cross cultural analysis of the use and perceptions of web based learning systems

8/3/2019 Cross Cultural Analysis of the Use and Perceptions of Web Based Learning Systems

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Cross cultural analysis of the use and perceptions of web Based learning systems

Jorge Arenas-Gaitn a,1, Patricio E. Ramrez-Correa b,*, F. Javier Rondn-Catalua a,1

a University of Seville, Dep. Administracin de Empresas y Marketing, Av. Ramon y Cajal 1, 41018 Sevilla, Spainb Universidad Catolica del Norte, Escuela de Ingeniera Comercial, Larrondo 1281, 1781421 Coquimbo, Chile

a r t i c l e i n f o

Article history:

Received 16 June 2010

Received in revised form

4 September 2010

Accepted 27 March 2011

Keywords:

Cross-cultural projects

Computer-mediated communication

Post-secondary education

Distance education and telelearning

a b s t r a c t

The main objective of this paper is to examine cultural differences and technology acceptances from

students of two universities, one is from a European country: Spain, and the other is in Latin America:

Chile. Both of them provide their students with e-learning platforms. The technology acceptance model

(TAM) and Hofstedes cultural dimensions are the tools used to measure the acceptance and use of

web-based learning platforms and cultural diversity of respondents, respectively. In summary, we can

affirm that the sample of tertiary Spanish and Chilean students are culturally different with regard to

some of Hofstedes dimensions, but their behavior of acceptance of e-learning technology globally

matches according to the TAM model. This study provides relevant implications for on-line courses

managers who have tertiary students from different nationalities.

2011 Elsevier Ltd. All rights reserved.

1. Introduction

Rather than replacing traditional classroom teaching, e-learning complements it and thousands of on-line courses are being offered

by universities and colleges world-wide in this way. E-Learning, also known as Web-based learning is defined as an Internet-enabled

learning process (Gunasekaran, Mcneil, & Shaul, 2002).It has been crucial to make learning methods become more portable and flex-

ible (Zhang & Nunamaker, 2003). And these characteristics are even more important in modern higher education. E-learning adoption by

university students is growing at a world-wide level. However, courses completely on-line (without traditional classroom teaching) are

less than 5%, and the number of students enrolled in at least a course with relevant on-line contents is ranged between 30 and 50%

(OECD, 2005).

However, the diverse cultural origins of tertiary students may derive from different perceptions and evaluations of similar e-learning

systems. But, given a common purpose and using technology that may minimize cultural differences, is it possible for universities to

overcome some of the cultural barriers to tertiary e-learning? What is the influence of culture on how university students learn and on the

technology used to deliver learning solutions in an efficient and effective manner?

Designing and implementing e-learning systems in a multi-culture environment is a challenge for tertiary learning institutions. In an

increasingly globalized world the presence of students from different nationalities enrolled in the same courses is actually a fact.

Furthermore, the growing competence of colleges and universities trying to attract new students will negatively affect the reputation ofthose educational institutions do not address these multi-cultural issues properly. Another important matter is related to the impact to the

learning effectiveness of multi-cultural students of the design and implementation of e-learning systems. The implications of this study

point out all these ideas and will help tertiary educational institutions managers to face theses challenges in a more efficient way.

As Nathan (2008) points out technical and hard scientific information such as engineering, anatomy, physiology, mathematics, etc., travel

well for the simple reason that location and cultural context do not change the basic content of the information and knowledge being

presented. But in social sciences the standardization of e-learning could be more difficult because of cultural aspects. Some authors (Raza &

Murad, 2008) think that e-learning sets up a new global social opportunity to transcend regional, racialand national prejudices. According to

these ideas, a strong controversy about the influence of cultural differences in e-learning exists. The importance of considering cultural

differences of students that use Web-based learning platforms is an incipient research stream. The significance of this topic deals with the

* Corresponding author. Tel.: 56 51 209 844; fax: 56 51 209 707.

E-mail addresses: [email protected] (J. Arenas-Gaitn), [email protected] (P.E. Ramrez-Correa), [email protected] (F. Javier Rondn-Catalua).1 Tel.: 34 95 455 4427; fax: 34 95 455 6989.

Contents lists available at ScienceDirect

Computers & Education

j o u r n a l h o m e p a g e : w w w . e l s e v i e r . c o m / l o c a t e / c o m p e d u

0360-1315/$ see front matter 2011 Elsevier Ltd. All rights reserved.

doi:10.1016/j.compedu.2011.03.016

Computers & Education 57 (2011) 17621774


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necessity of knowing if e-learning platforms should be accepted, used and perceived in the same manner by all students or national

differences should have to be taken into account.

This work derives from the confluence of three current research lines. The first, as we argued above, raise with the use of e-learning

platforms in higher education from universities around the world. Some recent studies above this topic are Ngai, Poon, and Chan (2007);

Blazic, Law, and Arh (2007); Raza, Kausar, and Paul (2007); and Raza and Murad (2008); Ebner, Lienhardt, Rohs, and Meyer (2010); Law, Lee,

and Yu (2010); Hourigan and Murray (2010), Paechter, Maier, and Macher (2010). In the second research stream, the theoretical frameworkthat provides technology acceptance model is used as a tool to study adoption and use of e-learning platforms by university students. There

is an important number of studies about this subject, such as Saad, Nebebe, and Tan (2007), Van Raaij and Schepers (2008), Zhang, Zhao,

and Tan (2008), Chang and Tung (2008), Halawi and McCarthy (2008), Liaw (2008), Liu, Liao, and Pratt (2009) and Park (2009). In the third

line of research, the key element that differentiates our work is to add to the two previous views the adoption of a cross-cultural approach.

This approach examines similarities and differences caused by national cultures in the adoption of e-learning technology by college

students. Although there are studies that have addressed e-learning from a cross cultural approach (Phuong-Mai, Terlouw, and Pilot (2005),

Teng (2007), Hannon andD Netto (2007), and Elenurm (2008), there is clearly a lackof jobs that combine the three proposed lines (Grandon,

Alshare, & Kwun, 2005).

This paper is structured in the following way. Firstly, the research objectives and literature review are presented. Secondly, a model is

proposed. Thirdly, analysis and results of the study are exposed. Finally, the discussion and conclusions are explained.

