investigating the factors determining e-learning effectiveness in tourism and hospitality education

This article was downloaded by: [University of North Texas]On: 26 November 2014, At: 15:28Publisher: RoutledgeInforma Ltd Registered in England and Wales Registered Number: 1072954 Registered office: Mortimer House,37-41 Mortimer Street, London W1T 3JH, UK

Journal of Hospitality & Tourism EducationPublication details, including instructions for authors and subscription information:http://www.tandfonline.com/loi/uhat20

Investigating the Factors Determining e-LearningEffectiveness in Tourism and Hospitality EducationMarianna Sigala aa University of the Aegean in Chios , GreecePublished online: 24 May 2013.

To cite this article: Marianna Sigala (2004) Investigating the Factors Determining e-Learning Effectiveness in Tourism andHospitality Education, Journal of Hospitality & Tourism Education, 16:2, 11-21, DOI: 10.1080/10963758.2004.10696789

To link to this article: http://dx.doi.org/10.1080/10963758.2004.10696789

PLEASE SCROLL DOWN FOR ARTICLE

Taylor & Francis makes every effort to ensure the accuracy of all the information (the “Content”) containedin the publications on our platform. However, Taylor & Francis, our agents, and our licensors make norepresentations or warranties whatsoever as to the accuracy, completeness, or suitability for any purpose of theContent. Any opinions and views expressed in this publication are the opinions and views of the authors, andare not the views of or endorsed by Taylor & Francis. The accuracy of the Content should not be relied upon andshould be independently verified with primary sources of information. Taylor and Francis shall not be liable forany losses, actions, claims, proceedings, demands, costs, expenses, damages, and other liabilities whatsoeveror howsoever caused arising directly or indirectly in connection with, in relation to or arising out of the use ofthe Content.

This article may be used for research, teaching, and private study purposes. Any substantial or systematicreproduction, redistribution, reselling, loan, sub-licensing, systematic supply, or distribution in anyform to anyone is expressly forbidden. Terms & Conditions of access and use can be found at http://www.tandfonline.com/page/terms-and-conditions

http://www.tandfonline.com/loi/uhat20

http://www.tandfonline.com/action/showCitFormats?doi=10.1080/10963758.2004.10696789

http://dx.doi.org/10.1080/10963758.2004.10696789

http://www.tandfonline.com/page/terms-and-conditions

http://www.tandfonline.com/page/terms-and-conditions

10 Volume 16, Number 2 11Journal of Hospitality &Tourism Education

Investigating the Factors Determining e-Learning Effectiveness in Tourism and Hospitality Educationby Marianna Sigala, Ph.D.

Introduction Internet advances enable

students to receive and interact

with educational materials and to

engage with teachers and peers

in ways that previously may have

been impossible. Indeed, because

of its three unique features namely,

interactivity, connectivity and

technological convergence, the

Internet has irrevocably altered

how people access information and

how much information anyone can

access, while local and wide-area

networks release the Internet as

a learning resource with software

tools that enable interactive com-

munication. Moreover, the WWW

enables instructors to electronically

publish and distribute course notes,

assignments and study guides in-

stantly and globally. Instructors can

also create online bibliographies

by “linking” their course work

presentations to related themes at

other websites. Computer network-

based systems are being designed

specifically to support classroom

experiences, especially group dis-

cussions and joint projects, while

electronic discussion groups and

“chat rooms” extend the reach of

the classroom beyond the physical

campus.

However, although e-learning is widely being ad-

opted for enhancing and complementing tourism and

hospitality instruction (Sigala & Christou, 2003) and

its advantages for tourism and hospitality education

are extensively argued (Sigala, 2002; Cho Schmelzer &

McMahon, 2002; Clements et al, 2001), little is known

on how to design and implement effective e-learning

platforms. On the other hand, it is generally agreed

that the re-implementation of conventional models

borrowed from classroom based or distance education

that are focused on passive transmission would permit

only marginal improvements. Thus, there is a need to

first re-examine how knowledge is acquired and online

learning and instruction occur and then identify the

factors that can enhance such online learning experi-

ences.

This paper aims to identify the critical success

factors determining effectiveness of e-learning used in

tourism and hospitality education.

However, as the evaluation of any

form of learning should be based

on a theoretical framework to al-

low for the interpretation of results

(Rice, 1984), the paper first investi-

gated and analysed the educational

objectives and theoretical under-

pinnings against which e-learning

must be evaluated. This analysis

then led to the identification of

the factors determining e-learning

effectiveness. The significance and

impact of these factors were tested

by gathering data from students

participating in Virtual Learning

Environments (VLE) that were used

as a support and enhancement

Marianna Sigala, Ph.D., is Lecturer in Operations & Production Management in the Business Administration department, at the University of the Aegean in Chios, Greece.

“Computer network-based systems are being designed specifically to support classroom experiences, especially group discussions and joint projects, while electronic discussion groups and “chat rooms” extend the reach of the classroom beyond the physical campus.”

Dow

nloa

ded

by [

Uni

vers

ity o

f N

orth

Tex

as]

at 1

5:28

26

Nov

embe

r 20

14


instructional tool for traditional

classroom-based instruction. Re-

search findings provided several

guidelines and suggestions for the

design and implementation of

technologically and pedagogically

effective e-learning applications.

Theoretical Underpinnings and Aims of e-Learning

Internet’s capabilities imply

a different type of thinking in

terms of how to make full use of

its learning-enhancing features and

pedagogical potential. In particular,

Internet’s affordance for enhanced

communication provides great

opportunities for combining collab-

orative techniques with technology

to dramatically enhance the learn-

ing process and learning outcomes

(Sigala, 2002; Cho et al, 2002).

