instructions 01A critical analysis is your reaction to th

instructions 01.docx
A critical analysis is your reaction to the information in an
article
and your evaluation of the manner in which the information is
presented in the article. 1) This critical analysis section of this
assignment should be four complete pages, typed, using APA
6th
edition format. 2) The title page is an additional page; and 3)
the
reference page is another additional page - A total of 6 pages
for
this assignment.
List the pointsarguments the author uses to support the thesis
or make his main points as the articles relate to your topic
Evaluate the authors’ presentation in each article. In other
words,
how well did the author makes his/her point or supports the
thesis of the
your paper
Continue analyzing your assignment by including areas listed
below.
• Criticize the facts or lack of facts, the organization, the tone,
the
author's credibility.
• Who wrote the articles? What do you know about the authors?
• Are the articles straight news reporting, a commentary on
some
event or situation, an editorial? Is it just the facts or a
discussion
of something that has happened?

• Do the authors appear objective? What kind of language does
the author use? Is it emotional?
• Are the facts correct, clear? Do they "seem" accurate. Is the
information complete? Does it appear that some important facts
are omitted?
• Do the writers appear to know the subject matter? As you read
the articles, do you "feel" that something is missing? Is it
logical?
Does it present support for his/her argument?
• Is there a clear thesis? Is it adequately supported with facts
and
data? Are inferences made?
• How is the material organized, for example:
A. Chronological order
B. Comparison/contrast
C. Definition
D. Cause/effect
E. Problem/solution
source 1.pdf
Future Trends in the Design Strategies
and Technological Affordances
of E-Learning
Begoña Gros and Francisco J. García-Peñalvo
Abstract
E-learning has become an increasingly important learning and
teaching mode in
recent decades and has been recognized as an efficient and
effective learning
method. The rapidly rising number of Internet users with
smartphones and tablets

around the world has supported the spread of e-learning, not
only in higher
education and vocational training but also in primary and
secondary schools.
E-learning and traditional distance education approaches share
the emphasis
on “any time, any place” learning and the assumption that
students are at a
distance from the instructor. The design of the initial e-learning
courses tended
to replicate existing distance education practice based on
content delivery. How-
ever, long textual lectures were clearly not suitable for the
online environment.
These early insights guided the development of e-learning
(technical and peda-
gogical) and emphasized the need for communication and
interaction.
B. Gros
Universidad de Barcelona, Barcelona, Spain
e-mail: [email protected]
F.J. García-Peñalvo
Universidad de Salamanca, Salamanca, Spain
e-mail: [email protected]
Gros, B., & García-Peñalvo, F. J. (2016). Future trends in the
design strategies and technological affordances of e-learning. In
M.
Spector, B. B. Lockee, & M. D. Childress (Eds.), Learning,
Design, and Technology. An International Compendium of
Theory, Research,
Practice, and Policy (pp. 1-23). Switzerland: Springer
International Publishing. doi:10.1007/978-3-319-17727-4_67-1

E-learning describes learning delivered fully online where
technology medi-
ates the learning process, teaching is delivered entirely via
Internet, and students
and instructors are not required to be available at the same time
and place.
E-learning practices are evolving with the mutual influence of
technological
e-learning platforms and pedagogical models. Today, the broad
penetration and
consolidation of e-learning needs to advance and open up to
support new
possibilities. Future e-learning should encompass the use of
Internet technologies
for both formal and informal learning by leveraging different
services and
applications.
The purpose of this chapter is to provide a general analysis of
the evolution
and future trends in e-learning. The authors intend to summarize
findings from
contemporary research into e-learning in order to understand its
current state and
to identify the main challenges in the technological and
pedagogical affordances
of e-learning.
Keywords
E-learning development • E-learning technology • E-learning
models • Learning
digital ecosystems
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mailto:[email protected]
Introduction
Advances in educational technology and an increasing interest
in the development of
asynchronous spaces influenced the rise of the term e-learning
in the mid-1990s as a
way to describe learning delivered entirely online where
technology mediates the
learning process. The pedagogical design and technology behind
e-learning have
gradually evolved to provide support and facilitate learning.
E-learning has become an increasingly important learning and
teaching mode, not
only in open and distance learning institutes but also in
conventional universities,
continuing education institutions and corporate training, and it
has recently spread to
primary and secondary schools. Moreover, greater access to
technological resources
is providing e-learning not only in formal education but also in
informal learning.
The evolution of e-learning has evolved from instructor-
centered (traditional
classroom) to student-centered approaches, where students have
more responsibility
for their learning. This evolution has been made possible due to
the technological

platforms that support e-learning. Learning management
systems (LMS) provide the
framework to handle all aspects of the e-learning process. An
LMS is the infrastruc-
ture that delivers and manages instructional content, identifies
and assesses individ-
ual and organizational learning or training goals, tracks
progress toward meeting
those goals, and collects and presents data to support the
learning process.
It is also important to stress the influence of social media on
users’ daily habits, as
this has led to increased demand for learning personalization,
social resources to
interact with peers, and unlimited access to resources and
information (Siemens,
2014). Moreover, e-learning is also being called on to offer
flexibility in the way and
place people learn and permit a natural and necessary
coexistence of both formal and
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informal learning flows. Thus, the “traditional” e-learning
platforms, despite their
extensive penetration and consolidation, need to evolve and
open themselves up to
supporting these new affordances to become another component
within a complex
digital ecosystem. This, in turn, will become much more than a

sum of its indepen-
dent technological components due to the interoperability and
evolution properties
orientated to learning and knowledge management, both at
institutional and personal
levels.
The continued growth and interest in e-learning have raised
many questions
related to learning design and technology to support
asynchronous learning: What
are the best instructional models in online settings? How have
the roles of instructors
and learners evolved? What are the most appropriate forms of
interaction and
communication? How can formal and informal learning be
combined? What is the
most appropriate technology to support e-learning? The main
goal of this chapter is
to describe the evolution of e-learning and to analyze the
current situation and future
trends in the design strategies and technological affordances of
e-learning.
The chapter is divided into four sections. Firstly, we describe
the meaning of the
term e-learning and its evolution from the early 1990s until
today. In the second part,
we focus on the evolution of pedagogical approaches in e-
learning. The third part
analyzes learning technologies with particular emphasis on the
development of the
learning ecosystem as a technological platform that can provide
better services than
traditional LMS. Finally, in the fourth part, based on the
resulting analysis, the

authors offer some general remarks about the future of e-
learning.
The Concept of E-Learning
In this section we analyze the meaning of the term e-learning in
relation to other
similar terminologies (distance education, online learning,
virtual learning, etc.) and
the evolution of e-learning generations from the early 1990s
until today.
Evolution of the Concept
A major confusion in the discourse on e-learning is its blurring
with distance
education: e-learning and distance education are not
synonymous. Distance educa-
tion can be traced back to ancient times, whereas e-learning is a
relatively new
phenomenon associated with the development of the Internet in
the 1990s. However,
it is undeniable that the origins of e-learning lie in distance
education and share the
idea that the use of media can support massive learning without
face-to-face
interaction.
The first documented example of training by correspondence (as
distance educa-
tion was known for many years) dates back to 1828, when
Professor C. Phillips
published an advertisement in the Boston Gazette offering
teaching materials and
tutorials by correspondence. In 1843, the Phonographic
Correspondence Society