2. Research objective

The main objective of this paper is to examine cultural differences and technology acceptances from students of two universities, one

from Spain and the other from Chile. Both of them provide their students e-learning platforms. The TAM model (extended with some TAM2

and TAM3 constructs) and Hofstedes cultural dimensions (including the new ones published in 2008) are the tools used to measure the

acceptance and use of web-based learning platforms and cultural diversity of respondents, respectively. In order to achieve this main

objective two research questions have to be answered. The first is to contrast if cultural differences between the Spanish and Chilean

samples exist. Spain is a European country member of the European Union and Chile is a Latin-American country associated to Mercosur. To

do this, the sample was divided into two groups: Spaniards and Chileans. First of all, Hofstede s dimensions were calculated for each sub-

sample. Then an Independent-Samples T Test procedure was applied. The second secondary aim is to compare the same TAM model in both

samples trying to study the acceptation of e-learning platforms in both universities. The Partial Least Squares (PLS) path model approach to

Structural Equation Modeling (SEM) has been applied to test this second objective.

3. Literature Review

In this section three parts are developed. Firstly, a brief literature review about e-learning in higher education is provided. Secondly,

Hofstedes cultural dimensions are explained and analyzed. Andfinally, TAM models andtheirapplications to e-learning are exposed briefly.

3.1. E-Learning in higher education

E-learning is becoming an increasingly important part of higher education in many different areas of knowledge. According to

Tavangarian, Leypold, Nlting, and Rser (2004) E-learning comprises all forms of electronically supported learning and teaching, which are

procedural in character and aim to effect the construction of knowledge with reference to individual experience, practice and knowledge of

the learner. Information and communication systems, whether networked or not, serve as specific media to implement thelearning process.

The first courses over the Web started to emerge in 1995 and there has been a rapid expansion of on-line learning since then. One of the

main reasons for the widespread use of on-line learning in many institutions is that most students now have access to the Internet. The

University of British Columbia, in Vancouver, Canada, offered itsfirst credit courses delivered entirelyover the Internet to distance education

students in 1996. The same year Murray Goldberg developed a software package called WebCT designed to enable Web-based courses to be

offered over the Internet (Bates, 2005).

In order to support e-learning, various Web-based learning systems have been developed for colleges and universities. Such as the Web

Course Homepage System (WebCH), Blackboard Learning System, the System for Multimedia Integrated Learning (Smile) and Web Course

Tools (WebCT), are some of the latest waves of technology-based pedagogical tools (Ngai et al., 2007). However, Web-based learning musttake into consideration that education has activated a shift from the teaching paradigm to the learning paradigm. As a result, students are

becoming more independent from the teacher. Unfortunately, much of the development of Web-based learning is carried out without a true

understanding of issues that are proper to Web-based learning ( Hadjerrouit, 2006). In general, Internet-based activities have been incor-

porated into regular face-to-face classes as an added resource, without reducing classroom time, but in many cases teachers have reduced

the number of face-to-face classes (Bates, 2005).

For lecturers and students, the implications of e-learning are extensive. Increasingly universities must provide quality and flexibility to

meet the diverse needs of students this will inevitably involve tailoring courses to suit differing educational needs and aspirations.

Another implication of virtual learning is the increase of international competition for students by many universities, of distance methods of

delivery and of new communication tools. These are very useful mechanisms that facilitate the internationalization of higher education

(ONeill, Singh, & ODonoghue, 2004). For this reason there are an increasing number of students of different countries and cultures enrolled

in the same courses. This fact brings into consideration the issue of cultural differences in accepting and reacting to new teaching tech-

nologies. Major cultural differences have been found in students with regard to traditions of learning and teaching. In many countries, there

is a strong tradition of the authoritarian role of teachers and the transmission of information from teachers to students. Thus, teachers need

to be aware of language, cultural or epistemological differences of their students, especially in distance classes (Bates, 2005). However, nodifferences between students from culturally and nearby countries from Central Europe have been found by Blazic et al. (2007) with regard

to the assessment of an e-learning portal. Furthermore, e-learning reflects the new dynamic response to the needs of a knowledge society

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and implies freedom and equality to access knowledge beyond cultural and social boundaries (Raza & Murad, 2008). Even Raza et al. (2007)

manifest that e-learning can help in creating globally shared information structure which accepts the valid expression of information

differences amongst people. Therefore, it is necessary to investigate this topic in more culturally different countries.

In this researchtwo differente-learning platforms are analyzed: WebCT (used by theUniversity of Seville in Spain) that is a commercially

available system, and Claroline (used by the Catholic University of the North in Chile). WebCT Campus Edition provides a Virtual Course

Environment with a complete set of tools for course preparation, delivery, and management. Instructors have all the tools they need toprepare course materials and manage their day-to-day teaching tasks. Claroline is an Open Source E-Learning and E-Working platform

allowing teachers to build on-line courses and to manage learning and collaborative activities on the web. Translated into 35 languages,

Claroline has a large world-wide users and developers community.

3.2. Hofstedes cultural dimensions

Cross-cultural studies have been developing in last decades. Essentially, these articles deal with studying differences in individual

behavior caused by national culture. The core of these studies is culture. However, culture is difficult to define. Based on various definitions

of culture, four main characteristics have emerged (Hoecklin, 1995). First, it is a shared system of meaning, a guide that people of a same

group followin order to be able to understand each others events, behaviorsand actions. Second, there is no culture absolute, that is, culture

is a relative notion: theway one nationalculture views theworld is relative to how another culture views theworld. Third,culture is learned,

rather than inherited. It is derived from an individuals social environment. Lastly, culture is a collective rather than an individual

phenomenon. Within one culture there can be large variations in individual values and behaviors.

This research line hasbeen developedfrom Hofstedes (1980) article.In this work, Hofstede presented the results of his extensive study ofnational cultures. Based on data from 117,000 IBM employees from 40 different countries, he extracted four dimensions of culture, indi-

vidualism vs. collectivism, masculinity vs. femininity, power distance, and uncertainty avoidance. Subsequently, and in collaboration with

Bond and a group of Asian scholars, a fifth dimension, long term orientation was added to the framework (Hofstede & Bond, 1988). Recently,

in collaboration with other authors, Hofstede has proposed an extension of his previous works adding two new dimensions: monumen-

talism vs. self-effacement and indulgence vs. restraint. A brief description of the seven cultural dimensions is provided according to

Hofstede, Hofstede, Minkov, and Vinken (2008) (Table 1):

In addition to the measurement scales proposed by Hofstede, the use of values of each dimension obtained by a large number of nations

has been the most common method of comparing national cultures used in academic research. These dimensions were published in

Hofstede & Bonds (1988) work. Based on this conceptual framework, cross-cultural analysis has been applied in marketing and manage-

ment for a long time (Magnusson, Wilson, Zdravkovic, Zhou, & Westjohn, 2006), and recently some of it has been applied to technological

(Lippert & Volkmar, 2007) and learning scopes (Elenurm, 2008; Shipper, Hoffman, & Rotondo, 2007).

