E-learning: AOU Students’ Acceptance of Technology

M.M. Abbad1, D. Morris2, A. Al-Ayyoub3, J.M. Abbad4

1 Bahrain University/ Information System, Mnamah, Bahrain

2 Coventry University/ Higher Education Development, Coventry, UK

3 Dar Al-Uloom Colleges/ CEIT, Al-Riyadh, SA

4 Al al-Bayt University/ Finance and Banking, Mafraq, Jordan

Abstract

This research investigates and identifies some of the major factors affecting students’ adoption of an e-learning system at Arab Open University in Jordan. E-learning adoption is approached from the information systems acceptance point of view. An extended version of the Technology Acceptance Model (TAM) was developed to investigate the underlying factors that influence students’ decisions to use an e-learning system. The proposed model uses the actual use of an e-learning system. It is different from most of the prior TAM studies, which only used a single dependent variable (intention to use). The model was estimated using Structural Equation Modelling (SEM). The final models derived from this study indicated that beliefs of usefulness and ease of use partially mediate the relationship between external factors and intention to use and actual use of e-learning systems.

Index Terms- Adoption, E-learning, TAM, and SEM.

1.Introduction

The Internet has been growing at an exponential rate. Based on numbers published by [1], there are approximately 1.5 billion Internet users around the world and approximately 42 million Internet users in the Middle East. The growth rate of Internet users between 2000 and 2008 in the world was 290%. The Middle East witnessed an impressive Internet usage growth rate of 1,177% between 2000 and 2008. In addition, the World Wide Web (WWW) has become the modern tool of communication and information resource all over the world. Because of such rapid growth, the Internet and the web have transformed the business environment and the way people communicate. In higher education institutions, in order to keep up with these rapid changes in information technologies (IT), adoption of the Internet for learning has been increasing. For example, the Open University (OU) has become the UK’s largest university with over 200,000 students [2]. This appears to be due, in part, to the flexibility and portability of the delivery of web-based learning.

Many institutions of higher education adopt web-based learning systems for their e-learning courses. However, there is a lack of empirical examination of the adoption of web-based learning systems [3]. Successful adoption requires a solid understanding of user acceptance processes and how to entice students to accept these technologies [4]. Much research has addressed the antecedents of technology use but the overwhelming majority of the studies have focused on users in developed countries[5]. Developing regions of the world have much to gain from the Internet and IT in general but have received relatively little research attention [6] even though culture may influence technology use [7].

Jordan is witnessing rapid developments in information technology. It has convenient telecommunication facilities among neighboring countries and it applies the latest technologies in Internet services. The total number of Internetusers increased from 127,300 in 2000 to 796,900 in 2007 and the penetration rate grew by 526% during this period [1].

The vision of HM King Abdullah II that “Jordan will become an IT hub for the region” [8] has been a rallying call to government ministries and agencies, private sector associations and companies, non-governmental bodies and individuals within the society to pull together to realise His Majesty’s vision for the future benefit of all citizens. In addition, the King expressed the country's aspiration to become a regional e-learning model. This is not just for Jordan, said the King “If we are successful here, we'll be doing it for the rest of the Middle East” [9].

The Arab Open University, (AOU) was founded by Prince Talal bin AbdulAziz under the umbrella of the AGFUND (Arab Gulf Program for United Nations Development Organizations) and is headquartered in Kuwait, but one of its first branches was founded in Jordan in 2002.

The problem of measuring and finding the ‘right’ factors [10] that determine computer usage has inspired many researchers in the management information system (MIS) community during the past two decades. For example, the Technology Acceptance Model (TAM) of Davis [11] has set the basis for future research in information and computer technology adoption and use.