was founded, which could be considered the first official
distance education
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institution as it would receive, correct, and return shorthand
exercises completed by
students following a correspondence course.
The idea that technology such as radio and television could be
used to bring
education to a wide audience began to surface as long ago as the
1920s, but it was not
until the early 1960s that the idea gained momentum, with the
landmark creation of
the Open University in the UK, with a manifesto commitment in
1966 that became a
reality in 1971 when this university started to accept its first
students.
The e-learning concept has evolved alongside the evolution of
its supporting
technology, from the early concept linked to the introduction of
personal computers
up to today’s distributed systems, which have favored learning
networks and the
roots of connectivism (Siemens, 2005). However, the most
outstanding and impor-
tant event in the history of e-learning is the emergence of the
Web, after which the
evolution of the e-learning model has been inextricably linked

to the evolution of the
Web (García-Peñalvo & Seoane-Pardo, 2015).
When a time approach is used to classify e-learning models
according to their
technological evolution, the most suitable metaphors are
generations (Downes,
2012; García-Peñalvo & Seoane-Pardo, 2015; Garrison &
Anderson, 2003; Gros
et al., 2009) or timelines (Conole, 2013), as opposed to other
taxonomies that use
variables such as centrality (Anderson, 2008) or the pedagogical
model (Anderson &
Dron, 2011).
Garrison and Anderson (2003) refer to five stages, or
generations, of e-learning,
each with its own theoretical model. The first is based on a
behaviorist approach; the
second appears as a result of the influence of new technologies
and an increasing
acceptance of the cognitive theory, including strategies focused
on independent
study; the third generation is based on constructivist theories
and centers on the
advantages of synchronous and asynchronous human
interaction; the fourth and fifth
generations have no theoretical background, and the authors
considered that their
main characteristics were not yet present in training programs,
but they would be
based on a huge volume of content and distributed computer
processing to achieve a
more flexible and intelligent learning model.
Gros et al. (2009) present three generations, each with a

different e-learning
model. The first generation is associated with a model focused
on materials, includ-
ing physical materials enriched with digital formats and clearly
influenced by the
book metaphor. The second generation is based on learning
management systems
(LMS) inspired by the classroom metaphor, in which huge
amounts of online
resources are produced to complement other educational
resources available on the
Internet known as learning objects (Morales, García-Peñalvo, &
Barrón, 2007;
Wiley, 2002). In this generation the interaction dynamics start
through messaging
systems and discussion forums. The third generation is
characterized by a model
centered on flexibility and participation; the online content is
more specialized and
combines materials created both by the institution and the
students. Reflection-
orientated tools, such as e-portfolios and blogs (Tan &
Loughlin, 2014), and more
interactive activities, such as games (Minović, García-Peñalvo,
& Kearney, 2016;
Sánchez i Peris, 2015), are also introduced to enrich the
learning experience with a
special orientation toward the learning communities model
(Wenger, 1998). In
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addition, web-based solutions are expanded to other devices
which leads to the
development of mobile learning training activities (Sánchez
Prieto, Olmos
Migueláñez, & García-Peñalvo, 2014).
Stephen Downes (2012) starts with a generation zero based on
the concept of
publishing multimedia online resources with the idea that
computers can present
content and activities in a sequence determined by the students’
choices and by the
results of online interactions, such as tests and quizzes. This
foundational basis is the
point of departure for all subsequent developments in the field
of online learning.
Generation one is based on the idea of the network itself, with
tools such as websites,
e-mail, or gopher to allow connection and virtual
communication through special-
ized software and hardware. Generation two takes place in the
early 1990s and is
essentially the application of computer games to online
learning. Generation three
places LMS at the center of e-learning, connecting the contents
of generation zero
with the generation one platform, the Web. Generation four is
promoted by the Web
2.0 concept, which in online education is known as e-learning
2.0 (Downes, 2005).
One of the most significant characteristics of e-learning 2.0 is
the social interaction
among learners, changing the nature of the underlying network
where the nodes are
now people instead of computers. This social orientati on also

causes a real prolifer-
ation of mobile access and the exploitation of more ubiquitous
approaches in
education and training (Casany, Alier, Mayol, Conde, & García-
Peñalvo, 2013).
Generation five is the cloud-computing generation (Subashini &
Kavitha, 2011) and
the open-content generation (García-Peñalvo, García de
Figuerola, & Merlo-Vega,
2010; McGreal, Kinuthia, & Marshall, 2013; Ramírez Montoya,
2015). Finally,
generation six is fully centered on Massive Open Online
Courses (MOOC) (Daniel,
Vázquez Cano, & Gisbert, 2015; SCOPEO, 2013).
Gráinne Conole (2013) presents a timeline to introduce the key
technological
developments in online education over the last 30 years (see
Fig. 1).
E-Learning Generations
Based on the generation metaphor presented above, García-
Peñalvo and Seoane-
Pardo (García-Peñalvo & Seoane-Pardo, 2015) reviewed the e-
learning conceptual-
ization and definition according to three different generations or
stages that are
consistent with the broad proposals of the different authors and
particularly with
Stephens Downes’ idea that generations are not replaced but
coexist, and the
maturity of the first brings the evolution of the following and
the emergence of
new generations (Downes, 2012). In fact, the term “e-learning”
have been used as a

teaching and learning method but also as a learning and
teaching approach.
The first generation is characterized by the emergence of online
learning plat-
forms or LMS as the evolution of a more generic concept of the
virtual learning
environments that were set up after the Web appeared, with the
broad (and poor) idea
that e-learning is a kind of teaching that uses computers (Mayer,
2003). These
learning environments are too centered on content and overlook
interaction. The
technological context is more important than the pedagogical
issues. The classic
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definitions of e-learning are generally associated with this e-
learning generation. For
example, Betty Collis (1996) defines tele-learning as “making
connections among
persons and resources through communication technologies for
learning-related
purposes.” Marc Rosenberg (2001) confines e-learning to the
Internet as the use of
Internet technologies to deliver a broad array of solutions that
enhance knowledge
and performance. He bases his idea on three fundamental
criteria: (1) networked,
(2) delivered to the end user via a computer using standard

Internet technology, and
(3) focused on the broadest view of learning. García-Peñalvo
(2005) defines
e-learning with a perspective focused on interaction, a
characteristic of the next
generation, “non-presential teaching through technology
platforms that provides
flexible access any time to the teaching and learning process,
adapting to each
student’s skills, needs and availability; it also ensures
collaborative learning envi-
ronments by using synchronous and asynchronous
communication tools, enhancing
in sum the competency-based management process.”
The second generation underlines the human factor. Interaction
between peers
and communication among teachers and students is the essential
elements for high-
quality e-learning that seeks to go beyond a simple content
publication process. Web
2.0, mobile technologies, and open knowledge movement are
significant factors that
help this e-learning generation to grow. Based on this, LMS
evolved to support
socialization, mobility, and data interoperability facilities
(Conde et al., 2014).
Examples of e-learning definitions that are congruent with these
second generation
principles include: “training delivered on a digital device such
as a smart phone or a
laptop computer that is designed to support individual learning
or organisational
performance goals” (R. C. Clark & Mayer, 2011) or “teaching-
to-learning process
aimed at obtaining a set of skills and competences from

students, trying to ensure the
Multimedia resources
The Web
Learning objects
Learning Management Systems
Mobile devices
Learning Design
Gaming technologies
Open Educational Resources
Social and participatory media
Virtual worlds
eBooks and smart devices
Massive Open Online Courses
Learning Analytics
80s
93
94
95