For some time, many articles have been showing that cross-cultural variables affect learning. Economides (2008) made a good review of

this type of work. Sanchez and Gunawardena (1998) found that Hispanic adult learners showed a strong preference for collaborative over

competitive activities. Computer conferencing would be appropriate since it supports group activities (discussion on a topic, problemsolving, role playing, etc.). Vogel et al. (2000) found that working together in collaborative teams with students from another study

background and country offers much educational value and is highly appreciated. However, Hong Kong students experienced a global team

feeling and trust towards their classmates while Dutch students did not. Gunawardena, Nolla, Wilson, Lopez, Ramirez & Megchun (2001)

observed that there were differences in perception of on-line group process and development between participants in Mexico and the

US. There were significant differences in perception for the Norming and Performing stages of group development. The groups also differed

Table 1

Hofstedes Cultural Dimensions.

Dimension Definition

Power Distance Is defined as the extent to which the less powerful members of institutions and organizations

within a society expect and accept that power is distributed unequally.

Individualism vs. Collectivism Individualism stands for a society in which the ties between individuals are loose: people

are expected to look after themselves and their immediate family only. Collectivism stands

for a society in which people from birth onwards are integrated into strong, cohesive in groups,which continue to protect them throughout their lifetime in exchange for unquestioning loyalty

Masculinity vs. Femininity Masculinity stands for a society in which social gender roles are clearly distinct: men are supposed

to be assertive, tough, and focused on material success; women are supposed to be more modest,

tender, and concerned with quality of life. Femininity stands for a society in which social gender roles

overlap: both men and women are supposed to be modest, tender, and concerned with quality of life

Uncertainty Avoidance Is defined as the extent to which the members of institutions and organizations within a society feel

threatened by uncertain, unknown, ambiguous, or unstructured situations.

Long Term Orientation vs. Short

Term Orientation

Long Term Orientation stands for a society which fosters virtues oriented towards future rewards,

in particular adaptation, perseverance and thrift. Short Term Orientation stands for a society which

fosters virtues related to the past and present, in particular respect for tradition, preservation of face,

and fulfilling social obligations

Indulgence vs. Restraint Indulgence stands for a society which allows relatively free gratification of some desires and feelings,

especially those that have to do with leisure, merrymaking with friends, spending, consumption and sex.

Its opposite pole, Restraint, stands for a society which controls such gratifications, and where people feel

less able to enjoy their lives.

Monumentalism vs. Self-Effacement Monumentalism stands for a society which rewards people who are, metaphorically speaking, like monuments:

proud and unchangeable. Its opposite pole, Self-Effacement, stands for a society which rewards humility andflexibility. The Monumentalism Index will probably be negatively correlated with the Long Term Orientation

Index, but it includes aspects not covered by the latter.

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in their perception of collectivism, low power distance, femininity, and high-context communication. Ramburuth and McCormick (2001)

found that Australian and Asian international students differed significantly in group learning, supporting the notion of Asian students

being more collaborative.

Chang and Lim (2002) found that culturally heterogeneous (mixed individualistic and collectivist) groups had higher reasoning levels

than homogeneous collectivistic groups but lower than individualistic groups. Park (2002) investigated the learning styles of English

learners (Armenian, Hong Kong, Korean, Mexican, and Vietnamese) in Californian secondary schools. He found significant ethnic groupdifferences. Hong Kong, Mexican, and Vietnamese students preferred group learning while Armenian and Korean students did not. Kim and

Bonk (2002) found that Korean students were more social and contextually driven on-line while Finnish students were more group-focused.

The US and Finnish students spent much time sharing knowledge and resources. Korean students showed a higher level of social interaction

behaviors than Finnish or American students, whose social interaction behaviors were almost absent. Phuong-Mai et al. (2005) pointed out

that the collectivist mentality of the Confucian heritage culture strongly supports cooperation, guarantees group success and enables the

learners best performance in groups. However, not all forms of cooperative learning will surely succeed within a Confucian heritage culture

environment.

In a study to examine the knowledge transfer and collaboration in distributed teams, Sarker (2005) observed that members of indi-

vidualistic cultures (US students) transferred/shared more knowledge than those in collectivist cultures (Thai students). The communication

style preferred by cultures (high-context vs. low-context) may have a significant impact on who is viewed as a knowledge transferor within

a collaborative group. Thai students seemed to avoid extensive communication about new and difficult concepts with their remote

participants. The US students were complaining about the limited and somewhat ineffective communication received from the Thai team

members.

Teng (2007) found that the US students haddeveloped a better sense of community andcloser relationships with their classmates. It was

easier for them to make group decisions. They demonstrated more enjoyment in working in groups and showed greater satisfaction with

their group performances. They agreed more that they had participated in the group projects to the best of their abilities. Also, they felt that

they were more supported by their group members and had known their group members better through this project. On the other hand,

Taiwanese students preferred building relationships than working in teams. A divide in the sense of importance of task completion between

the two countries was observed.

Multi-cultural collaborative learning does not always lead to successful outcomes. In a case study on collaborative learning in distributed

US and Japanese teams, Agerup and Bsser (2004) mentioned that based on cultural differences the graduate students initiative to

collaborate gradually failed. Instead of a mutual engagement that led to knowledge creation, only the lower level of a web-based coordi-

nation was reached.

Furthermore, Anakwe, Kessler, and Christensen (1999) examined the impact of cultural differences on potential users receptivity

towards distance learning. Findings revealed that an individual s culture affects his or her overall attitude towards distance learning.