  1. Technology Acceptance Model (TAM)

TAM is an intention-based model that was developed specifically for explaining and predicting user acceptance of computer technology. Although the TAM initially focused on system usage in the workplace, researchers have employed the model to help understand website usage [12,13]. The TAM model [11] is one of the most widely used models for information technology (IT) adoption [14,15,16]. In addition, this model has been used as a theoretical basis for many empirical studies and accumulated a great deal of support [17,18,19,20,21]. Additionally, technology acceptance has been applied to the domain of e-learning [22].

Ref. [19] argued TAM has more empirical evidence in explaining technology acceptance, and previous research suggested it could be an appropriate model to examine a student’s acceptance of learning environment applications over a period of time [16]. Because of that, this study used TAM as the baseline model to determine the main factors and the relationships between these factors in predicting a student’s acceptance of e-learning systems.

TAM, introduced by [23], is an adaptation of TRA specifically tailored for modelling user acceptance of information systems. According to TRA, beliefs influence attitudes, which lead to intentions, which then generate behaviour. TAM adopted this belief attitude-intention-behaviour relationship to model user acceptance of IT.

TAM model (Figure 1) posits that two particular beliefs, perceived usefulness (PU) and perceived ease of use (PEOU), are of the primary relevance for computer acceptance behaviours.

Figure 1: Technology Acceptance Model (TAM)

Perceived usefulness (PU) is defined as “the prospective probability that using a specific application system will increase his or her job performance within an organizational context” [23]. Perceived ease of use (PEOU) refers to “the degree to which the prospective user expects the target system to be free of effort” [23].

Perceived ease of use and perceived usefulness may not fully reflect the users’ intention to adopt IS, and researchers need to address how other factors affect usefulness, ease of use, and user acceptance [11]. However, these factors are likely to vary with the technology, target users, and context [13]. Ref. [24] stated that TAM provides a framework to investigate the effects of external factors on system usage.

  1. Theoretical Development

Similar to prior research on TAM [24,25], the “attitude” construct was removed to simplify the model. Figure 2 depicts the research model for the study, including the actual use of an e-learning system and the external factors. This is based on prior research, which suggested that user acceptance is determined by two key constructs: perceived usefulness and perceived ease of use. In addition, five external variables, subjective norms, Internet experience, system interactivity, self-efficacy, and technical support were integrated into TAM to adapt it for the empirical study of e-learning systems.

Figure 2: Research Model

  1. External Factors
  2. Subjective Norm (SN)

According to the TRA model, in addition to the individuals’ perceptions and beliefs, social influences may affect behaviour[26]. In Ref. [27], social influences were equivalent to subjective norms and referred to other people’s opinion, superior influence, and peer influence. Ref. [28] believed that in some cases people might use a system to comply with others’ mandates rather than their own feelings and beliefs.

Subjective norm has been found to play two separate and different roles: one as the antecedent of behavioural intention and the other as the antecedent of perceived usefulness. Empirical support for the relationship between social norms and behaviour can be found in many studies [20,29].

In the e-learning context, Ref. [30] suggested that SN influences the learner’s satisfaction with and motivation for e-learning. In addition, the SN was a significant prediction of students’ satisfaction [31]. Ref. [32] found that social factors enhanced students’ motivation and satisfaction. In this study, subjective norm refers to a student’s perception of opinions or suggestions of the significant referents concerning his or her acceptance of an e-learning system (LMS) at AOU.

SN has been empirically tested and has had a significant direct [27,33,34] or indirect effect [20] in predicting an individual’s intention to use computer technology.Recently Ref.[35] found that the effects of SN significantly influenced perceived usefulness.Thus, we hypothesized:

H1: Subjective norms will have a positive effect on perceived usefulness of the e-learning systems.

H2: Subjective norms will have a positive effect on the intention to use the e-learning systems.

4.2Internet Experience (IE)

Research studies suggest that prior experience is important in an individual’s acceptance of IT. For example, [36] found that prior experience is one of the factors explaining individual differences in technology acceptance research. Additionally, prior experience was found as strongly influencing intention to use and usage of a specific system through perceived ease of use [37] and through perceived usefulness [38]. Ref. [36] found that computer experience directly and indirectly influences microcomputer usage behaviour through perceived usefulness and perceived ease of use.

