911
"Motivation and Education: The Self-Determination
Perspective" Educational Psychologist, 26(3&4), 325-
346. Lawrence.
Fishbein, M., & Ajzen, I. (1975). Belief, attitude, intention
and behavior: An introduction to theory and research.
Reading MA: Addison-Wesley.
Kay, R.H., & Loverock, S. (2008). Assessing emotions
related to learning new software: The computer
emotion scale. Computers in Human Behavior. 24,
1605-1623.
Mazman SG and Kocak Y (2010). Modeling educational
usage of Facebook, Computers & Education, Volume
55, Issue 2, Elsevier, P. 444-453
Mikroyannidis, A (2012) "A Semantic Framework for
Cloud Learning Environments," in Cloud Computing
for Teaching and Learning: Strategies for Design and
Implementation, L. Chao, Ed.: IGI Global, 2012.
Teo, C.B., Chang, S.C.A., Leng, R.G.K. (2006): Pedagogy
Considerations for E- learning, http://www.itdl.org/
Journal/May_06/article01.htm (retrieved March 10,
2012)
Tseng, S.-C., & Tsai, C.-C. (2010). Taiwan college
students‘ self-efficacy and motivation of learning in
online peer-assessment environments. Internet and
Higher Education, 13, 164-169.
Sedayao J. (2008), Implementing and Operating an
Internet Scale Distributed Application Service
Oriented Architecture Principles Cloud Computing
using and Infrastructure, iiWAS2008, Austria, pp.
417-421, 2008.
Google Docs-Page(2012). Tool available online:
docs.google.com [last visit 24-09-2012]
Wiki Spaces-Page(2012). Available online:
www.wikispaces.com [last visit 24-09-2012]
Dipity-Page(2012). Tool available online:
www.dipity.com [last visit 24-09-2012]
Timetoast-Page(2012). Tool available online:
www.timetoast.com [last visit 24-09-2012]
MindMeister-Page(2012). Available online:
www.mindmeister.com[last visit 24-09-2012]
Cacoo-Page(2012). Tool available online:
www.cacoo.com [last visit 24-09-2012]
Issuu-Page (2012). Tool available online: www.issuu.com
[last visit 24-09-2012]
GoAnimate-Page(2012). Tool online:
www.goanimate.com [last visit 24-09-2012]
Xtranormal-Page(2012). Tool online:
www.xtranormal.com [last visit 24-09-2012]
Pixton-Page(2012). Tool available online:
www.pixton.com [last visit 24-09-2012]
Delicious-Page(2012). Tool available online:
www.delicious.com [last visit 24-09-2012]
Gloster-Page(2012). Tool available online:
www.gloster.com [last visit 24-09-2012]
CSEDU2013-5thInternationalConferenceonComputerSupportedEducation
716