网络在线学习外文文献翻译中英文

网络在线学习外文翻译中英文

英文

Online learning: Adoption, continuance, and learning outcome

—

A review of

literature

Ritanjali Panigrahi, Praveen Srivastava, Dheeraj Sharma

Abstract

The

use

of

Technology

to

facilitate

better

learning

and

training

is

gaining

momentum

worldwide,

reducing

the

temporal

and

spatial

problems

associated

with

traditional learning. Despite its several benefits, retaining students in online platforms

is

challenging.

Through

a

literature

review

of

the

factors

affecting

adoption,

the

continuation

of

technology

use,

and

learning

outcomes,

this

paper

discusses

an

integration of online learning with virtual communities to foster student engagement

for

obtaining

better

learning

outcomes.

Future

directions

have

been

discussed,

the

feedback mechanism which i

s an antecedent of students’ continuation intention has a

lot

of

scopes

to

be

studied

in

the

virtual

community

context.

The

use

of

Apps

in

m-learning

and

the

use

of

cloud

services

can

boost

the

ease

and

access

of

online

learning to users and organizations.

Keywords:

Online

learning,

Virtual

community,

Technology

adoption,

Technology continuation, Learning outcome

Introduction

Online

learning

and

training

are

gaining

popularity

worldwide,

reducing

the

temporal and spatial problems associated with the traditional form of education. The

primary

factors

behind

using

online

learning

are

not

only

to

improve

access

to

education

and

training,

and

quality

of

learning,

but

also

to

reduce

the

cost

and

improve the cost-effectiveness of education (Bates, 1997). Online learning is mainly

provided

in

two

ways

—

in

synchronous

and

asynchronous

environments

(Jolliffe,

Ritter,

&

Stevens,

2012).

The

time

lag

attributes

of

asynchronous

learning

unlike

synchronous

learning

in

online

platforms

take

the

advantage

of

accessing

materials

anytime

and

anywhere,

ability

to

reach

a

greater

mass

at

the

same

time,

and

uniformity of content. Online learning along with face-to-face learning is successfully

1

used

in

industry

as

well

as

academia

with

positive

outcomes

(Chang,

2016).

The

geographically distributed team in an organization can get their skill training through

online platforms at the same time, gaining a greater level of competitiveness. Online

learning

is

also

beneficial

for

students

as

they

can

learn

at

their

own

pace

with

the

availability

of

online

materials.

The

e-learning

market

is

becoming

popular

and

widely

adopted

by

the

education

sector

and

industry.

The

growth

of

the

e-learning

market can be demonstrated by the fact that the global e-learning market is expected

to reach 65.41 billion dollars by 2023 growing at a cumulative average growth rate of

7.07%

(Research

and

Markets,

2018a).

In

addition

to

this,

the

global

learning

management system (LMS) is expected to increase from 5.05 billion USD in 2016 to

18.44

billion

USD

by

2025

growing

at

a

rate

of

15.52%

(Research

and

Markets,

2018b).

Despite

several

advantages

of

online

learning

such

as

improving

access

to

education

and

training,

improving

the

quality

of

learning,

reducing

the

cost

and

improving the cost-effectiveness of education, retaining students in such platforms is

a key challenge with a high attrition rate (Perna et al., 2014). Several strategies such

as briefing, buddying, and providing feedback on the platform are proposed to retain

and

engage

students

(Nazir,

Davis,

&

Harris,

2015).

It

is

also

noted

that

more

self-discipline is required by students in online education, unlike traditional classroom

education

(Allen

&

Seaman,

2007).

Keeping

users

enrolled

and

engaged

is

a

challenging

job

as

a

personal

touch

by

the

instructor

is

missing

or

limited.

