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Electronic learning (e-learning) is one of the most significant recent developments in the information and communication technology (ICT) industry. The growth of e-learning systems presented a unique challenge for universities (Wang, 2003). According to some interpretations, e-leaning is a part of a continuum process in the presence of technology as a substantial component for replacing traditional learning systems (ZeKANOvic-korona et al., 2007). E-learning has been adopted in education for a variety of purposes, especially in higher education. Most universities use e-learning as a supplementary tool to enhance in-class instruction (Siritongthaworn et al., 2006).
In the present economic environment, characterized by technological dynamism and intensive competition, the problems of customer profitability have become paramount for the success of any business. Understanding customer needs and leveraging this information to manage customers more effectively is necessary to creating a competitive advantage in the new economy (Gurau, 2001). A marketing perspective suggests that students are as the ultimate customers of an educational system, since satisfaction with an educational product/service is one outcome of the exchange between instructors and students (Wang, 2003). In the e-learning environment, satisfaction includes both pedagogical aspects as well as the information systems. The prior research of fulfillment in the field of e-learning systems also provides a significant background to the e-learning context.
For comparing the e-learning system and traditional learning system, two comprehensive studies are illustrated. Mahdavi et al. (2008) compared traditional system with virtual educational system statistically in Iran. In this way, by the means of economical equations and statistical analysis they illustrated an in depth survey. Finally, by the means of hypothesis testing, they illustrated the best option for educational system is the combination of both systems. Fazlollahtabar and Sharma (2008) compared traditional engineering educational system with the e-learning engineering educational system on the economic dimension using hypothesis testing approach in Iran. The comparison involved trend analysis and prediction based on costs and benefits of the two systems. Interestingly, the analysis revealed that the traditional system had greater advantage on the economic dimension. Several factors support the e-learning system despite the associated economic disadvantage. The final analysis provided results in favor of a blended system which takes advantage of the traditional and e-learning systems.
Different studies have been worked out on cost optimization within e-learning environment. Mahdavi et al. (2008) identified varied cost elements in e-learning educational system and optimized them by the means of mathematical programming. Then they proposed an effective method to estimate the learning cost between any two skills of learner using the grey relational analysis. Mahdavi et al. (2008) developed their previous study combining the grey relational analysis and a radial basis function network to estimate the learning cost between any two skills after identification of varied cost elements in e-learning educational system and optimization by the means of mathematical programming. Fazlollahtabar and Yousefpoor (2009) applied the cost elements in the e-learning educational systems and proposed a combination of grey relational analysis and a radial basis function network to estimate the learning cost between any two skills. An integer programming method was employed to demonstrate that it is possible to facilitate the acquisition of single skills by considering a set of useful compound skills.