98
99
00
01
04
05
07
08
10
Fig. 1 The e-learning
timeline adapted from Conole,
2013
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highest quality in the whole process, thanks to: predominant use
of web-based
technologies; a set of sequenced and structured contents based
on pre-defined but
flexible strategies; interaction with the group of students and
tutors; appropriate
evaluation procedures, both of learning results and the whole

learning process; a
collaborative working environment with space-and-time
deferred presence; and
finally a sum of value-added technological services in order to
achieve maximum
interaction” (García-Peñalvo, 2008).
The third and last generation of e-learning is characterized by
two symbiotic
aspects. The first is technological: the LMS concept as a unique
and monolithic
component for online education functionality is broken (Conde-
González, García-
Peñalvo, Rodríguez-Conde, Alier, & García-Holgado, 2014).
Since the emergence
of Web 2.0 and social tools, the e-learning platform has become
another component
in a technological ecosystem orientated toward the learning
process (García-
Holgado & García-Peñalvo, 2013), transcending the mere
accumulation of trending
technology. This learning ecosystem should facilitate
interaction and offer greater
flexibility for any educational teaching.
The second aspect implies a loss of verticality in the e-learning
concept to become
a broader and more transverse element that is at the service of
education in its wider
sense. Both from an intentional (formal and informal) and
unintentional (informal)
view, learning ecosystems are at the service of people involved
in teaching and
learning processes or in self-learning. Thus, e-learning is
integrated into educational
designs or learning activities in a transparent way. It reveals the

penetration of
technology into people’s everyday lives, making it easier to
break down the barriers
between formal and informal learning (Griffiths & García-
Peñalvo, 2016).
Technological learning ecosystems facilitate this globalization
of the e-learning
notion, either to support an institutional context (García-
Holgado & García-
Peñalvo, 2014; García-Peñalvo, Johnson, Ribeiro Alves,
Minovic, & Conde-
González, 2014; Hirsch & Ng, 2011) or a personal one through
the concept, more
metaphorical than technological, of the personal learning
environment (PLE) (Wil-
son et al., 2007).
Nevertheless, technological learning ecosystems are supporting
other approaches
to using technology in the classrooms, such as flipped teaching
(Baker, 2000; Lage,
Platt, & Treglia, 2000). Flipped teaching methodology is based
on two key actions:
moving activities that are usually done in the classroom (such
as master lectures) to
the home and moving those that are usually done at home (e.g.,
homework) into the
classroom (García-Peñalvo, Fidalgo-Blanco, Sein-Echaluce
Lacleta, & Conde-
González, 2016). The Observatory of Education Innovation at
the Tecnológico de
Monterrey (2014) has also detected a tendency to integrate
inverted learning with
other approaches, for example, combining peer instruction
(Fulton, 2014), self-

paced learning according to objectives, adaptive learning (Lerís
López, Vea
Muniesa, & Velamazán Gimeno, 2015), and the use of leisure to
learn. Thus, the
flipped teaching model is based on the idea of increasing
interaction among students
and developing their responsibility for their own learning
(Bergmann & Sams, 2012)
using virtual learning environments as supported tools. These
virtual environments
allow students to access learning resources, ask questions, and
share material in
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forums, as it is mandatory for students to have help available
while studying at home
(Yoshida, 2016).
In this last stage, the MOOC concept has broken out strongly,
perhaps with no
new e-learning approach, but with sufficient impact to make
institutions reflect on
their e-learning processes and conceptions.
The term MOOC appeared for the first time in 2008 to describe
the connectivism
and connected knowledge course by George Siemens and others
(http://cckno8.
wordpress.com). This course gave rise to cMOOCs, where “c”
means that the course

is based on the connectivist approach (Siemens, 2005). A
second type of MOOC
appeared in 2011 under the name xMOOC, which is based on
digital content and
individualized learning as opposed to cMOOCs, which are more
related to collab-
orative learning. There is currently a great deal of interest in
MOOCs among the
e-learning community. Other proposals for improving MOOCs
have introduced the
use of associated learning communities (Alario-Hoyos et al.,
2013), adaptive capa-
bilities (Fidalgo-Blanco, García-Peñalvo, & Sein-Echaluce
Lacleta, 2013; Sein-
Echaluce Lacleta, Fidalgo-Blanco, García-Peñalvo, & Conde-
González, 2016;
Sonwalkar, 2013), and gamification capabilities (Borrás Gené,
Martínez-Nuñez, &
Fidalgo-Blanco, 2016).
However, the existing dichotomy between cMOOCs and
xMOOCs is questioned
by different authors due to its limitations. Thus, Lina Lane
(2012) proposes the
sMOOC (skill MOOC) as a third kind of MOOC based on tasks;
Stephen Downes
(2013) suggests four criteria to describe an MOOC’s nature,
autonomy, diversity,
openness, and interactivity; Donald Clark (2013) defines a
taxonomy with eight
types of MOOC, transferMOOC, madeMOOC, synchMOOC,
asynchMOOC,
adaptiveMOOC, groupMOOC, connectivistMOOC, and
miniMOOC; and finally
Conole (2013) provides 12 dimensions to classify MOOCs,
openness, massivity,

multimedia usage, communication density, collaboration degree,
learning path,
quality assurance, reflection degree, accreditation, formality,
autonomy, and
diversity.
With regard to the core elements that define this third
generation, García-Peñalvo
and Seoane-Pardo (2015, 5) propose a new definition of e-
learning as “an educa-
tional process, with an intentional or unintentional nature,
aimed at acquiring a range
of skills and abilities in a social context, which takes place in a
technological
ecosystem where different profiles of users interact sharing
contents, activities and
experiences; besides in formal learning situations it must be
tutored by teachers
whose activity contributes to ensuring the quality of all
involved factors.”
Pedagogical Approaches in E-Learning
In the previous section, we described the evolution of e-learning
and noted the
existence of different educational approaches over time. In this
section, we focus on
the evolution of e-learning, taking into account the pedagogical
approach.
Pedagogical approaches are derived from learning theories that
provide general
principles for designing specific instructional and learning
strategies. They are the
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http://cckno8.wordpress.com
http://cckno8.wordpress.com
mechanism to link theory with practice. Instructional strategies
are what instructors
or instructional designers create to facilitate student learning.
According to Dabbagh
(2005, p. 32), “there are three key components working
collectively to foster
meaningful learning and interaction: (1) pedagogical models;
(2) instructional and
learning strategies and, (3) pedagogical tools or online learning
technologies (i.e.,
Internet and Web-based technologies). These three components
form an iterative
relationship in which pedagogical models inform the design of
e-learning by leading
to the specification of instructional and learning strategies that
are subsequently
enabled or enacted through the use of learning technologies”
(see Fig. 2). Due to the
fact that learning technologies have become ubiquitous and new
technologies
continue to emerge bringing new affordances, pedagogical
practices are continu-
ously evolving and changing. This does not mean that some
designs and pedagogical
practices have disappeared. As we have mentioned, generations
of e-learning coex-
ist. For example, some instructive models based on the
transmission of knowledge