The

learning engagement which is an important antecedent for learning outcome is lower

for technology-mediated learning than face-to-face learning (Hu & Hui, 2012). As a

higher amount of money is spent on infrastructure, staff training, etc., organizations

seek to take maximum benefit from online learning which requires an understanding

of the factors that drive the adoption, continuation intention, and learning outcome of

users on online learning platforms. Therefore, the primary focus of research remains

on

how

to

retain

online

learning

users,

and

increase

the

efficiency

of

the

online

learning.

Users may learn inside and outside the classroom; inside classroom learning is

2

through

instructors

either

from

face-to-face,

pure

online

or

blended

learning

(combination

of

face-to-face

and

pure

online

learning)

whereas

outside

classroom

learning is conducted by users anytime and anywhere after the class. The exponential

growth of the

Internet has enabled individuals to share information, participate, and

collaborate to learn from virtual communities (VC) anytime and anywhere (Rennie &

Morrison, 2013). In a virtual community, people do everything that they do in real life

but leaving their bodies behind (Rheingold, 2000). Virtual communities keep its users

engaged

based

on

familiarity,

perceived

similarity,

and

trust

by

creating

a

sense

of

belongingness (Zhao, Lu, Wang, Chau, & Zhang, 2012). It is essential to assess the

role of a less constrained informal mode of learning (Davis

& Fullerton, 2016) like

virtual communities in the formal learning to engage and retain students.

Discussion

Getting a new idea adopted even when it has obvious advantages is often very

difficult

(Rogers,

2003).

Consistent

with

the

previous

statement,

despite

the

advantages

of online learning such as improving accessibility, quality, and reducing

cost, it has a long way to go to be adopted and used by organizations because of the

resistance at different levels (Hanley, 2018). The reasons for resistances offered by the

employees in an organizations include perceived poor focus of the e-learning initiative,

lack

of

time

to

learn

new

way

of

working,

too

much

effort

to

change,

lack

of

awareness, and resistance to change (Ali et al., 2016; Hanley, 2018). It is crucial from

an institutional point of view to overcome the resistance to adopt and implement the

online learning systems successfully.

Understanding the factors of online learning adoption, continuation use intention,

and

learning

outcomes

are

vital

for

an

e-learning

platform

providing

organization

because the success of the platform depends on the successful adoption, continuation

use, and finally achieving the desired outcomes. From the literature, it is found that

the

national

culture

affects

the

adoption

and

moderates

the

relationship

between

variables of adoption and use. Therefore, the results of adoption and use of technology

might differ in different counties with different cultural dimensions. At a broader level,

the

perceived

characteristics

of

innovation

(of

online

learning)

such

as

relative

3

advantage, compatibility, complexity, trialability, and observability play a significant

role

in

adoption.

At

an

individual

level,

the

primary

factors

of

adoption

are

the

individual

expectancies

such

as

the

perceived

usefulness,

perceived

ease

of

use,

perceived

enjoyment,

performance

expectancy,

effort

expectancy,

etc.,

and

the

external

influences

such

as

subjective

norm,

social

norms,

surrounding

conditions,

national

culture,

social

network

characteristic,

etc.

On

the

other

hand,

the

primary

factors of continuation of technology use are the experiences of the individuals in the

technology such as satisfaction, confirmation, self-efficacy, flow, trust, we- intention,

sense

of

belongingness,

immersion,

IS

qualities,

etc.

The

perceived

usefulness

and

perceived

ease

of

use

are

found

to

be

vital

for

both

the

technology

adoption

and

continuation use. This implies that the usefulness of the technology and how easy the

technology to use determines the adoption and continuation of technology. Apart from

these

technology

enablers,

the

platform

providers

should

consider

the

technology

inhibitors which negatively impact

the acceptance of the technology. The factors of

the learning outcomes such as self-efficacy, virtual competence, engagement, design

interventions, etc. should be considered before designing and delivering the content in

the

online

learning

platform

to

achieve

optimum

learning

outcomes.

