Screening of Students’ Intentions to Adopt Mobile - Learning: A Case from Egypt

Screening of Students’ Intentions to Adopt Mobile - Learning: A Case from Egypt

Sohayla M. El-Sherbiny Attalla (Mansoura University, Egypt), Reem El-Sherbiny (Mansoura University, Egypt), Wafaa A. Mokbel (Mansoura University, Egypt), Rania M. El-Moursy (Nile Academy for Commercial Science and Computer, Egypt) and Ahmed G. Abdel-Wahab (University of Mansoura, Egypt)
Copyright: © 2012 |Pages: 18
DOI: 10.4018/ijopcd.2012010105
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Mobile technology is a growing field with emerging new discoveries. The introduction of third generation mobile network services and the convergence of mobile and traditional internet services will make the mobile communication a key enabler for achieving competitive advantages in developing countries, including opportunities for mobile learning (M-learning). This study explores the possibility of applying M-learning in Egypt by looking at the factors that affect the students’ intentions to adopt M-learning. Data was collected by a survey of 239 business students of the English program in the faculty of commerce at Mansoura University. The technology adoption model is studied with two more independent variables, namely, pressure to act and resource availability. Results showed that there are four factors that can be used in modelling students’ intentions to adopt M-learning. These factors are attitude towards M-learning, perceived usefulness, availability of resources and perceived ease of use.
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There is no doubt that information and communication technologies are among the defining technological transformations of the late 20th and early 21st centuries. One of the most important of these technological advancements are those generations of small, portable mobile devices that provide a combination of telephone, internet, and data storage and management features. The communication and data transfer possibilities created by such mobile technologies has created opportunities for mobile learning. Mobile learning (M-learning) is an activity in which people carry out learning activities using a mobile device like a cell phone or a personal digital assistant (PDA). It allows users to access learning material anytime and anywhere (Clyde, 2004; Hill & Roldan, 2005). Mobile learning is uniquely suited to support context-specific and immediate learning, and this is a major opportunity for distance learning since mobile technologies can situate and connect learners (Traxler, 2007).

Although M-learning can be thought of as a subset of electronic learning (e-learning) (Peters, 2007) it can be differentiated from e-learning in that it is characterized by being personal, spontaneous, opportunistic, informal, pervasive, situated, context-aware, bite-sized, and portable. On the other side conventional e-learning is characterized by being structured, media-rich, broadband, interactive, intelligent, and usable (Traxler, 2007). M-learning is also linked directly to the “just enough, just in time, just for me” model of flexible learning (Figure 1), and is therefore just one of the options that can be adapted to suit individual learning needs (Peters, 2007). In other words, M-learning supports learning that recognizes the context and history of each individual learner and delivers learning to the learner when and where they want it. An ideal application for mobile learning revolves around providing performance support tools at the point directly where they are needed (Wagner, 2008) where it should be noted that M-learning is certainly not an end in itself, so it is important to consider where it fits within a holistic learning model (Gregson & Jordan, 2009).

Figure 1.

The “just enough, just in time, just for me” model of flexible learning (Perters, 2007)


Needs that can be enhanced using m-learning were as follows (Gregson & Jordan, 2009):

  • 1.


  • 2.

    Access and participation.

  • 3.

    Tutoring support to students in diverse locations.

  • 4.

    The usability of learning resources for students who are very mobile.

  • 5.

    Access to content and programme materials.

M-learning applications can be sub-divided into seven categories (Clough et al., 2009):

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