Determinants of E-Learning Acceptance: An Empirical Study in the Tunisian Context

Bouzaabia Rym, Bouzaabia Olfa, Ben M’Barek Mélika

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Faculty of Eco- nomic Sciences and Management of Tunis, University of Tunis El Manar, Tunis, Tunisia.

DOI: 10.4236/ajibm.2013.33036                

Abstract

This study proposes to identify the determinants of accepting e-learning by the employees of the Tunisian Post Office using the Technology Acceptance Model (TAM). An empirical study was conducted over a sample of 200 Tunisian employees. Our results indicated that for the Tunisian employees perceived usefulness, perceived ease of use, mastery of new information and communication technologies (NICT) as individual factors as well as the proposed technique as an organisational factor represented the main determinants of e-learning acceptance.

Keywords

E-Learning; Technology Acceptance Model; Tunisian Context; Structural Equation Modeling

1. Introduction

The emergence and evolution of the Internet have led to the development of useful and powerful tools for distance learning. As a result, e-learning is becoming increasingly important and is making the learning process more effective in many contexts [1].  

Education and industry have sought the contribution of e-learning in order to improve their competitivity [2], financially, socially and organisationally. Finance-wise, e-learning allows for reducing total training costs by eliminating various transportation and accommodation fees which sometimes exceed half of the total costs [3,4]. Organisation-wise, e-learning creates new individual training platforms, favours group training within virtual teams and prepares knowledge management thanks to electronic interactions which reinforce group and cooperative work [5]. Socially speaking, thanks to its permanent and participatory potentials, e-learning may be perceived by employees as a “strong social act that generates in them better behaviour at work” [6]. Despite these advantages, recourse to e-learning is not often accepted by end users. We notice that users are often unwilling to opt for e-learning even if this latter may generate significant increases in productivity [7]. The reasons seem to be subtle and exceed rational decisions traditionally recommended by the economic approach.

It would be then interesting to determine the factors that influence the implementation of e-learning among the training practices of Tunisian firms. Understanding determinants of e-learning adoption assumes the analysis of the manner with which trainees perceive, express and use this training technique.

Then, our study aims at determining the factors behind accepting e-learning by trainees. To this effect, we use a very well defined model, which is the Technology Acceptance Model (TAM), to conduct an empirical study over 200 employees of the Tunisian Post Office across the different regions of Sfax, Sousse, Tunis, Monastir and Jendouba to test our hypotheses.

In the first section, we present the review of the literature. In the second section, we present our research hypotheses. The third section discusses our methodology. Finally, the results of our research are presented and discussed in the last section.

2. Literature Review

2.1. Definition of E-Learning

E-learning generally refers to methods of learning which use electronic instructional content delivered via the internet and is a term which is synonymous with Webbased or online learning [8]. The widespread proliferation of internet technologies and applications provides incredible opportunities for the delivery of education and training. Moreover, with rapidly increasing internet usage e-learning has now become a portable and flexible new method for learners to gain essential knowledge [8]. Nowadays e-learning is emerging as a new paradigm of modern education, especially for small and mediumsized enterprises [9].

Many empirical studies support the idea that effective e-learning benefits organization success [10]. That is why e-learning plays such an important role in organizational training.

E-learning can be classified as asynchronous e-learning or synchronous e-learning [11,12]. First asynchronous e-learning is a form of self-study [13] commonly facilitated by media such as email and discussion groups; supports work relationships among learners with teachers, even when participants cannot be online at the same time. As such, it is a key component of flexible e-learning [14]. In contrast synchronous e-learning allows for real-time interaction and just-in-time response between instructors and learners [15] commonly supported by media such as videoconferencing and chat. It has a potential to support e-learners in the development of learning communities [14].

According to Favier et al. [16], the main stakeholders in an e-learning platform are learners, teachers-tutors, but also the institution in which the project takes place. These are the three areas of performance of e-learning [17]. E-learning provides for learners several advantages [18-20]:

• Ease of learning with better retention: E-learning offers to learners the opportunity of an easy access to relevant and useful knowledge [21-24]). Collins et al. [21] argue from them that “e-learning” enhances information storage rate.