are still used but, sometimes, they incorporate new strategies
such as gamification.
Conole (2014) divided pedagogies of e-learning into four
categories:
1. Associative – a traditional form of education delivery.
Emphasis is on the
transmission of theoretical units of information learning as an
activity through
structured tasks, where the focus is on the individual, with
learning through
association and reinforcement.
2. Cognitive/constructivist – knowledge is seen as more
dynamic and expanding
rather than objective and static. The main tasks here are
processing and under-
standing information, making sense of the surrounding world.
Learning is often
task orientated.
Fig. 2 A theory-based design framework for e-learning (Source:
Dabbagh (2005, p. 32))
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3. Situative – learning is viewed as social practice and learning
through social
interaction in context. The learner has a clear responsibility for
his/her own

learning. This approach is therefore “learner centered.”
4. Connectivist – learning through a networked environment.
The connectivist
theory advocates a learning organization in which there is not a
body of knowl-
edge to be transferred from educator to learner and where
learning does not take
place in a single environment; instead, it is distributed across
the Web and
people’s engagement with it constitutes learning.
Each of these theories has a number of approaches associated
with it which
emphasize different types of learning (Fig. 3). For example, the
associative category
includes behaviorism and didactic approaches, the
cognitive/constructivist category
includes constructivism (building on prior knowledge) and
constructionism (learn-
ing by doing), etc.
The development of the first e-learning platforms supported an
instructional
design based on the associative/behaviorist approach. The
design process follows
a sequential and linear structure driven by predetermined goals,
and the learning
output is also predefined by the learning designer. The
designers organize the content
and tasks and break them down from simple to complex.
Information is then
delivered to the learner from the simplest to the most complex
depending on the
learner’s knowledge.

Constructivist
Building on prior
knowledge
Task-orientated
Associative
Focus on individual
Learning through
association and
reinforcement
Situative
Learning through
social interaction
Learning in context
Connectivist
Learning in a
networked
environment
Reflective & dialogical
learning,
Personalised learning
Inquiry learning
Resource-based
E-training
Drill & practice
Experiential,
problem-based,
role play
Fig. 3 The pedagogies of e-learning. Source:

teachertrainingmatters.com/blog-1/2015/12/19/learn
ing-theories-in-practice
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http://teachertrainingmatters.com/blog-1/2015/12/19/learning-
theories-in-practice
http://teachertrainingmatters.com/blog-1/2015/12/19/learning-
theories-in-practice
This type of approach has major limitations because it is not
really suited to the
needs of the learner. The evolution of technology allows the
development of
approaches that accommodate constructivist and connectivist
perspectives that
engage learners and give them more control over the learning
experience.
Choosing the pedagogical approach is obviously related to what
we want to
achieve. However, it is important to establish a clear difference
between designing
face to face or e-learning. Many of the studies into the
effectiveness of e-learning
(Noesgaard & Ørngreen, 2015) have employed a comparative
methodology. This
means that the effectiveness of e-learning is based on the
comparison between
traditional face-to-face teaching and online learning. Along
these lines, Noesgaard
and Ørngreen (2015, p 280) ask “should different modalities

have the same measures
of performance, or should we consider e-learning to be a unique
learning process and
thus use different definitions of effectiveness?” This question is
important because
the effectiveness of e-learning can be analyzed in different
ways. For instance, we
can design e-learning to improve learning retention, work
performance, or social
collaboration. The measure to assess effectiveness will be
different in each case.
However, what is clear is that there are still some research gaps
regarding the impact
of e-learning on educational and training environments, as well
as insufficient
studies on cost-effectiveness and long-term impact.
Research on e-learning design points out that one of the most
significant require-
ments for further adoption of e-learning is the development of
well-designed courses
with interactive and engaging content, structured collaboration
between peers, and
flexible deadlines to allow students to pace their work
(Siemens, 2014). Certainly,
every aspect of such a design can be interpreted in different
ways. Nevertheless,
research shows that structured asynchronous online discussions
are the most prom-
inent approach for supporting collaboration between students
and to support learn-
ing. Darabi et al. (2013) consider that the greatest impact on
student performance is
gained through “pedagogically rich strategies” that include
instructor participation,
interaction with students, and facilitation of student

collaboration as well as contin-
uous monitoring and moderating discussions. A promising
approach to developing
self-regulatory skills using externally facilitated scaffolds is
presented in Gašević,
Adescope, Joksimović, and Kovanović’s (2015) study. Their
research shows that
meaningful student-student interaction could be organized
without the instructor’s
direct involvement in discussions. There is a significant effect
of instructional design
that provides students with qualitative guidelines on how to
discuss, rather than
setting quantitative expectations only (e.g., number of messages
posted) (Gašević
et al., 2015). The provision of formative and individualized
feedback has also been
identified as an important challenge in e-learning (Noesgaard &
Ørngreen, 2015).
In addition to support from the theories of learning, we can also
find e-learning
models that provide specific support for designing effective
learning experiences for
students participating in online courses. Bozkurt et al. (2015)
provide a content
analysis of online learning journals from 2009 to 2013. In their
study, they found that
the Community of Inquiry model has been particularly relevant
to the successful
implementation of e-learning.
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In the Community of Inquiry model (Garrison, Anderson &
Archer, 2003),
learning is seen as both an individual and a social process, and
dialogue and debate
are considered essential for establishing and supporting e-
learning. The Community
of Inquiry model defines a good e-learning environment through
three major
components:
1. Cognitive presence: the learners’ ability to construct
knowledge through com-
munication with their peers
2. Social presence: the learners’ ability to project their personal
characteristics and
identities in an e-learning environment
3. Teaching presence: defined as the design, facilitation, and
direction of cognitive
and social processes for the purpose of realizing personally
meaningful and
educationally worthwhile learning outcomes
Teaching presence provides the necessary structures for a
community’s forma-
tion, social presence fosters a community’s development by
introducing students and
instructor to each other, and cognitive presence ensures the
community’s continuing
usefulness to its participants.
After undertaking an extensive review of the literature on online

interactions and
communities, Conole (2014) developed a new Community
Indicators Framework
(CIF) for evaluating online interactions and communities. Four
community indica-
tors appear to be common: participation, cohesion, identity, and
creative capability.
Participation and patterns of participation relate to the fact that
communities develop
through social and work activity over time. Different roles are
evident, such as
leadership, facilitation, support, and passive involvement.
Cohesion relates to the
way in which members of a community support each other
through social interaction
and reciprocity. Identity relates to the group’s developing self-
awareness and in
particular the notion of belonging and connection. Creative
capability relates to
how far the community is motivated and able to engage in
participatory activity.
The Community Indicators Framework (CIF) provides a
structure to support the
design and evaluation of community building and facilitation in
social and partici-
patory media. Research shows that structured asynchronous
online discussions are
the most prominent approach for supporting collaboration
between students and to
support learning.
The approaches described are based on a conception of the use
of e-learning in
formal learning contexts. However, the broad penetration of e-
learning prompts the

need to develop designs that allow formal and informal settings
to be linked. In this
sense, we maintain that an ecological approach can be useful to
support the systemic
perspective needed to integrate formal and informal processes.
Brown (2000) uses the term ecology as a metaphor to describe
an environment
for learning. “An ecology is basically an open, complex
adaptive system compris-
ing elements that are dynamic and interdependent. One of the
things that makes an
ecology so powerful and adaptable to new contexts is its
diversity.” Brown further
describes a learning ecology as “a collection of overlapping
communities of
interest (virtual), cross-pollinating with each other, constantly
evolving, and largely
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self-organizing.” The ecology concept requires the creation and
delivery of a
learning environment that presents a diversity of learning
options to the student.
This environment should ideally offer students opportunities to
receive learning
through methods and models that best support their needs,
interests, and personal
situations.