Harasim (2000) also advocated that

the asynchronous, hypertext and

multimedia based nature of the

technology represents cognitive

advantages - such as flexibility with

regard to the nature of interaction,

reflection on stored communica-

tion or reduction of discriminatory

communication patterns based on

physical features and social clues

- that provide an augmented do-

main for collaborative learning.

The electronic implementation of

collaborative learning often results

in the development of a virtual

classroom, whereby tools such as

electronic bulletin boards, mail,

grade books, quizzes and lectures

are used to provide feedback,

distribute material and develop a

learning community similar to a

traditional classroom.

The general effectiveness of

collaborative learning in traditional

classrooms is supported by decades

of research (e.g. McKeackie, 1980;

Palloff & Pratt, 1999), while recent

studies (McConnell, 1994; Campos, Laferriere & Hara-

sim, 2001) point to Online Collaborative Learning (OCL)

as an effective learning method within electronic envi-

ronments. Thus, e-learning platforms are increasingly

adapting a pedagogical approach of OCL that is based

on the theoretical underpinnings of constructivism

(critical thinking skills) and collaboratism.

Constructivism argues knowledge is created by

searching for complexity and ambiguity, looking for

and making connections among aspects of a situation

and speculation (King, 1994). So, when learners are ex-

posed to new information, each learner evaluates and

analyses it, sees the relationships between the new

information and his/her existing knowledge and makes

inferences and judgments for new knowledge (Kafai

& Resnick, 1996). In other words, to enhance learn-

ing, students should think critically, have the ability of

analyzing situations, search for evidence and seek links

between a particular situation and their prior knowl-

edge and experience (Sigala, 2002). In such learning

environments, instructors should act as facilitators,

while students should actively participate in the learn-

ing process and control their learning pace.

Collaborative learning evolved from the work

of psychologists (e.g. Johnson & Johnson, 1975) and

involves social (interpersonal) processes by which

a small group of students work together to com-

plete a task designed to promote learning. Thus,

collaborative learning involves the creation and

interpretation of communications among persons/

groups who might have different understandings

and opinions (Sigala, 2002), which in turn enhance

learning by allowing individuals to exercise, verify,

solidify, and improve their mental models. Dillenbourg

& Schneider (1995) identified three collaborative

learning mechanisms directly affecting cognitive

processes. First is conflict/disagreement because

it forces learners to seek information and find a

solution. Moreover, internalization of interactions with

more knowledgeable peers, explanations from more

advanced peers as well as self-explanations (self-

explanation effect) can also enhance learners’ learning

processes. In collaborative learning, group processes

are a part of the individual learning activity—individual

and collective activities are mutually dependent on

each other. This is because the learner actively con-

structs knowledge by formulating ideas into words,

and these ideas are built upon through reactions and

responses of peers. In other words, individual learn-

ing is a result of group processes

and so, learning is not only active

but also interactive. Thus, col-

laborativism may also be seen as

a variation of constructivism that

stresses the cooperative efforts

among students and instructors

in the learning process (Sigala,

2002).

Collaborative and constructiv-

ism learning environments were

found to significantly foster and

enhance the development of com-

munication, interpersonal, social,

cognitive and metacognitive skills

and competencies (Palloff & Pratt,

1999; McConnell, 1994; Campos et

al, 2001). In the context of tour-

ism and hospitality education,

such skills and competencies are

crucially important, as the nature

of the industry requires graduates

to work, communicate and col-

laborate (online and offline) within

multi-cultural, multi-lingual as

well as geographically dispersed

environments (Sigala, 2002; Cho et

al, 2002). Thus, the applicability

and benefits of online construc-

tivism and collaborative learning

approaches for tourism and hos-

pitality education become clearly

apparent.

Factors Determining e-Learning Effectiveness

Evaluation reports of distance

education and computer mediated

learning experiences usually not

only include variables regarding

learner achievement, but also

variables concerning the teaching

methods and learning environ-

ment. Indeed, Webster & Hackley

(1997) remarked that although

students’ performance (measured

by their marks) represents a key

aspect of teaching effectiveness,

they highlighted that the follow-

Dow

nloa

ded

by [

Uni

vers

ity o

f N

orth

Tex

as]

at 1

5:28

26

Nov

embe

r 20

14


ing dimensions also capture the

concept of effectiveness: student

participation and involvement;

cognitive engagement; technol-

ogy self-efficacy (i.e. ones belief

on his capacity to interact with

a given technology); perceived

usefulness of the technology;

and the relative advantages/

disadvantages of online delivery.

Bernard Rubalcava & Pierre (2000)

also argued that OCL should be

evaluated on its three dimensions

namely commitment, coordination

and communication by measuring

variables such as group cohesion

and productivity, use of resources

and level of communication.

Moreover, because OCL

requires learners to be active par-

ticipants of their own learning,

other learner’s variables should also

be considered. However, previous

studies investigating the learning

quality/effectiveness have gener-

ally used students’ grades, attitude

surveys and observational data

(Porras-Hernadez, 2000). There are

some studies that go beyond ex-

amining general attitudes towards

technology by including affec-

tive aspects such as confidence in

learning abilities and expectations

(Brosnan, 1998; Schlechter, 1990).

More recent studies evaluating

OCL are also focusing on specific

abilities and attitudes needed in

e-learning by including student’s

perceptions of themselves (Bernard

et al, 2000; Martinez, 1999) rather

than only looking at students’ per-

ceptions of technology, tasks and

their ability with technology. Por-

ras-Hernadez (2000) also stressed

the need to include learners’ capa-

bility for educational achievement

in general, while Hammond’s (2000)

findings revealed that two learn-

ers’ factors determine learning

effectiveness namely cognitive aspects (e.g. previous

experience in mediated education and computer skills)

and affective variables (e.g. expectations, self-efficacy

for self-regulated learning, perceptions of instructors

and their efforts, feelings of anxiety and success).