Specifically, individualists motives and communication patternsfit to distancelearning as a medium of instructionor communication, while

collectivists motives and communication patterns turn away from distance learning. Mercado, Parboteeah, and Zhao (2004) evaluate the

particular challenges of designing and delivering a web course for an international user group. They integrate the burgeoning literature on

on-line communication and distance education with Hofstedes (2001) taxonomy of national cultures. Hannon and DNetto (2007) found

that learners from different cultures respond differently to the organizational imperatives and arrangements which are built into on-line

learning technologies

Grandon et al. (2005) proposed a research model based on TAM to examine factors that influence students intentions to take on-line

courses. To validate the research model, data were collected from college students in the United States and South Korea. For American

students, convenience, quality, subjective norm, and perceived ease of use were significant predictors of students intention. Only quality

and subjective norms were significant factors impacting Korean students intentions.

Elenurm (2008) highlights factors supporting and inhibiting cross-cultural synergies between action learning and e-learning. Particu-

larly, Chinese students had greater difficulties adapting to the self-managing mode of teamwork than western European students. Power

distance helps to explain the normative and cultural need for a hierarchy-based leadership shaped by the Confucian tradition. At the same

time, Chinese students were however more systematic and workaholic in their efforts, if their role in the team was clearly specified, than

students from southern Europe. One explanation of this may be linked to Asian long term orientation, and uncertainty avoidance, in the

knowledge acquisition and transfer context, means that experts are eager to get exact formal descriptions of their tasks.

Nathan (2008) shows how cultural differences can have a practical impact on learning methodologies. In this context,the development of

global learning platforms based on technology and e-learning is a challenge. For example, WebCT can be used in different cultures andlanguages. The paper discussed a number of culturally-specific issues that need to be addressed in the design and development process of

building a global learning system.

Based on the findings and conclusions of the investigations mentioned above, it can be affirmed that cultural differences affect the

development of e-learning. According to Hofstede (1980), there are differences between cultural values of Chilean and Spanish citizens. In

this context, Contreras (2003) concluded that cultural differences among Chilean and Spaniards MBA students exist. Based in the previous

statement, we propose the following hypotheses:

H0a. There are statistically significant differences between the cultural values of the sample of Chilean and Spanish students.

H0b. There are statistically significant differences between Chilean and Spanish students in the relationships among the constructs of the

proposed model in higher education.

3.3. E-Learning & TAM models

Proposed by Fred Davis (Davis, 1989), TAM posits that individual behavior intention to use information technology is determined by the

perceived usefulness and perceived ease of use. Also, perceived ease of use is directly impacted by perceived usefulness. Since then, several



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revisions and expansions have developed the original model. The most popular developments have been TAM2 (Venkatesh & Davis, 2000)

and TAM3 (Venkatesh & Bala, 2008).

The literature presents several studies using TAM to assess users acceptance of e-learning technology. In most of these studies, the

TAM was extended using factors predictors or moderators, such as: subjective norms ( Grandon et al., 2005; Lee, Cho, Gay, Davidson, &

Ingraffea, 2003; Park, 2009; Van Raaij & Schepers, 2008; Yuen & Ma, 2008); computer self-efficacy (Chang & Tung, 2008; Grandon

et al., 2005; Hayashi, Chen, Ryan, & Wu, 2004; Ong & Lai, 2006; Ong, Lai, & Wang, 2004; Park, 2009; Yuen & Ma, 2008 ); perceivedplayfulness (Chen, Chen, Lin, & Yeh, 2007; Roca & Gagn, 2008; Zhang et al., 2008); cognitive absorption (Liu et al., 2009; Saade &

Bahli, 2005); system features (Chang & Tung, 2008; Chen et al., 2007; Liu et al., 2009; Park, 2009); computer anxiety (Van Raaij &

Schepers, 2008); gender (Ong & Lai, 2006); motivational factors (Park, Lee, & Cheong, 2007; Roca & Gagn, 2008); personal inno-

vativeness (Van Raaij & Schepers, 2008); technical support (Ngai et al., 2007); perceived credibility (Ong et al., 2004); and compat-

ibility (Chang & Tung, 2008). Venkatesh and Bala (2008) proposed job relevance (REL) and result demonstrability (RES) as predictors of

TAM in the general context of information systems. Nevertheless, we dont find in the literature a specific validation of these

propositions.

The TAM model has been used successfully in the context of e-learning (Saad et al., 2007). In particular, Halawi & McCarthy (2008)

suggested that students use e-learning environment (USE) if they perceive it is useful (PU) and easy to use (PEOU). Previously, Ngai et al.

(2007) indicated that the perceived ease of use (PEOU) and perceived usefulness (PU) are the main factors affecting the attitude of

university students to use e-learning (BI). Also, Hayashi et al. (2004) verified that the perceived usefulness (PU) directly affects students

intention to continue using e-learning (BI). Considering the importance of a replica in a culturally different sample from those already

explored, and based on these previous studies, the following hypotheses are proposed:

H1a. PU is positively related to BI in adopting e-learning in higher education in Chile.

H1b. PU is positively related to BI in adopting e-learning in higher education in Spain.

H2a. PEOU is positively related to PU in adopting e-learning in higher education in Chile.

H2b. PEOU is positively related to PU in adopting e-learning in higher education in Spain.

H3a. PEOU is positively related to BI in adopting e-learning in higher education in Chile.

H3b. PEOU is positively related to BI in adopting e-learning in higher education in Spain.

H4a. BI is positively related to USE in adopting e-learning in higher education in Chile.

H4b. BI is positively related to USE in adopting e-learning in higher education in Spain.

Venkatesh and Bala (2008) proposed that job relevance (REL) and result demonstrability (RES) are antecedents of perceived usefulness

(PU). On the other hand, the same authors suggested that perception of external control (PCE) is an antecedent of perception of ease of use

(PEOU). Considering the importance of a replica in a culturally different sample explored in Venkatesh and Bala (2008), particularly in an e-learning environment, the following hypotheses are proposed:

H5a. REL is positively related to PU in adopting e-learning in higher education in Chile.

H5b. REL is positively related to PU in adopting e-learning in higher education in Spain.

H6a. RES is positively related to PU in adopting e-learning in higher education in Chile.

H6b. RES is positively related to PU in adopting e-learning in higher education in Spain.

H7a. PCE is positively related to PEOU in adopting e-learning in higher education in Chile.

H7b. PCE is positively related to PEOU in adopting e-learning in higher education in Spain.

Fig. 1. Proposed model.