The instructional design and content elements that form a
learning ecology need
to be dynamic and interdependent. The learning environment
should enable instruc-
tional elements designed as small, highly relevant content
objects to be dynamically
reorganized into a variety of pedagogical models. This dynamic
reorganization of
content into different pedagogical models creates a learning
system that adapts to
varying student needs.
Barron (2006) defines personal learning ecologies as “the set of
contexts found in
physical or virtual spaces that provide opportunities for
learning. Each context is
comprised of a unique configuration of activities, material
resources, relationships
and the interactions that emerge from them” (Barron, 2006, p.
195).
From this perspective, learning and knowledge construction are
located in the
connections and interactions between learners, teachers, and
resources and seen as
emerging from critical dialogues and enquiries. Knowledge
emerges from the
bottom-up connection of personal knowledge networks. Along
these lines, Chatti,
Jarke, and Specht (2010, p. 78) refer to the learning as a
network (LaaN) perspective.
“Each of us is at the centre of our very own personal knowledge
network (PKN). A
PKN spans across institutional boundaries and enables us to
connect beyond the
constraints of formal educational and organisational

environments. Unlike commu-
nities, which have a start-nourish-die life cycle, PKNs develop
over time.”
Knowledge ecologies lie at the heart of the LaaN perspective as
a complex,
knowledge-intensive landscape that emerges from the bottom-up
connection of
personal knowledge networks.
The value of the ecological perspective is that it provides a
holistic view of
learning. In particular, it enables us to appreciate the ways in
which learners engage
in different contexts and develop relationships and resources.
The emphasis is on
self-organized and self-managed learning. The learner is viewed
as the designer and
implementer of their own life experience.
The important question here is whether we are using the
appropriate technology
in e-learning to support an ecological approach. In the next
section, we analyze the
use of learning management systems (LMS) and propose new
technological inno-
vations and solutions to improve e-learning.
Learning Ecosystems
There are very few technological innovations that reach a
sufficient level of maturity
to be considered as consolidated technologies in the productive
sector. It is also true
that some of these technologies arrive on the scene surrounded
by a halo of

fascination that leads to the creation of different ad hoc
practices, often resulting in
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unfulfilled expectations and eventually the complete
disappearance of said
technology.
In e-learning, LMS are a paradigmatic case. They are a fully
consolidated
educational technology, although the educational processes in
which they are
involved could improve substantially. E-learning platforms are
well established in
the higher education area and enjoy very significant adoption in
other educational
levels and the corporate sector.
Although LMS are very complete and useful as course
management tools, they
are too rigid in terms of communication flow, limiting
participants’ interaction
capabilities too much. For this reason, teachers and students
tend to complement
e-learning platforms with other tools, thereby creating personal
learning networks
(Couros, 2010).
It would seem that LMS have lost their appeal as a trending or
research topic due

to their known limitations, while different approaches and
technologies are
appearing in the education sector to claim the apparently empty
throne. Various
reports on educational technology trends underline topics such
as MOOCs
(SCOPEO, 2013), gamification (Lee & Hammer, 2011), learning
analytics
(Gómez-Aguilar et al. 2014), adaptive learning (Berlanga &
García-Peñalvo,
2005), etc., but none of these proposed technologies, by
themselves, have achieved
the disruptive effect that allows them to substantially improve
or change teaching
and learning processes.
Consequently, LMS can no longer be regarded as the only
component of tech-
nological/educational innovation and corporate knowledge
management strategy
(García-Peñalvo & Alier, 2014). Nevertheless, these platforms
should be a very
important component of a new learning ecosystem in
conjunction with all the
existing and future technological tools and services that may be
useful for educa-
tional purposes (Conde-González et al., 2014).
Technological ecosystems are the direct evolution of the
traditional information
systems orientated toward supporting information and
knowledge management in
heterogeneous contexts (García-Peñalvo et al., 2015).
Recently, there has been a fundamental change of approach in
debates on

innovation in academic and political systems toward the use of
ecologies and
ecosystems (Adkins, Foth, Summerville, & Higgs, 2007;
Aubusson, 2002; Crouzier,
2015). The European Commission has adopted these two
concepts as regional
innovation policy tools according to the Lisbon Declaration,
considering that a
technological ecosystem has an open software component-based
architecture that
is combined to allow the gradual evolution of the system
through the contribution of
new ideas and components by the community (European
Commission, 2006).
In fact, the technological ecosystem metaphor comes from the
field of biology
and has been transferred to the social area to better capture the
evolutionary nature of
people’s relationships, their innovation activities, and their
contexts (Papaioannou,
Wield, & Chataway, 2009). It has also been applied in the
services area as a more
generic conceptualization of economic and social actors that
create value in complex
systems (Frow et al., 2014) and in the technological area,
defining Software
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Ecosystems (SECO) (Yu & Deng, 2011) inspired by the ideas of

business and
biological ecosystems (Iansiti & Levien, 2004).
These software ecosystems may refer to all businesses and their
interrelations
with respect to a common product software or services market
(Jansen, Finkelstein,
& Brinkkemper, 2009). Also, from a more architecture-
orientated point of view, a
technological ecosystem may be studied as the structure or
structures in terms of
elements, the properties of these elements, and the relationships
between them, that
is, systems, system components, and actors (Manikas & Hansen,
2013).
Dhungana et al. (2010) state that a technological ecosystem may
be compared to a
biological ecosystem from resource management and
biodiversity perspectives, with
particular emphasis on the importance of diversity and social
interaction support.
This relationship between natural and technological is also
presented by other
authors who use the natural ecosystem concept to support their
own definition of
technological ecosystems (Chang & West, 2006; Chen & Chang,
2007). Although
there are various definitions of natural or biological ecosystems,
there are three
elements that are always present in all of them: the organisms,
the physical environ-
ment in which they carry out their basic functions, and the set
of relationships
between organisms and the environment. Thus, the
technological ecosystem may

be defined as a set of software components that are related
through information flows
in a physical medium that provides support for these flows
(García-Holgado &
García-Peñalvo, 2013).
The ecosystem metaphor is suitable for describing the
technological background
of educational processes because the ecosystem may recognize
the complex network
of independent interrelationships among the components of its
architecture. At the
same time, it offers an analytic framework for understanding
specific patterns in the
evolution of its technological infrastructure, taking into account
that its components
may adapt to the changes that the ecosystem undergoes and not
collapse if they
cannot assume the new conditions (Pickett & Cadenasso, 2002).
On the other hand,
the users of a technological ecosystem are also components of
the ecosystem
because they are repositories and generators of new knowledge,
influencing the
complexity of the ecosystem as artefacts (Metcalfe &
Ramlogan, 2008).
From the learning technologies perspective, the past has been
characterized by the
automation that spawned the development of e-learning
platforms. The present is
dominated by integration and interoperability. The future
challenge is to connect and
relate the different tools and services that will be available to
manage knowledge and
learning processes. This requires defining and designing more

internally complex
technological ecosystems, based on the semantic
interoperability of their compo-
nents, in order to offer more functionality and simplicity to
users in a transparent
way. Analyses of the behavior of technological innovations and
advances in cogni-
tive and education sciences indicate that the (near) future use of
information tech-
nology in learning and knowledge management will be
characterized by
customization and adaptability (Llorens, 2014).
The learning ecosystem as a technological platform should be
organized into a
container, the architectural framework of the ecosystem, and its
functional compo-
nents (García-Holgado & García-Peñalvo, 2016).
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INT
The framework should involve the integration, interoperability,
and evolution of
the ecosystem components and a correct definition of the
architecture that supports it
(Bo, Qinghua, Jie, Haifei, & Mu, 2009). The current status and
technical and
technological evolution of technological ecosystems show very
pronounced paral-
lelism with all the technology developing around the Internet
and cloud services.