Leidner & Jarvenpaa (1993) also found that stu-

dents’ frustration stemming from technical problems

and inadequate technical and /or lack of immediate

feedback and ambiguous instruction could also impact

e-learning. Overall, Dillon & Gunawardena (1995)

summarized the factors determining e-learning ef-

fectiveness in three categories namely technology,

instructor and student factors.

The following technology issues were found to af-

fect e-learning effectiveness (Dillon & Gunawardena,

1995; Laurel, 1990; Blattner & Dannenberg, 1992): a)

medium’s reliability, quality and richness; b) capability

for both synchronous and asynchronous communica-

tion; c) quality of interface, e.g. factors regarding:

ease of use, navigation, screen design, information

presentation, aesthetics and overall functionality

(Martinez, 1999); d) the perceived richness of the

used technology. According to the rich medium theory

(Laurel, 1990), a rich medium is one that allows for

both synchronous and asynchronous communication as

well as supports a variety of didactical elements (text,

graphic, audio and video).

However, it is not the technology but rather its

instructional implementation that determines learn-

ing effectiveness. Thus, the role of the instructor

becomes central and instrumental in the effectiveness

of e-learning. Actually, the following instructor fac-

tors can influence learning outcomes (Salmon, 2002):

attitude towards technology, control of technology

and teaching style, e.g. the way he/she facilitates/

mediates OCL learning platforms. In particular, the

instructors’ facilitating and mediating capabilities and

roles are crucially important because unless these

are effectively achieved, serious problems may arise.

For example, an online conference may turn into a

monologue of lecture type material to which very few

responses are made or to a disorganized mountain of

information that is confusing and overwhelming for

the participants. To avoid such situations, Harasim

(2000) stressed that instructors should adapt an on-

line instruction-teaching paradigm that is away from

the traditional lecture format as well as become

active e-moderators. Actually, instructors must as-

sume three crucial tasks namely

contextualizing, monitoring and

meta-communication functions

(Feenberg, 1989), which Salmon

(2002) summarized into the con-

cept of weaving. The first two

functions aim to compensate for

the absence of physical cues found

in traditional classrooms, while

meta functions aim to resolve

problems in communication that

are addressed in classrooms by

body language and to summarize

the state of a discussion to provide

the sense of accomplishment and

direction. Coppola, Hiltz & Rot-

ter (2002) also highlighted that

in becoming “virtual” lecturers,

instructors need to assume a cogni-

tive role that is related to mental

processes of learning, information

storage and thinking, an affective

role related to influencing the re-

lationships between students, the

instructor and the virtual classroom

as well as a managerial role dealing

with class/course management and

student monitoring.

Finally, students’ factors de-

termining e-learning effectiveness

include (Porras-Hernadez, 2000;

Slate, Manuel & Brinson, 2002):

prior experience with technology;

country of origin and native tongue;

education skills and self-discipline;

perceptions of the self and self-

regulatory processes. The latter

can crucially determine students’

participation and learning effec-

tiveness in VLE, since e-learning

emphasizes and requires learners’

ability and responsibility of their

own learning. Hammond (2000) also

found that students’ perceptions on

the electronic medium significantly

affected their participation in OCL.

Online discussions have four ma-

jor characteristics: messages are

permanent; messages are public;

Dow

nloa

ded

by [

Uni

vers

ity o

f N

orth

Tex

as]

at 1

5:28

26

Nov

embe

r 20

14


mance, direction of discussions,

argument construction and infor-

mation search. Overall, e-learning

was used for complementing

class-based instruction by making

it more constructivist and socially

participative, rather than replacing

the current instructivist and behav-

iouristic educational model.

Research Aim, Methodology and Measurement of Constructs

The study aimed to investigate

the factors determining e-learn-

ing effectiveness from a students’

perspective. A structured question-

naire was developed and sent to

all students (293) participating in

the researcher’s VLE by an e-mail

attachment. Overall, 281 responses

were gathered. The high response

rate (95.9%) was achieved because

of the professional contact of the

researcher with the students, a fol-

low up that provided 151 additional

responses as well as learners’ assur-

ance regarding data confidentiality.

The first part of the question-

naire gathered data regarding

learners’ native language, gender,

previous experience with e-learn-

ing and learners’ level and type of

use of the VLE’s features (Table 1).

For investigating students’ use of

e-mail/chat discussions, McKenzie

& Murphy’s (2000) model for ana-

lyzing students’ online interactions

was used. Their model is grounded

in a cognitive and collaborative

view of learning and so, it can

identify the level of skills and the

engagement in knowledge co-con-

struction with peers from learners’

communication. Hammond’s (2000)

measurement scale was also used

for measuring students’ percep-

tions towards online forums (Table

2). E-learning effectiveness and

communication is asynchronous;

and messages can be edited before

sending. Depending on the way

students perceive these attributes,

students’ participation on online

forums varies considerably. For

example, the permanency of mes-

sages may encourage learners to

contribute as they can easily access

and refer to past debates. However,

this can also discourage communi-

cation, as writers know that their

texts are open for scrutiny and that

they cannot easily retract anything

they would write.

Development of the examined e-learning environments

Primary data for investigating

the factors determining the e-learn-

ing effectiveness were collected

from students participating in Virtual

Learning Environments (VLE) that the

lecturer/researcher developed to

support and enhance the classroom-

based instruction of three modules.

VLE were argued as effective tools

to enhance classroom-based teach-

ing because of three major reasons.

First, classes were very large (around

100 students per class) to enable and

foster dialogue/interaction among

students. Resources (staff) and time

requirements (students had differ-

ent timetables as well as working

part-time) constrained the ability

to organize tutorials with smaller

groups of students. Finally, one

module involved teaching overseas

during only one week, meaning that

the lecturer could not organize addi-

tional classroom seminars during the

semester. So, the VLE aimed to:

• Allow students to exchange

ideas among themselves and

with the lecturer asynchronously

(through e-mail) and synchro-

nously (e.g. chat room sessions).