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4. Proposed model

According to the aforementioned hypotheses, as can be seen from Fig. 1, the proposed model hypothesizes that job relevance (REL) and

result demonstrability (RES) are underlying determinants of perceived usefulness (PU); perception of external control (PCE) is underlying

determinant of perceived ease of use (PEOU); PEOU is positively related to PU; Both PU and PEOU influence students behavioral intentions

(BI) to use the e-learning platform; while behavioral intentions, in turn, influence actual use of the system (USE). The model core proposes

that two constructs of beliefs (PU and PEOU) have indirect effects on actual use of the e-learning platform through the mediation of the

behavioral intentions to use e-learning systems. Furthermore, external variables including, REL, RES, and PCE have indirect effects on

behavioral intentions to use e-learning systems through the mediation of PU and PEOU.

5. Research method

5.1. Scales

The measurement scales applied have been widely tested in other investigations. Specifically, to measure the TAM constructs the scales

proposed by Venkatesh and Bala (2008) have been adapted. Use (USE) was operationalized by asking the respondents, On average, how

much time do you spend on Learn On-line each day? (In minutes) . Moreover, to measure the cultural dimensions, Values Survey Module

(VSM 08) proposed by Hofstede et al. (2008) is used. The VSM 08 is a 34-item questionnaire developed for comparing culturally influenced

values and sentiments of similar respondents from two or more countries, or sometimes regions within countries. It allows scores to be

computed on seven dimensions of national culture. Five of the dimensions measured are described extensively in the work of Geert Hof-

stede (Hofstede, 2001). They deal with key issues in national societies, known from social anthropology and cross-cultural research. These 5

dimensions have been used plentifully in many studies, showing no problems of reliability and validity. The other two dimensions are based

on the work of Michael Minkov (2007). Their authors advise that they are experimental but they expect these 2 new dimensions may reveal

aspects of national culture not yet covered in the Hofstede dimensions. Therefore, only the assessment model to measure constructs related

to TAM is performed. Appendix A presents the items for each construct. All items were measured on a 5-point Likert scale, except use that isa temporal measure (minutes per week).

5.2. Sample

The empirical research is based on a non-probabilistic and self-selection sampling method, therefore it is a convenience sample.

Specifically, the data was collected in Chile and Spain from a sample of on-line questionnaires from May 14, 2009 to July 15, 2009. The on-

Table 2

Hofstedes indices obtained.

Power Distance (*) Individualism vs.

Collectivism

Masculinity vs.

Femininity (*)

Uncertainty

Avoidance

Long Term Orientation

vs.Short Term Orientation

Indulgence Monumentalism (**)

Spain 56.04 45.35 63.44 48.23 50.67 53.1 47.61

Chile 52.98 46.54 66.04 48.87 50.90 54.18 52.86

** significant 95%.

* significant 90%.

Table 3

Results from the cross-loadings procedure by PLS for Spain.

Latent Variables

Indicators BI PCE PEOU PU REL RES USE

BI1 0.84 0.27 0.29 0.26 0.07 0.31 0.17

BI2 0.88 0.31 0.34 0.28 0.11 0.35 0.13BI3 0.80 0.34 0.39 0.30 0.18 0.35 0.12

PCE1 0.27 0.79 0.50 0.33 0.24 0.26 0.09

PCE2 0.28 0.85 0.53 0.31 0.12 0.20 0.08

PCE3 0.36 0.84 0.53 0.16 0.01 0.27 0.05

PEOU1 0.37 0.55 0.85 0.38 0.26 0.29 0.15

PEOU2 0.36 0.51 0.83 0.22 0.11 0.34 0.07

PEOU3 0.32 0.49 0.87 0.22 0.15 0.35 0.01

PEOU4 0.28 0.50 0.71 0.15 0.18 0.29 0.08

PU1 0.34 0.35 0.33 0.84 0.41 0.39 0.21

PU2 0.22 0.23 0.21 0.86 0.40 0.43 0.32

PU3 0.27 0.22 0.20 0.85 0.42 0.36 0.24

PU4 0.29 0.26 0.26 0.77 0.33 0.44 0.19

REL1 0.16 0.18 0.25 0.46 0.92 0.40 0.29

REL2 0.09 0.09 0.12 0.41 0.85 0.26 0.28

REL3 0.14 0.11 0.19 0.36 0.85 0.33 0.31

RES1 0.43 0.34 0.41 0.30 0.16 0.70 0.10

RES2 0.34 0.19 0.30 0.38 0.25 0.86 0.08RES3 0.23 0.20 0.25 0.45 0.44 0.80 0.23

USE 0.17 0.09 0.10 0.29 0.34 0.18 1.00



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line questionnaire wassent to students of the Catholic Universityof theNorth(Chile)and theUniversityof Seville (Spain) that usee-learning

platforms provided by these universities. The exclusion of invalid questionnaires due to duplications or empty fields provided a final sample

size of 352 students,193 from the Spanish University and 159 from the Chilean. 52.4% of the students are men and the rest women. 52.3% of

them are from Spain, 45.4% are from Chile and there are 2.3% of other nationalities: Peruvian, Mexican, Argentinean, from the USA, Polish,

Italian, Belgian and Bulgarian. 94.5% of respondents think they are members of the biggest ethnic group in their respective countries. Their

average age is 22, they have been studying for 4 years (on average) at the University, and 28% do tasks that impede them going to lectures.

The response ratios are 34.6% and 35.33% for the Spanish and Chilean samples, respectively.

5.3. Statistical tools

Various statistical tools have been applied in this research. At first, the sample was divided into two groups: Spain with 183 cases and

Chile with 159 cases. First of all, Hofstedes dimensions were calculated for each sub-sample. Then the Independent-Samples T Test

procedure was applied (using SPSS software) in orderto contrast if cultural differencesbetween the Spanish andChileansamples exist. After

that, the Partial Least Squares (PLS) path model approach to Structural Equation Modeling (SEM) was applied to test the research question

(Chin, 1998; Tenenhaus, Vinzi, Chatelin, & Lauro, 2005). Specifically, multi-group PLS analysis was used to compare between-group

differences. SmartPLS 2.0 M3 software (Ringle, Wende, & Will, 2005) was used for measurement models analysis and structural model

analysis.