The

learners’

intention

to

use

full

e-learning

in

developing

countries

depends

on

the

lea

rners’

characteristics, and learners’ adoption of blended learning (Al

-Busaidi, 2013). Studies

for example by Verbert et al. (2014) have shown that blended learning yields the best

outcome in terms of grade when students learn in online collaborative learning with

teacher’s

initiation

and

feedback.

On

the

contrary,

some

studies

have

shown

that

contents such as business games do not need the interaction with the instructor; in fact,

they are negatively related to perceived learning (Proserpio & Magni, 2012). MOOC

(Massive Open Online Course) users have organized face-to-face meetings to fulfill

their belongingness or social connectedness as a part of their learning activity (Bulger,

Bright, & Cobo, 2015). This indicates that not everyone is good with a digitized form

of learning, and hence both face-to-face and online components should be integrated

for better outcomes.

Lack of human connection is one of the limitations of online learning (Graham,

4

2006)

which

may

reduce

the

satisfaction

level.

To

address

this

limitation,

personalization

functions

of

e-learning

systems

began.

The

satisfaction

level,

perceived and actual performance, self-efficacy scores increase in personalized online

learning where learning materials are provided according to the cognitive capability

and

style

of

each

individual

(Xu,

Huang,

Wang,

&

Heales,

2014).

Although

personalization

of

e-learning

systems

is

beneficial,

they

are

socially

and

ethically

harmful,

and

special

attention

should

be

given

to

issues

such

as

privacy

compromisation,

lack

of

control,

the

commodification

of

education,

and

reduced

individual capability (Ashman et al., 2014). Personal e-learning systems collect user

information to understand the users’ interests and requirements for the learning which

violates the privacy of individuals. The system utilizes the user information to show

the

personal

content

where

the

individuals

do

not

have

control

over

the

learning

content.

Hence

they

are

limited

to

certain

personal

contents

which

reduce

their

individual capabilities.

Studies, for example, Zhao et al. (2012) have shown that VCs create a sense of

belongingness

and

keeps

the

members

engaged

which

results

in

improving

the

learning outcome, and users with same age groups are less likely to attrite (Freitas et

al.,

2015).

Studies

have

shown

that

engagement

is

promoted

when

criteria

such

as

problem-centric

learning

with

clear

expositions,

peer

interaction,

active

learning,

instructor accessibility and passion, and using helpful course resources are met (Hew,

2015).

Social

interactions

through

social

networking

produce

an

intangible

asset

known as social capital (Coleman, 1988) in terms of the trust, collective action, and

communication.

Social

capital

is

positively

related

to

online

learning

satisfaction

in

group

interactions,

class

interactions,

learner- instructor

interactions,

as

well

as

increasing students’ e

-learning performance in groups (Lu, Yang, & Yu, 2013).

The continuous development of mobile technology has expanded the opportunity

to learn from mobile devices anywhere, anytime. M-Learning is much more beneficial

for

accessing

education

in

remote

areas

and

developing

countries.

The

success

of

M-learning

in

organizations

depends

on

organizational,

people,

and

pedagogical

factors

apart

from

technological

factors

(Krotov,

2015).

A

range

of

mobile

5

technologies

such

as

laptops,

smartphones,

and

tablets

are

embraced

by

students

to

support

informal

learning

(Murphy,

Farley,

Lane,

Hafeez-Baig,

&

Carter,

2014).

Learning

through

mobile

devices

poses

both

opportunities

as

well

as

challenges;

it

provides flexibility in learning, on the other hand, it is a limitation for those who do

not

have

connectivity

and

access

to

these

devices.

In

student-centered

learning

especially collaborative and project- based learning, the use of mobile devices can be

promoted by the mobile apps (Leinonen, Keune, Veermans, & Toikkanen, 2014). The

use

of

mobile

apps

along

with

guidance

from

teachers

integrates

reflection

in

the

classroom learning (Leinonen et al., 2014).