• Create a data centre to store teaching and

learning material of the modules in a secure en-

vironment (lecture notes/presentations, working

papers/reports, bookmarks). This allowed material

to be updated and accessed at any time.

• Allow students to become more familiar with In-

ternet tools and their potential.

To achieve these, the Yahoo! service (http://

groups.yahoo.com/) was used for creating and mod-

erating students’ virtual communities that had the

following features:

• a message area; group members can receive/send

e-mails through their e-mails, send and access/re-

trieve any message sent to the group by using the

Webmail.

• file area; an area whereby teaching and learning

material can be stored, accessed/downloaded by

any group member. A directory structure was de-

veloped to make navigation/search easier.

• bookmark area; bookmarks of relevant material,

e-journals, associations, research centers etc,

were stored in a specific location, as this area was

being updated more regularly.

• other features including chat sessions, polls, mem-

bers’ area (profile, interests) and calendar were

available and students were motivated to use

them.

Yahoo! groups were used because of their

familiarity/popularity among students and the previous

evidence of their good performance in designing VLE

(e.g. Joia, 2002). To foster online discussions and use

of the VLE, students were asked to accomplish an on-

line group task (Salmon, 2002). The task was linked to

the modules’ assessment (to motivate participation),

while its process was weekly monitored/moderated

by both the students and the lecturer through the

provision of summary reports and formative feedback

respectively. Specifically, students were divided into

pair of groups each one debating a contrasting argu-

ment to the other group. Every week one student per

group summarized and commented the online discus-

sions of his/her group and posted his/her file to the

pairing group. The following week, online discussions

aimed to address the comments and arguments of the

opponent team. The instructor took active participa-

tion in discussions by reading summaries and providing

overall feedback to groups regarding their perfor-

Dow

nloa

ded

by [

Uni

vers

ity o

f N

orth

Tex

as]

at 1

5:28

26

Nov

embe

r 20

14


the other factors affecting it were

measured as follows. Students per-

ceived performance of e-learning

effectiveness, including students’

participation, technology self-ef-

ficacy, perceived usefulness of

technology and advantages of e-

learning, was measured by 9 items,

whose sum gave the effectiveness

index (Table 3). These 9 items was

adopted from Reeves & Harmon’s

(1993) model. Reeves & Harmon’s

(1993) constructs (using a five point

Likert scale, ranging from highly

agree to highly disagree) were

also adopted for measuring the

technology factors and instructor

characteristics. Specifically, eleven

items captured the reliability,

quality and medium richness of

the technology platform (Table 4),

whose sum built the technology index. Twelve items

captured instructors’ teaching style, facilitating role

and control of technology (Table 4), whose sum pro-

vided the instructor index. Bandura’s (1989) 13 items

scale was adopted for measuring students’ self-control

and self-regulatory abilities, whose sum built the stu-

dent index (Table 4).

Analysis of the findingsConcerning the demographic profile of the re-

spondents, 40% were male, 74% did not have English

as their mother tongue, while only 22% had a previous

experience with e-learning.

Type and Level of Use of VLEStudents were asked to indicate their usage of the

VLE’s features in a five point Likert scale ranging from

not at all to very often (Table 1). The file and book-

mark area as well as the e-mail represent the most

heavily used VLE’s features, while the calendar, polls,

chat sessions and the members’ area are the least used

features. It can be argued that the members’ area was

Table 1

Use of VLE and e-mail/chat forums (% of students)

Not Not Some- Very at all much times Often often

1 2 3 4 5Use of VLE File area 1 7 18 43 31 Message area 10 28 35 19 8 Bookmark area 8 22 21 28 21 Chat sessions 36 18 34 7 5 Polls 41 46 9 4 0 e-mail 0 2 24 19 55 Members’ area 41 38 19 2 0Use of e-mail/chat forums Suggest and/or get advice on learning sources/ information 5 13 36 41 5 Provide examples to explain concepts/theories 14 19 27 37 3 Compare information/concepts and identify areas of disagreement 28 23 21 26 2 Critically evaluate an argument/theory and/or provide own ideas 41 18 34 5 2 Negotiating/co-constructing of meaning and implications of concepts 21 34 29 14 2 Testing and modification of proposed argument 11 54 15 12 8 Post personal messages 79 9 10 1 1 Introductory posts for getting to know peers 22 19 41 7 11 Technical and other information 23 24 26 19 8

not used a lot since it did not pro-

vide great help to students, as they

knew and could meet each other

in the classroom. However, find-

ings overall suggest that students

made more use of features that

were consistent with a tutor-di-

rected learning style that requires

the self-study of pre-identified

material. The use of innovative

features such as chat sessions and

polls was limited, unless otherwise

indicated by the tutor (e-mail fo-

rums). In other words, it seemed

that students were transferring

online their previous, tutor-di-

rected learning styles. Specifically,

students’ previous experience

in classrooms, whereby one-way

communication and simple memo-

rization of learning material may

Dow

nloa

ded

by [

Uni

vers

ity o

f N

orth

Tex

as]

at 1

5:28

26

Nov

embe

r 20

14


have dominated in the expense of

two-way discussions, might have

affected students’ perceptions of

the usefulness and so, use of online

discussions.

Students’ focus on traditional

ways of learning is also reflected

on the type and quality of their

e-mail/chat discussions (Table 1).