6. Analysis and results

Hofstedes indices for both sub-samples are shown in Table 2. Significant differences exist in 3 of the 7 dimensions (Power Distance,

Masculinity vs. Femininity and Monumentalism) applying an independent sample ttest. This procedure compares means for two groups ofcases Spanish vs. Chilean students. SPSS was the software use for this analysis. These results partially support H0a.

A PLS path model is described by two models: (1) a measurement model relating the manifest variables (MVs) to their own latent

variables (LVs) and (2) a structural model relating some endogenous LVs to other LVs.

Table 4

Results from the cross-loadings procedure by PLS for Chile.

Latent Variables

Indicators BI PCE PEOU PU REL RES USE

BI1 0.81 0.47 0.30 0.39 0.42 0.34 0.25

BI2 0.90 0.41 0.41 0.44 0.36 0.45 0.24BI3 0.84 0.30 0.47 0.40 0.35 0.39 0.30

PCE1 0.40 0.82 0.49 0.38 0.20 0.13 0.21

PCE2 0.38 0.80 0.43 0.42 0.21 0.16 0.13

PCE3 0.35 0.86 0.59 0.40 0.23 0.12 0.08

PEOU1 0.49 0.58 0.89 0.57 0.35 0.26 0.22

PEOU2 0.37 0.57 0.87 0.48 0.24 0.15 0.15

PEOU3 0.41 0.51 0.89 0.45 0.31 0.26 0.22

PEOU4 0.30 0.42 0.78 0.31 0.16 0.18 0.17

PU1 0.40 0.46 0.43 0.88 0.26 0.42 0.20

PU2 0.43 0.44 0.48 0.87 0.26 0.30 0.28

PU3 0.36 0.37 0.46 0.87 0.23 0.31 0.19

PU4 0.49 0.41 0.51 0.86 0.34 0.34 0.19

REL1 0.43 0.24 0.33 0.29 0.89 0.50 0.15

REL2 0.36 0.22 0.23 0.27 0.89 0.37 0.06

REL3 0.39 0.24 0.29 0.29 0.90 0.40 0.08

RES1 0.44 0.14 0.23 0.26 0.46 0.85 0.06

RES2 0.43 0.18 0.26 0.34 0.32 0.88 0.13RES3 0.36 0.11 0.18 0.40 0.47 0.88 0.09

USE 0.31 0.16 0.22 0.24 0.11 0.11 1.00

Table 5

Cronbachs a coefficient, composite reliability and AVE.

Latent Variables Spain Chile

Cronbachs Alpha Composite Reliability AVE Cronbachs Alpha Composite Reliability AVE

BI 0.79 0.88 0.70 0.81 0.89 0.73

PCE 0.76 0.86 0.68 0.77 0.86 0.68

PEOU 0.83 0.89 0.67 0.88 0.92 0.74

PU 0.85 0.90 0.69 0.90 0.93 0.76

REL 0.85 0.91 0.77 0.87 0.92 0.80RES 0.70 0.83 0.62 0.84 0.90 0.76

USE 1.00 1.00 1.00 1.00 1.00 1.00



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6.1. Measurement models analysis

Prior to analyzing the structural model, the reliability and validity of the measurement models were measured. The individual reliability

was assessed examining the loads (l) or simple correlations of the measures or indicators with their respective LVs (indicators with

l ! 0.707 were accepted). Readers that want to know more about the measurement models analysis may see Barclay, Thompson, and

Higgins (1995) or Carmines and Zeller (1979). Tables 3 and 4 show the results from the cross-loading procedure for Spain and Chile

respectively.

The reliability of the LV indicates how rigorous observed variables are measuring the same LV, Cronbachs a coefficient was used as the

index of LV reliability (LV with a > 0.7 were accepted). In addition, composite reliability was calculated. The LV convergent validity was

assessed by examining the average variance extracted (AVE), see Fornell and Larcker (1981) (AVE > 0.5 were accepted). Table 5 shows

Cronbachs a coefficient, composite reliability and AVE by LVs.

The LV discriminate validity was tested by analyzing if the square root of the AVE from each LV is greater than the correlations with the

rest of the LVs (see Tables 6 and 7).

6.2. Structural model analysis

Following the validity and reliability of the measurement model being supported, relationships between constructs were tested. The

hypotheses were assessed by examining path coefficients (b) and their significance levels (b>0.2 were accepted). Bootstrapping with 50 0

sub-samples was performed to test the statistical significance of each path coefficient using t-tests. The variance explained (R-square) in the

endogenous LV and the regression coefficients significance (F-test) serve as indicators of the explanatory power of the model.

The results of PLS analyses for the Spanish model and the Chilean model are shown in Figs. 2 and 3 respectively.

The results support H1a, H1b, H2a, H2b, H3a, H3b, H4a, H4b, H5a, H5b, H6a, H6b, H7a and H7b.

In order to view themodelacross thetwo countries, a multi-group PLS analysiswas conducted by comparing differencesin coefficients of

the corresponding structural paths (Chin, 2000; Keil et al., 2000). Table 8 shows the results.The results do not support H0b.

7. Discussion

The power of globalization and the effect of technology result in the acceptance of e-learning throughout the education system

being inevitable (Clegg, Hudson, & Steel, 2003). Globalization is the characteristic that best defines the current environment. It is

a complex phenomenon which includes different topics. Two of them can be highlighted. Firstly, the increasing timing of technological

change in the field of communications and information technology (CIT) has made a real revolution. Secondly, due to the increase of

contacts between people, companies, institutions and other agents across the planet, globalization has entailed a process of homog-

enization of many aspects of life: education, consumption pattern, technology, culture. However, nowadays the existence of important

cultural differences is patent and this is partly caused by contact multiplication. Cross-cultural studies lay on these ideas. Despite this,

there is a lack of cross-cultural research that may help in explaining differences and similarities among students perceptions about on-

line instruction.

This work tries to contribute elements that help to reduce such a failure. In this sense, this study follows in the way started by Grandonet al. (2005) and followed by Roca, Chiu, and Martinez (2006) and Lee (2010). They pointed out the acceptance of technology by students

based on TAM. And, of course, this is a central element of e-learning. However, this work has two important differences to previous ones.

First,in order to analyze cultural differencesin therespondents behavior from the two samples,the scale proposed by Hofstede et al. (2008)

was applied. This aspect differs from previous work for two reasons: most research simply accepts the values published by Hofstede (1980)

Table 6

Latent Variable Correlations for Spain (diagonal elements are Square Roots of the AVE).