More specifically, the evolution in data collection, analysis
procedures, and decision-
making drink from the same fountain as certain types of
emerging technologies such
as the Internet of things, the processes that extract concepts
from business intelli-
gence, or data mining processes applied to knowledge
management.
Figure 4 presents the essential architecture of a learning
ecosystem,
distinguishing the framework and a set of basic components for
analytics, adaptive
knowledge management, gamification, and evidence-based
portfolios.
The interconnection of platforms, tools, and services requires
communication
protocols, interfaces, and data and resource description
standards that enable data to
be entered and transmitted with minimal quality requirements
that allow its meaning
and context to be preserved. Interconnection protocols and data
collection rely on
platform interoperability, on the possibility of using sensors and
other ways of
gathering evidence of learning, on open data with standard
semantic content, and
even on descriptors and evidence linked to knowledge
acquisition processes (Retalis,
Papasalouros, Psaromiligkos, Siscos, & Kargidis, 2006). The
current state of devel-
opment of e-learning ecosystems and their extension to different
learning method-
ologies and paradigms pinpoints the relevance of this research
area for the process,

Fig. 4 Ecosystem architecture
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because data is the raw material (U.S. Department of Education
- Office of Educa-
tional Technology, 2012) for designing the learning cycle (data-
driven design),
assessing learning tasks and activities (learning analytics), and
even as a means of
providing real-time feedback (data-driven feedback) and
tailoring the learning
environment to the learner’s needs.
The most outstanding characteristic of these learning
ecosystems is that they are a
technological approach but they are not an end in themselves.
Instead, they serve the
pedagogical processes that teachers want to organize in the
technological contexts
they provide, masking the internal difficulty of the technology
itself.
Concluding Remarks
In the 1990s, student profiles in e-learning were similar to those
of classic distance
education: most learners were adults with occupational, social,
and family commit-
ments (Hanson et al., 1997). However, the current online learner

profile is beginning
to include younger students. For this reason, the concept of the
independent adult,
who is a self-motivated and goal-orientated learner, is now
being challenged by
e-learning activities that emphasize social interaction and
collaboration. Today’s
online learners are expected to be ready to share their work,
interact within small
and large groups in virtual settings, and collaborate in online
projects. According to
Dabbagh (2007, p. 224), “the emerging online learner can be
described as someone
who has a strong academic self-concept; is competent in the use
of online learning
technologies, particularly communication and collaborative
technologies; under-
stands, values, and engages in social interaction and
collaborative learning; pos-
sesses strong interpersonal and communication skills; and is
self-directed.” Stöter,
Bullen, Zawacki-Richter, and von Prummer (2014) identify a
similar list to Dabbagh
and also include learners’ personality traits and disposition for
learning, their self-
directedness, the level of motivation, time (availability,
flexibility, space) and the
level of interaction with their teachers, the learning tools they
have at their disposal,
and the level of digital competency, among many other
characteristics.
The research into learner characteristics identifies behaviors
and practices that
may lead to successful online learning experiences for learners.
However, it is

important to emphasize that due to today’s greater diversity of
profiles, there are
many influences on students’ individual goals and success
factors that are not easy to
identify. As Andrews and Tynan (2012) pointed out, part-time
online learners are a
very heterogeneous group. Due to this diversity of e-learners, it
is not appropriate to
privilege a particular pedagogical model, instead it is very
important to design
learning environments that take learners’ needs and the context
into account.
Providing formative, timely, and individualized feedback has
also been identified
as an important challenge in the online learning environment.
Likewise, more recent
studies have also highlighted the importance of timely,
formative, effective, and
individualized feedback in order to efficiently support learning.
As Siemens (2014) argues, there is also a great opportunity for
further research to
examine how (and whether) institutions are redesigning online
courses based on the
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lessons learned from MOOCs. Moreover, another potential line
of research might be
investigating how universities position online learning with

respect to on-campus
learning. Finally, current research also shows that higher
education has been primar-
ily focused on content design and curriculum development.
However, in order to
develop personalization, adaptive learning is crucial.
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source 2.pdf

Ahmadi International Journal of Research in English Education
(2018) 3:2
REVIEW Published online: 20 June 2018.
Mohammad Reza Ahmadi1*
* Correspondence:
[email protected]
1 Guilan University, Guilan, Iran
Received: 30 October 2017
Accepted: 10 January 2018
Published online: 20 June 2018
Abstract
The use of technology has become an important part of the
learning process

in and out of the class. Every language class usually uses some
form of
technology. Technology has been used to both help and improve
language
learning. Technology enables teachers to adapt classroom
activities, thus
enhancing the language learning process. Technology continues
to grow in
importance as a tool to help teachers facilitate language
learning for their
learners. This study focuses on the role of using new
technologies in learning
English as a second/foreign language. It discussed different
attitudes which
support English language learners to increase their learning
skills through
using technologies. In this paper, the researcher defined the
term technology
and technology integration, explained the use of technology in
language
classroom, reviewed previous studies on using technologies in
improving
language learning skills, and stated certain recommendations for
the better

use of these technologies, which assist learners in improving
their learning
skills. The literature review indicated that the effective use of
new
technologies improves learners’ language learning skills.
Keywords: technology, language learning, use
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nology
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uage+learning
http://ijreeonline.com/search.php?sid=1&slc_lang=en&key=use
http://dx.doi.org/10.29252/ijree.3.2.115
http://ijreeonline.com/article-1-120-en.html
(2018) 3:2 116
Website: www.ijreeonline.com, Email: [email protected]
Volume 3, Number 2, June 2018
1. Introduction
Language is one of the significant elements that affects
international communication activities.
Students utilize different parts of English language skills such
as listening, speaking, reading, and
writing for their proficiency and communication (Grabe &

Stoller, 2002). In addition, Ahmadi
(2017) stated that one of the important elements for learning is
the method that instructors use in
their classes to facilitate language learning process. According
to Becker (2000), computers are
regarded as an important instructional instrument in language
classes in which teachers have
convenient access, are sufficiently prepared, and have some
freedom in the curriculum. Computer
technology is regarded by a lot of teachers to be a significant
part of providing a high-quality
education.
According to Bull and Ma (2001), technology provides offers
unlimited resources to language
learners. Harmer (2007) and Genç lter (2015) emphasized and
teachers should encourage learners
to find appropriate activities through using computer technology
in order to be successful in
language learning. Clements and Sarama (2003) declare that the
use of suitable technological
materials can be useful for learners. According to Harmer
(2007), using computer-based language
activities improve cooperative learning in learners.