Indeed, most students sent e-

mails mainly for providing and/or

getting advice regarding sources

of material and on providing

examples to explain concepts. E-mails illustrating

higher order critical thinking and analytical skills

(e.g. compare information / concepts and identify

areas of disagreement, negotiating /co-constructing

of meaning and implications of concepts, testing

and modification of proposed argument) were sent

less frequently. In other words, students used e-mail

discussions for complementing and supporting their

traditional ways of learning (self-directed study)

rather than for engaging in collaborative and con-

structivist online learning interactions that they

could in turn internalize for enhancing their own

learning.

However, data regarding stu-

dents’ perceptions towards online

forums revealed that the former

may have affected their participa-

tion in online/e-mail discussions.

Indeed, as the mean values of

negative statements are higher

than the mean values of positive

statements regarding perceptions

for online communication (Table

2), it is evident that students held

negative perceptions regarding

the features and affordability of

online forums to enhance and sup-

Table 2

Students’ Perceptions for Online Forums

Native Non-Native Overall English English Sample Speakers Speakers t-Test (281) (74) (207) M SD M SD M SD tWriter cannot interact with other people while composing a text, lacks visual clues 4.21 1.23 4.19 1.25 4.23 1.23 0.1076

Composing text is a discipline 3.92 0.95 3.41 0.81 4.02 0.94 0.0032*

Reticence and fear for going public 3.41 0.89 3.19 0.84 4.10 0.93 0.0011*

Texts cannot be easily undone 3.19 0.85 3.01 0.83 3.42 0.87 0.0932

Can address all members of the group quickly 3.24 0.81 3.11 0.81 3.31 0.82 0.1004

Allow reflection on other people’s comments 3.09 0.84 2.91 0.81 3.12 0.85 0.0851

Members can read and contribute their own texts when they like 2.56 0.93 2.63 0.82 2.48 0.98 0.1248

Can easily manipulate language & writing to clarify and structure complex ideas 1.85 1.21 2.02 1.09 1.82 1.25 0.1178

Negative perceptions are indicated with bold font

(1 – 5 Likert scale, from strongly disagree to strongly agree)

* significant at �=0.05

Dow

nloa

ded

by [

Uni

vers

ity o

f N

orth

Tex

as]

at 1

5:28

26

Nov

embe

r 20

14


port their learning. So, students’

perceptions that “online discus-

sions lack visual clues” and that

“the composition of messages is

a discipline” as well as students’

perceived fear of having their ideas

in public exposure coupled with

the fact that comments cannot be

changed after posted, might have

inhibited them from participating

in online discussions. Specifically, a

t-test (t=0.0032, p=0.05) revealed

that learners that did not have

English as their native language

more significantly agreed that

composing a text is a discipline.

Non-native English speaking students were also found

to have a significantly greater negative perceived fear

for putting their messages in public exposure (t=0.001,

p=0.05). These findings suggest that skills in English

language might have also affected students’ participa-

tion in online forums.


The previous findings can also be explained by

examining the items capturing students’ perceptions

for their e-learning experience and performance

(Table 3). It is evident that students did not fully

perceive the value of online discussions in the

learning process. In particular, a great majority of

students strongly agreed that yahoo! groups provided

them the opportunity to gather

and share a substantial volume

of learning material (traditional

method of learning), while a

significantly smaller proportion

of students claimed to perceive

and agree on the value of online

interactions for learning (i.e. the

collaborativism and constructivism

learning approaches of the e-learn-

ing). However, as the average

e-learning effectiveness score (the

average of the sums of all items

of each student) was 36.09 (maxi-

mum score=45), it can be claimed

that overall learners had relatively

Table 3

Students’ Perceived Performance of e-Learning Effectiveness (% of students)

Strongly Strongly

agree disagree 5 4 3 2 1

I could easily use the technology 76 12 8 3 1

I made adequate use of yahoo! Groups features 65 26 5 3 1

Reading classmates contributions helped me better understand how theories could be applied to real life 23 43 12 15 7

I appreciate that I could contribute to the discussion 27 34 20 16 3

I appreciate that my colleagues had the opportunity to comment on my thinking 25 36 27 10 2

I feel that colleagues’ feedback on my comments helped me understand the issues involved 11 37 36 14 2

Making comments on my peers’ contribution helped me understand how theories can be applied. 11 37 43 6 3

I found instructor intervention in discussions useful 18 39 27 12 4

Yahoo! Groups offered opportunities to gather and share a greatamount of material 44 20 32 3 1

Dow

nloa

ded

by [

Uni

vers

ity o

f N

orth

Tex

as]

at 1

5:28

26

Nov

embe

r 20

14


Table 4


Technology factors Factor 1 Factor 2 Factor 3Easy access to Website 0.613 0.501 0.525Did not experience problems while browsing 0.826 0.511 0.402Browsing speed was satisfactory 0.838 0.592 0.394Overall, the website was easy to use 0.762 0.563 0.438Website was easy to navigate 0.591 0.682 0.499Information was well structured/presented 0.502 0.842 0.503Website contained useful features 0.583 0.773 0.482I found the screen design pleasant 0.534 0.745 0.500Website gave me direct/timely feedback 0.492 0.601 0.783I could interact with peers through the Web 0.499 0.502 0.778I could easily contact the instructor 0.404 0.403 0.784Percentage of variance explained 43.20 15.30 9.69Cumulative percentage of variance explained 43.20 58.50 68.19Cronbach alpha 0.88 0.84 0.73

Instructor’s characteristics Factor 1 Factor 2 Factor 3Instructor’s online teaching material held my interest 0.832 0.581 0.400Instructor was friendly towards individual students 0.902 0.442 0.392Instructor had a genuine interest in students 0.823 0.601 0.411Students felt welcome in seeking advice/help 0.852 0.482 0.423We were invited to ask questions / receive answers 0.871 0.402 0.428Instructor handled the Web technology effectively 0.593 0.719 0.512Instructor was helpful in solving technical problems 0.624 0.864 0.409Instructor explained how to use the website 0.591 0.835 0.402Instructor solicit comments 0.464 0.442 0.687Instructor summarized state of discussion 0.492 0.501 0.616Instructor corrected discussions 0.572 0.482 0.732We were encouraged to participate in discussions 0.463 0.401 0.741Percentage of variance explained 28.44 23.50 17.12Cumulative percentage of variance explained 28.44 51.94 69.06Cronbach alpha 0.87 0.84 0.70