• Flexibility of time and place: e-learning gives students the opportunity to attend training at anytime, anywhere [25]; this is the “Just in time” approach [19,26].

• Customizing e-learning: “e-learning” allow learners to learn according to their individual pace and according to their personal agendas [11,26,27].

• Improving Productivity: E-learning offers opportunities to improve and increase learners’ effectiveness [21,23].

• Interactivity and institution-community collaboration: e-learning binds each learner with other learners and experts together to form a collaborative learning community [11,21,26].

However, these assumptions are not shared by all researchers [28,29] and are dependent on the acceptance of e-learning technologies for learners, which is linked to a number of contextual factors.

2.2. The Technology Acceptance Model

The technology acceptance model was introduced by Davis [30] as an adaptation of the theory of reasoned action to model user acceptance of information systems. Its purpose is to explain the determinants of the acceptance of the use of computers and related technologies in a wide range of technologies and user groups. TAM has been made ​​to trace the impact of external factors on the beliefs, attitudes and intentions by identifying a limited number of variables suggested by previous research regarding the cognitive and emotional determinants of accepting the computer and using TRA as the theoretical foundation for modeling the theoretical relationships between these variables.

TAM explains the acceptance of information technology in performing tasks and identifies perceived usefulness (PU) and perceived ease of use (PEOU) as two key determinants that enhance the use of technology [2]. Davis [30] offers the following definitions of the two key concepts of the model:

• Perceived usefulness is “the degree to which a person believes that using a particular system would enhance his job performance” [30].

• Ease of use refers to “the degree to which a person believes that using a particular system would be free of effort” [30].

“According to the TAM, both PU and PEOU influence the attitude of individuals towards the use of a particular technology, while attitude and PU predict the individual’s behavioural intention (BI) to use the technology” [13]. PU is influenced by PEOU, because, other things being equal, the easier a technology is to use, the more useful it will be [31]. “PU is also influenced by PEOU. TAM also suggests that external variables intervene indirectly, influencing both PU and PEOU” [13].

Davis model is presented as the Figure 1 shows.

2.3. Extended TAM

TAM has been the subject of several applications and has been shown to be a significant predictor in a variety of studies. Venkatesh and Davis [32] examined the impact of gender on the acceptance of technology and have concluded that gender is a fundamental aspect of culture and it can affect the process of technology adoption.

Figure 1. Technology acceptance model.

Mathieson [33] compared TAM and theory of planned behaviour and noted that both provide a good explanation of intention. However, while TAM is the easiest to apply, it provides only general information about the views of technology users. Mathieson [33] postulates that the key concepts of TAM remain insufficient to predict intention to use, and those other variables, equally powerful and meaningful, should be incorporated into the model.

Moreover, the fact that TAM in its first version has evaded subjective norms has been criticized. Thompson [34] showed that the addition of an appropriate social factor increases its predictive value. For their part, Venkatesh and Davis [32] assume that the first version of TAM lacks pragmatic usefulness because it does not explain the factors of each concept of the model.

In this paper an extended model is proposed, based on an extension of the TAM approach. The extended model includes constructs and relationships which may prove to be important in the context of e-learning. These constructs are: Social factors; System factors; Individual factors organizational factors and Voluntariness of use factors.

3. Research Model and Hypotheses

Our research design was inspired by the model of technology acceptance and various extensions and modifications made to this model [15,32,33]. Four types of factors influence usefulness and perceived ease of use of elearning: Social factors (Interpersonal influences and intrapersonal influences), System factors (content quality), organizational factors (technics assistance) and individual factors (NICT self-efficacy).

Perceived usefulness jointly reacts with perceived ease of use on attitude toward the use of e-learning. The intended use of e-learning is influenced at the same time by attitude towards this behaviour, by interpersonal influences, and perceived usefulness of e-learning.

Finally, voluntariness will have a moderating effect on the relationship between social factors (INI/ EXI) and the intention to use e-learning [35].

Figure 2 shows an operationalization of the extended TAM.

Conflicts of Interest

The authors declare no conflicts of interest.

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