Furthermore, Tomlison (2009) and Genç lter (2015) say that
computer-based activities provide
learners rapid information and appropriate materials. They
continue that internet materials
motivate learners to learn more. In addition, Larsen-Freeman
and Anderson (2011) supported the
view that technology provides teaching resources and brings
learning experience to the learners’
world. Through using technology, many authentic materials can
be provided to learners and they
can be motivated in learning language.
Technology has always been an important part of teaching and
learning environment. It is an
essential part of the teachers’ profession through which they can
use it to facilitate learners’
learning. When we talk about technology in teaching and
learning, the word ‘integration’ is used.
With technology being part of our everyday lives, it is time to
rethink the idea of integrating
technology into the curriculum and aim to embed technology
into teaching to support the learning
process. That is to say, technology becomes an integral part of
the learning experience and a
significant issue for teachers, from the beginning of preparing

learning experiences through to
teaching and learning process (Eady & Lockyer, 2013).
Solanki and Shyamlee1 (2012) and Pourhosein Gilakjani (2017)
supported the view that language
teaching method has been changed due to technology. The
researchers continued that the
application of technology helps learners learn on the basis of
their interests. It also satisfies both
visual and auditory senses of the learners. According to Lam
and Lawrence (2002) and Pourhosein
Gilakjani (2017), technology assists learners in adjusting their
own learning process and they can
have access to a lot of information that their teachers are not
able to provide.
According to Pourhosein Gilakjani (2013), the use of
technologies has the great potential to change
the existing language teaching methods. Pourhosein Gilakjani
and Sabouri (2014) emphasized that
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(2018) 3:2 117
through using technology, learners can control their own
learning process and have access to many

information over which their teachers cannot control.
Technology has an important role in
promoting activities for learners and has a significant effect on
teachers’ teaching methods. If
teachers do not use technologies in their teaching they will
never be able to keep up with these
technologies. Thus, it is very important for teachers to have a
full knowledge of these technologies
in teaching language skills (Pourhosein Gilakjani, 2017; Solanki
& Shyamlee1, 2012).
Developing learners’ knowledge and skills pertinent to
computer technology provides equity of
opportunity, regardless of learners’ background. Although
learners have been born into a
technologically rich world, they may not be skilful users of
technology (Bennett, Maton & Kervin,
2008). In addition, just providing access to technology is not
adequate. Meaningful development
of technology-based knowledge is significant for all learners in
order to maximize their learning
(OECD, 2010). In this review paper, the researcher will review
some of the significant issues
pertinent to the use of technology in the learning and teaching
of English language skills. These

issues are as follows: definition of technology, the use of
technology in the classroom, previous
studies on using technologies in improving English language
learning skills, and recommendations
for using technologies.
2. Definition of Technology and Technology Integration
Technology has been defined by different researchers.
According to İŞMAN (2012), it is the
practical use of knowledge particularly in a specific area and is
a way of doing a task especially
using technical processes, methods, or knowledge. The usage of
technology includes not only
machines (computer hardware) and instruments, but also
involves structured relations with other
humans, machines, and the environment (İŞMAN, 2012).
According to Hennessy, Ruthven, and Brindley (2005) and
Pourhosein Gilakjani (2017),
technology integration is defined in terms of how teachers use
technology to perform familiar
activities more effectively and how this usage can re-shape
these activities. Dockstader (2008)
defined technology integration as the use of technology to
improve the educational environment.

It supports the classroom teaching through creating
opportunities for learners to complete
assignments on the computer rather than the normal pencil and
paper.
3. Use of Technology in English Language Class
Technology is an effective tool for learners. Learners must use
technology as a significant part of
their learning process. Teachers should model the use of
technology to support the curriculum so
that learners can increase the true use of technology in learning
their language skills (Costley,
2014; Murphy, DePasquale, & McNamara, 2003). Learners’
cooperation can be increased through
technology. Cooperation is one of the important tools for
learning. Learners cooperatively work
together to create tasks and learn from each other through
reading their peers’ work (Keser,
Huseyin, & Ozdamli, 2011).
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Bennett, Culp, Honey, Tally, and Spielvogel (2000) asserted

that the use of computer technology
lead to the improvement of teachers’ teaching and learners’
learning in the classes. The use of
computer technology helps teachers meet their learners’
educational needs. According to
Bransford, Brown, and Cocking (2000), the application of
computer technology enables teachers
and learners to make local and global societies that connect
them with the people and expand
opportunities for their learning. They continued that the
positive effect of computer technology
does not come automatically; it depends on how teachers use it
in their language classrooms.
According to Susikaran (2013), basic changes have come in
classes beside the teaching methods
because chalk and talk teaching method is not sufficient to
effectively teach English. Raihan and
Lock (2012) state that with a well-planned classroom setting,
learners learn how to learn
efficiently. Technology-enhanced teaching environment is more
effective than lecture-based class.
Teachers should find methods of applying technology as a
useful learning instrument for their
learners although they have not learnt technology and are not

able to use it like a computer expert.
The application of technology has considerably changed English
teaching methods. It provides so
many alternatives as making teaching interesting and more
productive in terms of advancement
(Patel, 2013). In traditional classrooms, teachers stand in front
of learners and give lecture,
explanation, and instruction through using blackboard or
whiteboard. These method must be
changed concerning the development of technology. The usage
of multimedia texts in classroom
assists learners in become familiar with vocabulary and
language structures. The application of
multimedia also makes use of print texts, film, and internet to
enhance learners’ linguistic
knowledge. The use of print, film, and internet gives learners
the chance to collect information and
offers them different materials for the analysis and
interpretation of both language and contexts
(Arifah, 2014).
Dawson, Cavanaugh, and Ritzhaupt (2008) and Pourhosein
Gilakjani (2014) maintained that using
technology can create a learning atmosphere centered around
the learner rather than the teacher

that in turn creates positive changes. They emphasized that by
using computer technology,
language class becomes an active place full of meaningful tasks
where the learners are responsible
for their learning. Drayton, Falk, Stroud, Hobbs, and
Hammerman (2010) argued that using
computer technology indicates a true learning experience that
enhances learners’ responsibilities.
Technology encourages learners to learn individually and to
acquire responsible behaviors. The
independent use of technologies gives learners self-direction.
According to Arifah (2014), the use of internet increases
learners’ motivation. The use of film in
teaching helps learners to realize the topic with enthusiasm and
develop their knowledge. Learners
can learn meaningfully when technology is used in the process
of learning through using computer
and internet. When learners learn with technology, it assists
them in developing their higher order
thinking skills. It can be concluded that the true combination of
multimedia and teaching
methodology is very important to attract learners’ attention
towards English language learning.