Ref. [39] suggested that a student’s course website use tended to be greater when the site was viewed as being useful and easy to use. Thus, as student experience with a technology increases, they perceive it to be easier to use and more useful, and therefore, are more likely to use it.

Based on evidence from prior TAM research, students’ experience with web-based learning technology was conceptualized as an exogenous (external) variable. In addition, to explain user beliefs concerning usefulness and ease of use toward LMS, prior experience on the Internet has to be considered. Thus, we hypothesized:

H3: Internet experience will have a positive effect on ease of use of the e-learning systems.

H4: Internet experience will have a positive effect on perceived usefulness of the e-learning systems.

4.3System Interactivity (SI)

Research suggests that system characteristics can influence the intention to use and usage behaviour of the system. For example, [28] proposed that system characteristics exhibit indirect effects on usage intentions or behaviours through their relationships with perceived usefulness and perceived ease of use.

Ref. [40] noted that the main advances in distance education would come from technology that allowed increased learner interaction. Two types of interaction would be provided by a web-based learning system: instructor-to-student and student-to-student interactions. Ref. [41] stated, “the key elements of learning processes are the interactions among students themselves, the interactions between faculty and students, and the collaboration in learning that results from these interactions”.

Ref. [42] stated that a web-based learning (WBL) environment should combine both synchronous and asynchronous communication to support various elements such as text, graphics, audio and video messages. Ref. [43] found that students’ grades are highly correlated with student’s interactivity. Because of that, system interactivity is expected to be one of the factors that may affect students’ adoption of e-learning systems. Therefore, we hypothesized:

H5: System interactivity will have a positive effect on ease of use of the e-learning systems.

H6: System interactivity will have a positive effect on perceived usefulness of the e-learning systems.

4.4Self-Efficacy (SE)

Self-efficacy is a belief in an individual’s capability to perform certain behaviours or it is one’s personal beliefs about his or her ability to perform certain tasks successfully [44,45]. Perceived self-efficacy refers to the beliefs in one’s capability to organize and execute the courses of action required to produce a given accomplishment or outcome and originates from various sources including performance accomplishments, vicarious experience, verbal persuasion, and psychological states. Self-efficacy was one of the important beliefs in the social learning theory [44,45]. Ref. [28] and [46] suggested that self-efficacy is an antecedent of perceived ease of use and object use ability. Ref. [47] also found that computer self-efficacy was a significant determinant of behavioural intention to use information technology. Similarly, [48] reported that computer self-efficacy was a significant determinant of behavioural intentions. Ref. [49] examined the affect of self-efficacy on the perceived ease of use factor using e-mail and Gopher. Their studies found that perception about a new system’s ease of use were anchored in a person’s computer self-efficacy. Ref. [50] concluded that self-efficacy is a major predictor of intention and behaviour after controlling for intention. In the e-learning context, self-efficacy is interpreted as one’s self-confidence in his or her ability to perform certain learning tasks using an e-learning system. For example, students with high sense of an educational self-efficacy believe that they can study using e-learning system. While, students with a low sense of educational self-efficacy believe they cannot study using an e-learning system. A student who has a strong sense of his or her capability in dealing with an e-learning system has a more positive perception of ease of use and usefulness and he or she is more willing to accept and use the system. A student’s self-efficacy affects her/his actual behaviour decision or intention toward the educational process as well as their specific educational activities.

H7: Self-efficacy will have a positive effect on ease of use of the e-learning systems.

H8: Self-efficacy will have a positive effect on perceived usefulness of the e-learning systems.