Students’ self-regulatory Factor 1 Factor 2 Factor 3Meet deadlines for work assignments 0.911 0.553 0.525Arrange a place to study without distractions 0.813 0.502 0.492Organise your studies’ work 0.849 0.493 0.401Take notes of lecture/tutorial instruction 0.822 0.473 0.573Concentrate on studies’ subjects 0.738 0.492 0.539Use the library to get information for module 0.502 0.825 0.495Use other references to prepare for module 0.448 0.623 0.404Understand information presented in books 0.602 0.776 0.462Understand information in lectures and textbooks 0.482 0.819 0.438Participate in lectures/tutorials’ discussions 0.531 0.592 0.679Consult other educators to prepare for module 0.502 0.421 0.611Participate in study groups 0.499 0.403 0.647Ask for academic advice (in person or by email) 0.418 0.512 0.680Percentage of variance explained 45.01 12.9 10.9Cumulative percentage of variance explained 45.01 57.91 68.81Cronbach alpha 0.84 0.85 0.75

Dow

nloa

ded

by [

Uni

vers

ity o

f N

orth

Tex

as]

at 1

5:28

26

Nov

embe

r 20

14


positive perceptions towards the

effectiveness of e-learning.

A set of 11 items using a five

point Likert scale measured the

technology factors and a technol-

ogy score was subsequently built

by adding up the value of these

items. The relationship between

technology factors and learning

effectiveness was examined by

conducting a two-tailed Pearson

correlation. A correlation coeffi-

cient of 0.681 (p=0.001) revealed a

significant relation between tech-

nology factors and performance of

e-learning effectiveness. A factor

analysis was further undertaken

for identifying the particular tech-

nology factors. The factors were

extracted with a principal compo-

nent analysis and the factor matrix

was rotated using the varimax

method. Three factors were found

to explain the 68.19% of the vari-

ance (Table 4) with a high level of

reliability (Cronbach alpha > 0.7):

1) easy access and navigation; 2)

interface; and 3) interaction both

with peers and instructors.

By adding the value of the 12

items measuring the instructor

factors, an instructor score was

calculated and then correlated

with the e-learning effective-

ness core for investigating their

relation. A two-tailed Pearson

correlation coefficient of 0.609

(p=0.001) between the instruc-

tor index and the effectiveness

index revealed a significant rela-

tion between these two variables.

A factor analysis with the 12

items capturing instructor fac-

tors revealed that three factors

(with a high level of reliability,

Cronbach alpha >0.7) explained

the 69.06% of the variance (Table

4): 1) instructor attitudes to-

wards learners; 2) instructor

technical competence; and 3) instructor efforts for

facilitating/mediating forums and interactions.

A two-tailed Pearson correlation test between

the student score (the sum of the value of the 13

items capturing self-control and –regulatory students’

abilities) and e-learning effectiveness examined the

relation between the two variables. A significant cor-

relation between the student score and e-learning

effectiveness (P=0.702, p=0.001) revealed that stu-

dents’ e-learning experience is significantly related

with students’ factors. A factor analysis was also used

for identifying the underlying factors in students’ abili-

ties. The latter revealed that three factors (with a high

reliability level, Cronbach alpha >0.7) explained the

68.81% of the variance (Table 4): 1) students’ ability

of controlling learning processes; 2) students’ effort in

searching and understanding learning material; and 3)

students’ ability to participate in OCL processes.

Discussion and implications of the findings The study aimed at investigating the factors

affecting e-learning effectiveness from a students’ per-

spective. E-learning effectiveness included students’

participation, technology self-efficacy, perceived

usefulness of technology and advantages of e-learn-

ing. Findings provided evidence of the impact of three

factors on e-learning effectiveness, whose implications

should be considered and addressed if technological

and pedagogical successful e-learning environments

are to be designed and implemented. Suggestions for

achieving superior students’ participation and full ex-

ploitation of e-learning tools are also provided in the

following.

First, the development of effective e-learning

platforms should make good use of Internet’s capabili-

ties and features. Internet tools should be developed

and used for providing enhanced access, navigation

and interface design as well as level of user-interac-

tion. Unless students can easily understand as well

as effectively directed to what they are required to

do and where to find appropriate material, their use

of learning tools and so, their learning experience/

benefits are going to be minimal. There is also a need

to ensure that online material is more than digital

photocopies of current texts/lecture notes and that it

truly takes advantage of the potential of the Internet

(e.g. interactivity, personalization, use of multimedia

resources, hypertext).

Concerning the impact of

instructor factors on e-learning

effectiveness, research findings

indicated that three instructor

characteristics could significantly

affect e-learning: instructor atti-

tudes towards students; instructor

technical competence; and

instructor efforts for facilitating/

mediating interactions and discus-

sions. This suggests a need for a

shift in the academic role from

the “intellect-on-stage and men-

tor” towards a learning catalyst.

In other words, instructors’ ability

to catalyze students so that they

can discover their own learn-

ing is very vital in e-learning.

However, the latter is in contrast

with recent findings (Sigala &

Christou, 2002) revealing that

a great majority of tourism and

hospitality educators are mainly

using the Internet as a mechanism

for distributing and/or gather-

ing information rather than as

a tool for continuous pedagogi-

cal innovation and improvement

of their teaching and learning

practices. To allow educators to

further develop their pedagogical

use of the Internet and to im-

migrate their instruction modes

from traditional lecture-oriented

to learners-oriented learning en-

vironments, institutions should:

overcome obstacles regarding

educators’ awareness of tech-

nological capabilities and online

pedagogical practices; provide

more opportunities and resources

for developing educators’ techno-

logical competencies and support.