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4. Previous Studies on the Benefits of Technology in Improving
Language Skills
Some studies have been done on the advantages of using
technology in English language teaching
and learning. Hennessy (2005) stated the use of ICT acts as a
catalyst in motivating teachers and
learners to work in new ways. The researcher understood that as
learners become more
autonomous, teachers feel that they should urge and support
their learners to act and think
independently. The application of Computer Assisted Language
Learning (CALL) changes
learners’ learning attitudes and enhances their self-confidence
(Lee, 2001).
Information and communication technologies (ICTs) have some
benefits for teaching and learning.
First, learners play an active role, which can help them retain
more information. Next, follow-up
discussions involve more information where learners can
become more independent. Finally,

learners can process new learner-based educational materials
and their language learning skills can
increase (Costley, 2014; Tutkun, 2011).
The use of technology has changed the methods from teacher-
centered to learner-centered ones.
Teachers should be facilitators and guide their learners’
learning and this change is very useful for
learners to increase their learning (Riasati, Allahyar, & Tan,
2012). Gillespie (2006) said that the
use of technology increases learners’ cooperation in learning
tasks. It assists them in gathering
information and interacting with resources such as videos.
Warschauer (2000a) described two different views about how to
integrate technology into the
class. First, in the cognitive approach, learners get the
opportunity to increase their exposure to
language meaningfully and make their own knowledge. Second,
in the social approach, learners
must be given opportunities for authentic social interactions to
practice real life skills. This
objective can be obtained through the collaboration of learners
in real activities.
Eaton (2010) told that computer-based communication is a

useful feature for language learning.
Computer-assisted discussion features more equal participation
than face to-face discussion. Zhao
(2013) supported the above view and said that access to
authentic materials in the target language
is critical for successful language learning.
According to Rodinadze and Zarbazoia (2012), technology helps
learners and teachers in studying
the course materials owing to its fast access. Advancements i n
technology have a key role in
preparing learners to use what they learn in any subject matter
to finding their place in the world
labor-force. Technology facilitates learners’ learning and serves
as a real educational tool that
allows learning to occur.
Baytak, Tarman, and Ayas (2011) carried out a on the role of
technology in language learning. The
results revealed learners’ learning was improved by integrating
technology into the classroom.
Learners stated that the use of technology in school makes
learning enjoyable and helps them learn
more. Learners also said that technology makes learning
interesting, enjoyable, and interactive.

The other outcome of this research was that the use of
technology increases learners’ motivation,
social interactions, learning and engagement.
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Mouza (2008) and Sabzian, Pourhossein Gilakjani, and Sodouri
(2013) asserted that one of the
impacts of using technology in the language classes is the
increase in cooperation among teachers
and learners. When teachers allow learners to become assistants
in the teaching process, this can
increase learners’ confidence. Learners are granted the chance
to reinforce opinions and abilities
already learnt. Learners can help teachers in technology
integration because learners have had
abundant time to master technology while teachers work on
directing the instruction.
Drayton, Falk, Hobbs, Hammerman, and Stroud (2010) also
emphasized that the use of computer-
based classroom shows a real learning experience that increases
learners’ responsibility. Teachers
said that the use of Internet and e-mail urges learner-centered

learning. Warschauer (2000) and
Parvin and Salam (2015) carried out a study and declared that
by using technology, learners get
the chance to increase their exposure to language in a
meaningful context and make their own
knowledge. Learners should have opportunities for social
interactions to practice real life skills.
This is achieved through learners’ cooperation in real activities.
Baytak, Tarman, and Ayas (2011) performed a research towards
the effect of technology on
learning. The findings obtained from this study revealed that
learners increased their learning
through incorporating technology into their classes. The
researchers emphasized that technology
made learners’ learning interesting and interactive and
increased their motivation, social
interactions, and engagement.
Peregoy and Boyle (2012) carried a study on using technology
in improving learners’ reading and
writing skills. The results of this study indicated that
technology tools enhanced learners’ reading
and writing skills because they are user-friendly, and learners
can learn at a faster and more

effective way. The other finding of this study was that leaners
learn more effectively when they
use technology tools instead of traditional teaching method
because the Internet provided a
favorable learning environment for learners’ learning,
facilitated a new platform for learners who
can have a convenient access to learning lessons.
The other study was done by Alsaleem (2014) on using
WhatsApp applications in English dialogue
journals to improve learners’ writing, vocabulary, word choice,
and speaking ability. Based on the
results of this study, it was concluded that WhatsApp showed
improvement in learners’ writing
skills, speaking skill, vocabulary, and word choice. Godzicki,
Godzicki, Krofel, and Michaels
(2013) performed a study on examining students’ motivation
and engagement in the classroom.
The findings obtained from this study revealed that students
were more likely to engage in
classroom when technology is used as an educational tool inside
the class. Technology tools show
an improvement when it comes down to accessibility and
motivation.
Lin and Yang (2011) performed a study to investigate whether

Wiki technology would improve
learners’ writing skills. Learners were invited to join a Wiki
page where they would write passages
and then read and answer the passages of their fellow
classmates. Learners indicated that the
immediate feedback they received was a benefit of using this
kind of technology. Another finding
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(2018) 3:2 121
was that learners learned vocabulary, spelling, and sentence
structure by reading the work of their
classmates.
5. Recommendations for the Successful Integration of
Technology
In the following section, the researcher presents some
recommendations for learners to improve
their language skills through using technology:
1. Teachers should implement a technology plan that considers
integration strategies along with
purchasing decisions (Pourhossein Gilakjani, Leong, & Hairul,
2013).

2. Professional development should be specifically considered
in order to assure learners’ learning
and to change the attitudes of teachers unfamiliar with the
advantages that technology provides
(Pourhossein Gilakjani, Leong, & Hairul, 2013).
3. The technology plan must be closely aligned with the
curriculum standards. Teachers should
know what educational approach is the most effective one when
integrating technologies in the
classroom (Pourhossein Gilakjani, Leong, & Hairul, 2013).
4. The computer technology is an integral part of the learning
activity through which skills are
transferred to learners.
5. Language teachers should urge their learners to use
technology in developing their language
skills.
6. Universities should regard technology as a significant part of
teaching and learning programs.
7. Technology experts should provide extra assistance for
teachers who use it in teaching their
English courses.
8. Teachers should be a pattern for their learners in using
computer technology (MEB, 2008;

Pourhossein Gilakjani, & Sabouri, 2017).
9. Teachers should create technology-integrated lesson
materials. These materials should
concentrate on teaching and learning, not just on technology
issues.
10. Teachers should find the ways that technology can help
them towards learner-centered
instruction as opposed to teacher-centered instruction.
11. Teachers should be aware of their roles as guides and
facilitators of their learners’ learning
(Molaei & Riasati, 2013; Pourhossein Gilakjani, & Sabouri,
2017).
12. In order to facilitate the integration of technology, enough
support and technical assistance
should be provided for teachers.
13. Training should be provided for teachers to learn how to use
and teach it effectively.
14. Teachers should seek the guidance from their colleagues
who can help them teach better
through using technology.
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(2018) 3:2 122

15. Technology is one of the important tools of language
learning activity; it helps learners to
improve their language learning skills.
16. Teachers should encourage their learners to use technology
in increasing their language
abilities.
6. Conclusion
In this paper, the researcher reviewed some important issues
pertinent to the use of technology in
language learning. The literature review indicated that
technology resources cannot guarantee
teachers’ teaching and learners’ learning. Teachers should be
convinced of the usefulness and
advantages of technology in improving learners’ learning. This
means that teachers need support
and training for integrating technology into language teaching.
The review revealed that when
technology is used appropriately, it can bring about a lot of
advantages to teachers and learners. It
is a resource that can be used by learners because it helps them
solve their learning problems and

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