Latent Variables BI PCE PEOU PU REL RES USE

BI 0.84

PCE 0.37 0.82

PEOU 0.41 0.63 0.82

PU 0.34 0.32 0.31 0.83

REL 0.15 0.15 0.22 0.47 0.88

RES 0.40 0.29 0.39 0.49 0.38 0.79

USE 0.17 0.09 0.10 0.29 0.34 0.18 1.00

Table 7

Latent Variable Correlations for Chile (diagonal elements are Square Roots of the AVE).

Latent Variables BI PCE PEOU PU REL RES USE

BI 0.85

PCE 0.46 0.82

PEOU 0.47 0.62 0.86

PU 0.49 0.48 0.54 0.87

REL 0.44 0.26 0.32 0.32 0.89RES 0.46 0.16 0.25 0.39 0.48 0.87

USE 0.31 0.16 0.22 0.24 0.11 0.11 1.00



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and Hofstede & Bond (1998); and in the used scale appeared two new dimensions: Monumentalism vs. Self-Effacement and Indulgence

versus Restraint. This will ensure the measure of similarities and cultural differences between the samples under study. Andfinally, based on

TAM, this research area is wider than Grandon et al. (2005), Roca et al. (2006) and Lee (2010) because some new constructs from TAM2 and

TAM3 and Hofstede have been added.

Since the rapid growth of the incorporation of information technologies into learning environments, identifying critical factors related to

user acceptance of technology is an important issue (Yi & Hwang, 2003). However, most literature about e-learning has tended to be

descriptive and with a focus on technology rather than on theoretical contributions ( Nichols, 2003). In this context, different authors

indicate that user acceptance is the most important determinant of continuance intentions when using any technology, in particular, the

success of an e-learning environment depends to a considerable extent on acceptance and use of the students ( Roca & Gagn, 2008; Van

Raaij & Schepers, 2008). Although the procedure of identifying intentions of the students and understanding the factors that influence

the beliefs of students in relation to e-learning can help to create mechanisms for attracting more students to adopt this learning envi-

ronment (Grandon et al., 2005), littleresearch has been done to verify theprocess of how universitystudentsadopt anduse e-learning (Park,

2009).Results show cultural differences between the Spanish and Chilean students, however, both samples display a similar behavior with

regard to the acceptation of e-leaning platforms. What are the implications of these results for tertiary education managers ?

First, we note the similarities, but above all, cultural differences that appear between samples of Chilean and Spanish students. Both

Hispanic-speaking nationalities have some links based on a shared past. However, Spain is a European country andChile is an Americanone.

Both are two nations with significant differences; this is evident in cross-cultural studies. The obtained results are consistent with Hofstede,

who pointed out similarities and differences between the two nations. The outcomes are according to Contreras (2003), who found cultural

differences between Chilean and Spanish MBA students. In agreement to data, three of the seven Hofstede dimensions are significantly

different (Power Distance, Masculinity vs. Femininity and Monumentalism). It is quite logical not to find differences for Long Term

Orientation vs. Short Term Orientation because this is a dimension created to differentiate oriental cultures. With regard to Uncertainty

Fig. 2. Spain Model: R Square and Path Estimate (Standard Error) of PLS Analyses.

Fig. 3. Chile Model: R Square and Path Estimate (Standard Error) of PLS Analyses.



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Avoidance, Hofstede and Bond (1988) found similar values for Spain and Chile, showing people from these countries having a homogeneous

behavior in this topic. With reference to Indulgence versus Restraint, it is a new dimension that Hofstede et al. (2008) has incorporated

recently and there are no studies published about this construct. Nevertheless, the results obtained for Individualism vs. Collectivism are

surprising because in our study this dimensionis quite similar in both countries, but Hofstede and Bond (1988) found differences. According

to this, tertiary education institutions have to consider that cultural differences in students exist even between, a priori, similar cultures. We

can affirm free from doubt that students from more culturally different countries will show bigger differences. This implies that educational

institutions have to make an effort in order to adapt their learning systems to this ever-increasing fact if they want to possess a good

positioning in this market.At the same time, globalization is standardizing some behaviors, especially among the youth and with regard to new technologies. The

results of this work reveal that both samples of students do not show a different technology acceptation model of e-learning platforms. In

spite of the cultural differences, e-learning platforms are perceived similarly between both samples. This is an important fact for educational

institution managers because this part of learning can be standardized and do not need to be adapted.

8. Conclusions

The main objective of this paper is to examine cultural differences and technology acceptances from tertiary students from Spain and

Chile using e-learning platforms. In order to achieve this main objective two research questions have to be answered. The first is to

contrast if cultural differences between the Spanish and Chilean samples exist. According to our result, the first research question is

answered in this way: there are significant cultural differences between both samples of students according to Hofstedes dimensions. In

this sense, some reflections can be mentioned. On the one hand, one of the key differentiators of this work is the application of the new

Hofstede et al. (2008) scale to a sample of Spanish and Chileans tertiary students. Most of the research being conducted within the

framework of cross-cultural studies, just taking the scores obtained by Hofstede, or any of the other theoretical frameworks that exist:

Trompenaar (1993), Schwartz (1999) or GLOBE (House, Hanges, Javidan, Dorfman & Gupta, 2004). We have decided to adopt the proposal

of Hofstede et al. (2008) due to the appearance of two new dimensions (Monumentalism vs. Self-Effacement and Indulgence versus

Restraint); there are not available reference scores for these dimensions yet. In this sense, this paper presents one of the first contributions

presenting scores for these new dimensions in Spain and Chile. Moreover, as was gathered in the literature review, the cross-cultural

research takes mainly as a framework Anglo-Saxon countries (USA or UK) or Asian (China). There is a clear lack of research on other

geographical areas. Our work is a contribution in this issue, addressing the differences between European and other Latin American

nation, both of Hispanic speakers.