Such efforts would increase edu-

cators’ ability and willingness to

develop and integrate in their

current instruction pedagogically

effective e-learning models.

Dow

nloa

ded

by [

Uni

vers

ity o

f N

orth

Tex

as]

at 1

5:28

26

Nov

embe

r 20

14


Findings also indicated stu-

dents’ self-regulatory educational

abilities, and specifically their

capability in participating in col-

laborative learning processes,

impacted on their e-learning ef-

fectiveness. Moreover, students’

usage patterns of VLE’s features

and e-mail/chat discussions sug-

gested that students transferred

their previous and traditional learn-

ing style on the VLE. Specifically, it

was found that students used VLE’s

features to support and comple-

ment their self-study processes

rather than enhancing their OCL.

Students’ use of online forums

also reflected a lack of ability and

willingness to engage in higher

order critical thinking and ana-

lytical activities. Students’ online

learning style and use of VLE can

in some way be explained by the

fact that a great majority of stu-

dents more strongly perceived the

negative rather than the positive

aspects of online forums. The fact

that several students did not have

English as their mother language

was also found to have an impact

on students’ perceptions towards

online discussions and so, students’

participation in them. Moreover,

students’ focus on traditional

learning styles and their lack of

experience on how to achieve and

engage in critical thinking and ana-

lytical skills may also explain their

limited exploitation of the VLE’s

collaborative features.

To overcome such problems, it

is suggested that the motivational

and behavioral preparation of

online learners is desirable, espe-

cially when the learners possess

low confidence and/or skill levels.

Particularly, skills and behaviors

that are essential for effective col-

laboration should be identified in

advance as well as subsequently taught to learners and

then reinforced as the process proceeds. To achieve

that, the type and structure of online learning activi-

ties should be designed in such a way so that simple

preparatory assignments would precede more complex

assignments. This allows students to get acquainted

with their peers and practice on online conferencing

and team working, before difficult e-tasks are intro-

duced. Scaffolding is also found to be an effective

method that helps students to immigrate from tutor-

directed learning styles (Salmon, 2002). In scaffolding,

instructors design and give students a priori the steps/

activities of the learning process in which the latter

need to engage. For example, for each type of team

communication desired, a corresponding subject cat-

egory of e-mail can be established. Thus, tutors could

use scaffolding to: guide students in online discussions

and help them achieve their tasks (overcome students’

inexperience); conduct e-mail analysis by subject cat-

egories to diagnose any problematic group/situation;

provide appropriate formative monitoring and feed-

back; give summative student evaluation based on the

quality of his/her contribution.

The creation of a good social climate and sense

of belonging in a learning community might also help

students enhance their participation in OCL, because

community bonding can significantly reduce students’

perceived fear of online discussions. Indeed, the cre-

ation of a learners’ community is crucially essential.

Learning collaboratively is basically a social process

that must be encouraged and nurtured and this can

be achieved by several methods such as: making the

environment as democratic as possible to encour-

age the involvement of everyone; establish a “failure

safe space”, e.g. by providing a restricted space that

is unavailable to the instructor, for students to con-

verse amongst themselves; arranging for at least one

face-to-face group encounter for participants to get

acquainted or organizing a videoconference; providing

adequate levels of tutor support, initially, that gradu-

ally gives way to increased responsibility on the part of

students; encourage learners to set priorities regarding

reading and reflecting on messages; establish a well-

organize structure to facilitate efficient interaction.

Conclusions and Recommendations E-learning is currently one of the major issues af-

fecting the majority of educational institutions. This

study aimed to investigate the factors determining

learning effectiveness in VLE from a

students’ perspective. To that end,

a literature review analyzing the

aims of e-learning and identifying

the factors determining e-learn-

ing effective development and

implementation was undertaken.

The significance and impact of

specific factors were tested and

empirically examined by gathering

data from students participating in

VLE developed by using the Yahoo!

group services. Research findings

revealed that three factors clus-

tered within three categories were

found to affect e-learning: tech-

nology, instructors’ and students’

factors. These should be carefully

considered for the development,

successful implementation and con-

tinuous improvement of e-learning

platforms. Thus, based on the find-

ings, specific practical implications

and suggestions were also provided.

Overall, good and fully ex-

ploitation of Internet’s tools

and features (i.e. network/

collaborative, interactive, multi-

media and hypertext capabilities)

is required in order to enhance

the learning experience and ef-

fectiveness of VLE. The Internet

should not be used as an electronic

page turning device of traditional

learning material and activities.

Moreover, to fully benefit from

e-learning, both students and

educators should immigrate from

e-learning models that simply re-

implement existing and traditional

practices by simply making them

available electronically. As e-learn-

ing is redefining how skills and

knowledge are acquired, educators

need to re-examine how e-learning

is occurred as well as how to fa-

cilitate, participate and foster OCL

and how to direct and support stu-

dents for becoming self-disciplined

Dow

nloa

ded

by [

Uni

vers

ity o

f N

orth

Tex

as]

at 1

5:28

26

Nov

embe

r 20

14


and active members of online com-

munities.

However, the study is limited

to the fact that learning effec-

tiveness was measured only by

students’ perceptions. Future

research should aim to assess

whether the communication, so-

cial, interpersonal and technology

skills that e-learning is argued to

enhance are actually achieved

as well as to investigate the fac-

tors that may moderate, impact,

facilitate their achievement. The

replication of the study in differ-

ent VLE, contextual and learner

environments could also further

refine, develop and enhance cur-

rent findings. Of particular interest

and importance is the identification

of any specific factors relating to

learners’ cultural and/or learning

disabilities that could impact on

e-learning and the investigation of

effective ways for addressing the

former.