Cloud

computing

provides

organizations

with

a

way

to

enhance

their

IT

capabilities without a huge investment in infrastructure or software. The benefits of

cloud

computing

are

low

cost,

scalability,

centralized

data

storage,

no

maintenance

from user side (no software needed), easy monitoring, availability and recovery, and

the

challenges

include

it

requires

fast

and

reliable

internet

access,

and

privacy

and

security issues (El Mhouti, Erradi, & Nasseh, 2018). The primary factors for adoption

of

cloud

computing

in

e-learning

are

ease

of

use,

usefulness,

and

security

(Kayali,

Safie,

& Mukhtar, 2016). Private cloud

inside

educational

institutes can

acquire the

additional

benefits

in

non- compromising

the

security

and

data

privacy

concerns

associated

with

cloud

computing

(Mousannif,

Khalil,

&

Kotsis,

2013).

Cloud

computing provides support to the online learning platforms to store and process the

enormous amount of data generated. The problem of managing the increasing growth

of

online

users,

contents,

and

resources

can

be

resolved

by

using

cloud

computing

services (Fernandez, Peralta, Herrera, & Benitez, 2012).

Future directions

Future directions of research in online learning are as follows: First, the feedback

mechanism used in

online learning in

institutions has not

been used to

measure the

continuation

intention

in

VCs.

Feedback

enables

learners

to

define

goals

and

track

their progress

through dashboard

applications to promote awareness,

reflection, and

sense-

making

(Verbert

et

al.,

2014).

The

students

who

received

teachers’

feedback

along

with

online

learning

achieved

better

grades

than

those

who

did

not

receive

6

feedback

(Tsai,

2013)

and

students

positively

perceive

the

feedback

systems

more

than the educators (Debuse & Lawley, 2016). Although immediate feedback is one of

the dimensions of the flow (Csikszentmihalyi, 2014), the factor has not been studied

in a VC context.

It is vital for managers to check if feedback on a community post

fosters

the

members’

continuation

intention,

and

they

should

design

user

interfaces which encourage providing feedback. Second, it is high time to develop an

integrated

model

for

formal

learning

(online

and

blended)

with

VCs

for

students’

engagement. Informal learning as itself, not limited to the body of knowledge, rather,

is the result of the interaction of people via communities of practice, networks, other

forms, etc. (Rennie & Mason, 2004). The networked communities build intimacy and

support

which

helps

in

self- directed

learning

(Rennie

&

Mason,

2004)

which

is

an

important

parameter

for

online

learning.

Community

commitment

(Bateman

et

al.,

2011), immersion (Shin et al., 2013), we-intentions (Tsai & Bagozzi, 2014), sense of

belongingness (Zhao et al., 2012), etc. from the VC would help students to continue

the engagement for a better learning outcome. Moreover, it is found that collaborative

chat

participation

in

MOOCs

slows

down

the

rate

of

attrition

over

time

(Ferschke,

Yang, Tomar, & Rosé

, 2015). It is of great importance to check if learning outcome

improves

when

the

virtual

community

is

integrated

or

embedded

in

the

learning

environment

(online

and

blended).

The

educators

and

managers

should

encourage

their students and employees to participate in VCs. Third, the growth of the adoption

of

mobile

devices

has

expanded

the

arena

of

e-learning

platforms.

Integrating

the

virtual communities via a mobile platform with online learning can foster the student

engagement resulting in higher learning outcome. Fourth, cloud computing has great

potential

in

dealing

with

the

scalability

issues

arising

from

the

rise

in

numbers

of

users,

content,

and

resources

in

online

learning.

Furthermore,

it

can

provide

tremendous

benefits

to

organizations

as

well

as

users

in

terms

of

ease

of

access,

flexibility,

and

lower

cost.

Although

a

few

studies

cover

cloud

computing

infrastructure

in

education

and pedagogic processes,

the

empirical

research

on

the

cloud

computing

for

education

is

very

shallow

(Baldassarre,

Caivano,

Dimauro,

Gentile, & Visaggio, 2018). As the mobile devices are often limited by storage space,

7