The second research question is to compare the same TAM model in both samples trying to study the acceptation of e-learning

platforms in both types of students. According to the results obtained from Smart PLS, there are some important noticeable

implications. The most important one is that there are no significant differences between the sample of Chilean and Spanish

students in every relationship of the TAM model. The general behavior in accepting e-learning platforms is quite similar for both

sub-samples. With regard to on-line learning, the effects of globalization on the homogenization of tertiary students are perhaps

stronger than in other types of population. University students use new technologies more frequently than other types of pop-ulations, and especially e-learning platforms because in many subjects they have to employ them compulsorily. However, the

strength of the relationships among constructs differs to some extent in both samples. In both groups the strongest link is between

perception of external control and perceived ease of use. But the second strongest one is between perceived ease of use and

perceived usefulness for Chileans and between perceived ease of use and behavioral intention for Spaniards. There are some other

differences in the relationships between both models but they are not statistically significant. According to the previous results and

answering the second research question, the acceptance of e-learning platforms for both samples of students is similar, in spite of

some minor differences.

In summary, we can affirm that the samples of tertiary Spanish and Chilean students are culturally different with regard to some of

Hofstedes dimensions, but their behavior of acceptance of e-learning technology matches globally according to the TAM model.

Finally, it is advisable to set out some limitations. Firstly, the model does not include all the TAM 3 variables. We recommend that

future research could include all of them. Also, it is necessary to validate and generalize the results in future investigations.

Furthermore, we must point out that the majority of individuals who participated were Spanish-speaking. The sample size did not

enable us to make generalizations, and it may not hold for different nationalities. To ensure the validity and reliability of the scale

proposed by Hofstede et al. (2008) samples of ten different countries at least are necessary, with fifty individuals each sub-sample. Wecould not reach this kind of samples. Similarly, it would be interesting to include Measurement Equivalence across test samples in

future research.

Table 8

Path comparison statistics between Spain and Chile.

Paths Spain Chile t-pooled Significance level

BI -> USE 0.1661 0.31 0.60484616 n.s.

PCE -> PEOU 0.6298 0.6159 0.04221354 n.s.

PEOU -> BI 0.3395 0.2856 0.13562768 n.s.

PEOU -> PU 0.11 0.463 1.16939694 n.s.

PU -> BI 0.2342 0.3309 0.24855508 n.s.

REL -> PU 0.3242 0.0488 0.98004029 n.s.

RES -> PU 0.3219 0.253 0.21502603 n.s.



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Appendix A; Items for constructs

TAM CONSTRUCTS

Itemsa

Behavioral Intentions(BI)

BI1 Assuming I had access to Learn On-line, I intend to use it

BI2 Given that I had access to Learn On-line, I predict that I would use it

BI3 I plan to use Learn On-line in the next months

Perception of External Control (PCE)

PCE1 I have control over using the system

PCE2 I have the resources necessary to use the system

PCE3 Given the resources, opport unit ies and knowledge it takes to use the system, it is e asy fo r me t o use the system

Perceived ease of use (PEOU)

PEOU1 My interaction with Learn On-line is clear and understandable

PEOU2 Interacting with Learn On-line does not require a lot of my mental effort

PEOU3 I find Learn On-line to be easy to use

PEOU4 I find it easy to get Learn On-line to do what I want it to do

Perceived Usefulness(PU)

PU1 Using Learn On-line improves my performance in my studies

PU2 Using Learn On-line in my studies increases my productivity

PU3 Using Learn On-line enhances my effectiveness in my studies

PU4 I find Learn On-line to be useful in my job/studies

Job Relevance (REL)

REL1 In my studies, usage of Learn On-line is important

REL2 In my studies, usage of Learn On-line is relevant

REL3 The use of Learn On-line is pertinent to my various study-related tasks

Result Demonstrability (RES)

RES1 I have no dif ficulty telling others about the results of using Learn On-line

RES2 I believe I could communicate to others the consequences of using Learn On-line

RES3 The results of using Learn On-line are apparent to me

USE

USE On average, how much time do you spend on Learn On-line each day? (In minutes)

a All items were measured on a 5-point Likert scale.

Cultural dimensions

Itemsa

In choosing an ideal job, how important would it be to you to.

m01 01. have suf ficient time for your personal or home life

m02 02. have a boss (direct superior) you can respect

m03 03. get recognition for good performance

m04 04. have security of employment

m05 05. have pleasant people to work with

m06 06. do work that is interesting

m07 07. be consulted by y our boss in decisions invo lving your work

m08 08. live in a desirable area

m09 09. have a job respected by your family and friends

m10 10. have chances for promotion

In your private life, how important is each of the following to you .

m11 11. keeping time free for fun

m12 12. moderation: having few desires

m13 13. being generous to other people

m14 14. modesty: looking small, not big

m15 15 . I f there is somethi ng exp en sive you real ly want to b uy b ut you d o not h ave enough money. always save before buying

m16 16. How often do you feel nervous or tense?

m17 17. Are you a happy person?

m18 18. Are you the same person at work (or at school if youre a student) and at home?

m19 19 . Do oth er p eopl e or ci rc umstan ces ever p revent you from d oi ng wha t you reall y want to?

m20 20. All in all, how would you de scribe yo ur state of health these days?

m21 21. How important is religion in your life ?

m22 22. How proud are you to be a citizen of your country?

m23 23. How often, in your experience, are subordinates afraid to contradict their boss (or students their teacher?)

To what extent do you agree or disagree with each of the following statements?

m24 24. One can be a good manager without having a precise answer to every question that a subordinate may raise about his or her work

m25 25. Persistent efforts are the surest way to results

m26 26. An organization structure in which certain subordinates have two bosses should be avoided at all cost

m27 27. A companys or organizations rules should not be broken - not even when the employee thinks breaking the

rule would be in the organizations best interest

m28 28. We should honour our heroes from the past

Cultural Dimension Index formulab

Individualism Index (IDV) IDV 35(m04 m01) 35(m09 m06) C(ic)



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Indulgence versus Restraint Index (IVR) IVR 35(m12 m11) 40(m19 m17) C(ir)

Long Term Orientation Index (LTO) LTO 40(m18 m15) 25(m28 m25) C(ls)

Masculinity Index (MAS) MAS 35(m05 m03) 35(m08 m10) C(mf)

Monumentalism Index (MON) MON 35(m14 m13) 25(m22 m21) C(mo)

Power Distance Index (PDI) PDI 35(m07 m02) 25(m23 m26) C(pd)

Uncertainty Avoidance Index (UAI) UAI 40(m20 - m16) 25(m24 m27) C(ua)

a All items were measured on a 5-point Likert scale.b C is a constant (positive or negative) that depends on the nature of the samples.



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cross cultural analysis of the use and perceptions of web based learning systems

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