References Bandura, A. (1989). Multidimensional

Scales of Perceived Self Efficacy. Working Paper, Stanford University, USA.

Bernard, R., Rubalcava, B., & Pierre, D. (2000). Collaborative Online Distance Learning: Issues for Future Practice and Research. Distance Education, 21, 260-277.

Blattner, M., & Dannenberg R. (1992). Multimedia Interface Design. New York: ACM.

Brosnan, M. (1998). The Impact of Com-puter Anxiety and Self-efficacy Upon Performance. Journal of Computer Assisted Learning, 14, 223 – 234.

Campos, M., Laferriere, T., & Hara-sim, L. (2001). The Post-secondary Networked Classroom; Renewal of Teaching Practices and Social In-teraction. Journal of asynchronous learning networks 5 (2), 36- 52.

Cho, W., Schmelzer, C.D., & McMahon, P.S. (2002). Preparing Hospitality Managers for the 21st Century: The Merging of Just-in-time Education,

Critical Thinking, and Collaborative Learning. Journal of Hospitality & Tourism Research, 26 (1), 23-37.

Clements, C., Buergermeister, J., Holland, J., & Monteiro, P. (2001). Creating Virtual Learning Community. Journal of Teaching in Travel and Tourism, 1 (2/3), 73 – 89.

Coppola, N.W., Hiltz, S.R., & Rotter, N.G. (2002). Becoming a Virtual Professor: Pedagogical Roles and Asynchronous Learning Networks. Journal of Management Information Systems, 18 (4), 169 – 189.

Dillenbourg, P., & Schneider, D. (1995). Collaborative Learning and the Internet. http://tecfa.unige.ch/tecfa/research/CMC/colla/iccai95_1.html [Accessed 2001, 18 July]

Dillon, L., & Gunawardena, C. (1995). Evaluation of Telecom-munications-based Distance Education. Open University report. Milton Keynes: Open University.

Feenberg, A. (1989). On the Theory and Practice of Computer Conferencing. In R. Mason and A. Kaye (eds.) Mindweave: communication, computers and distance education, pp. 23 – 47. Oxford: Pergamon Press.

Hammond, M. (2000). Communication in Online Forums: Value and Constraints. Computers & Education, 35, 251-262.

Harasim, L. (2000) Shift Happens: Online Education as a New Paradigm in Learning. The Internet and Higher Education, 3 (1/2), 41-61.

Johnson, D., & Johnson, R. (1975). Learning Together and Alone: Cooperation, Competition, and Individualization. Englewood Cliffs: Prentice Hall

Joia, L.A. (2002). Analyzing a Web-based e-Commerce Learn-ing Community: A Case Study in Brazil. Internet Research: Electronic Networking Applications and Policy, 12, 305 – 317.

Kafai, Y., & Resnick, M. (1996). Constructionism in Practice: Designing, Thinking and Learning in a Digital World. Hills-dale: Lawrence Erlbaum

King, A. (1994). Inquiry as a Tool in Critical Thinking. in D. Halpern, Changing Classrooms, San Francisco: Jossey-Bass.

Laurel, B. (1990). The Art of Human Computer Interface De-sign. Reading, MA: Addison Wesley.

Martinez, M. (1999). Research Design, Models, and Methodolo-gies for Examining How Individuals Successfully Learn on the Web. Special Research in Technical Communication, 46, 470-487.

McConnell, P. (1994). Implementing Computer Supported Co-operative Learning. London: Kogan Page.

McKeackie, W. (1980). Learning, Cognition and College Teach-ing. San Francisco: Jossey-Bass.

McKenzie, W., & Murphy, D. (2000). “I hope this goes somewhere”: Evaluation of an online discussion group. Aus-tralian Journal of Educational Technology, 16, 239 – 257.

Palloff, R., & Pratt, K. (1999). Building Learning Communities in Cyberspace: Effective Strategies for the Online Class-room. San Francisco: Jossey Bass.

Porras-Hernadez, H. (2000). Student Variables in the Evalu-ation of Mediated Learning. Distance Education, 21, 385-403.

Reeves, T., & Harmon, S. (1993). Evaluation of Processes for Hypermedia. Educational Research Association, Atlanta,

April 14.

Rice, R.E. (1984). Evaluating New Me-dia. In J. Johnston, Evaluating the New Technologies. San Francisco: Jossey-Bass.

Salmon, G. (2002). E-tivities. The Key to Active Online Learning. London: Kogan Page.

Schlechter, T.M. (1990). The Relative In-structional Efficiency of Small Group Computer-based Training. Journal of Education Computing Research, 6, 329-341.

Sigala, M. (2002). The Evolution of In-ternet Pedagogy: Benefits for Tourism and Hospitality Education. Electronic Journal of Hospitality, Leisure, Sport & Tourism Education, 1 (2), 29

Sigala, M., & Christou, E. (2003). En-hancing and Complementing the Instruction of Tourism and Hospitality Courses Through the Use of Online Educational Tools. Journal of Hospi-tality & Tourism Education, 15(1), 6 – 16

Slate, J., Manuel, M., & Brinson, K. (2002). The Digital Divide: Hispanic College Students’ Views of Education-al Uses of the Internet. Assessment & Evaluation in Higher Education, 27 (1), 75 – 93.

Webster, J., & Hackley, P. (1997). Teaching Effectiveness in Technology Mediated Learning. Academy of Man-agement Journal, 40, 1282-1309.

Dow

nloa

ded

by [

Uni

vers

ity o

f N

orth

Tex

as]

at 1

5:28

26

Nov

embe

r 20

14

investigating the factors determining e-learning effectiveness in tourism and hospitality education

Documents