4.5Technical Support (TS)

Ref. [51] defined technical support as people assisting the users of computer hardware and software products, which can include hotlines, online support service, machine-readable support knowledge bases, faxes, automated telephone voice response systems, remote control software and other facilities. Technical support is one of the important factors in the acceptance of technology for teaching [52,53,54]and in user satisfaction [55]. High levels of organizational support, including management support and information center support, were thought to promote more favourable attitudes about the system among users and information specialists, and lead to greater success for personal computing systems [36]. Ref. [56] study founded that training and prior computer experiences had a significant impact on system use.

E-learning projects that were not successful in achieving their goals did not have access to technical advice and support [57,58]. If technical support is lacking, e-learning will not succeed [39]. Ref. [39] study showed that students indicated that they would register in future e-learning based courses assuring their positive attitude and support to e-learning technology and tools. In addition, technical support is the major contributor to the effectiveness of the web-based learning system.

Recently, [3] extended the TAM to include technical support as a precursor and investigated the role of the extended model in user acceptance of WebCT. The result showed that technical support has a significant direct effect on perceived ease of use and usefulness, while perceived ease of use and usefulness are the dominant factors affecting the attitude of students using WebCT. In addition, the results indicated the importance of perceived ease of use and perceived usefulness in mediating the relationship of technical support with attitude and WebCT usage. In this study, technical support is expected to be one such external factor affecting the acceptance of an e-learning system at AOU in Jordan.

H9: Technical support will have a positive effect on ease of use of the e-learning systems.

H10: Technical support will have a positive effect on perceived usefulness of the e-learning systems.

  1. TAM’s Factors

The TAM model posited the beliefs of perceived usefulness (PU) and perceived ease of use (PEOU) as the determinant factors for the intention to use IT. The IT usage intentions, in turn, directly influenced usages. The two variables (PU and PEOU) have been hypothesized to be fundamental factors of user acceptance of information technology. Therefore, we hypothesized:

H11: Perceived ease of use will have a positive effect on perceived usefulness of the e-learning systems.

H12: Perceived ease of use will have a positive effect on the intention to use the e-learning systems.

H13: Perceived usefulness will have a positive effect on the Intention to use the e-learning systems.

H14: Intention to use will have a positive effect on the actual use of e-learning systems.

  1. Methodology
  2. Measures

Given the existence of numerous published articles dealing with the variables in this study, prior literature represents an important source of content for measure development. The definitions of the variables, introduced in the previous sections were used as a guide for selecting which items from the literature to include in the initial pools. These indicators were adapted to the present context by specifying the desired target (using e-learning system LMS). A seven-point scale was employed in this research to measure TAM variables. This scale is suggested in the literature to meet the reliability and validity criteria [11,20,23]. Consistent with these studies, the TAM variables will be measured using Likert-type (agree-disagree) rating formats. The extent of agreement with belief statements is measured using seven-point “circle the number” rating scale formats. One item was used to obtain a self-reported measure of actual system use. A measure of frequency of use of the system was used to measure the actual use of the system. Frequency of using a system is typical of the usage metric routinely used in MIS research [23,59].

6.2Subjects

Since Arabic is the main language spoken in Jordan, the empirical study was conducted in the Arabic language. Thus, the original instrument has been translated from the English language into Arabic language. The translation process of the questionnaire consists of two phases. The first phase is translating the questionnaire from English to Arabic language through two translators. The second phase is comparing the two versions and resolving any differences. After preparing the final version of the questionnaire, the questionnaire was piloted. The Arabic questionnaire was pilot tested using Arab Open University students. Participants in the study consisted of undergraduate students who were taking the last lecture of the first basic computer literacy classes called GR100 and TU170 at Arab Open University (AOU) in Jordan. Participation in this study was voluntary, and 486 of 654 students (74.3%) who were enrolled in these classes agreed to take part (238 GR100 and 248 TU170). Sixteen questionnaires with more than 5% of missing data were identified and deleted. Thus, 470 questionnaires were included in the analysis. The sample was 470 cases, the analysisconducted on 36 items (see Appendix A), and the ratio of items to cases was 1:13.