With the proliferation of mobile computing technology, mobile learning (m-learning) will play a vital role in the rapidly growing electronic learning market. M-learning is the delivery of learning to students anytime and anywhere through the use of wireless Internet and mobile devices. However, acceptance of m-learning by individuals is critical to the successful implementation of m-learning systems.Thus, there is a need to research the factors that affect user intention to use m-learning. Based on the unified theory of acceptance and use of technology (UTAUT), which integrates elements across eight models of information technology use, this study was to investigate the determinants of m-learning acceptance and to discover if there exist either age or gender differences in the acceptance of m-learning, or both. Data collected from 330 respondents inTaiwan were tested against the research model using the structural equation modelling approach. The results indicate that performance expectancy, effort expectancy, social influence, perceived playfulness, and self-management of learning were all significant determinants of behavioural intention to use m-learning. We also found that age differences moderate the effects of effort expectancy and social influence on m-learning use intention, and that gender differences moderate the effects of social influence and self-management of learning on m-learning use intention.These findings provide several important implications for m-learning acceptance, in terms of both research and practice.

http://www.anitacrawley.net/Resources/Articles/Wang%20Investigating%20the%20determinants%20and%20age%20and%20gender%20Wang.pdf

Investigating the determinants and age and gender differences in the acceptance of mobile learning

Factors affecting engineers' acceptance of asynchronous e-learning systems in high-tech companies

Purpose – The main purpose of this study is to examine whether quality factors as the antecedents to learner beliefs can affect learners' intention to use an e‐learning system.Design/methodology/approach – This study gathered sample data from eight high‐tech companies in Taiwan. A total of 680 questionnaires were randomly distributed, 522 questionnaires were returned for a response rate of 76.76 percent, and 483 usable questionnaires were analyzed, with a usable response rate of 71.03 percent. Data were analyzed by using structural equation modeling.Findings – Information quality, service quality, system quality, and instructor quality, as the antecedents of e‐learning acceptance can provide detailed accounts of the key forces underpinning employees' perception with regard to their beliefs (i.e. perceived usefulness, perceived ease of use, and perceived enjoyment), and this situation can further enhance employees' usage intention of the e‐learning system.Originality/value – Based on the extended technolog...

http://ir.lib.cyut.edu.tw:8080/bitstream/310901800/22630/2/%E7%A8%8B%E6%B0%B8%E6%98%8E%28Effects+of+quality+antecedents+on+e-learning+acceptance%29.pdf

Effects of quality antecedents on e‐learning acceptance

The Learning Management System (LMS) has been established in a number of universities worldwide to help connect students and lecturers without the confines of the traditional classroom. It is an environment with digital software which is designed to manage user learning interventions as well as deliver learning content and resources to students. Since the LMS system has already been implemented and it has also been made compulsory for the lecturers to apply in their daily lectures, it is vital to identify feedback of students as users of LMS. Previous studies have shown various findings in relation to the impact of using LMS in the higher learning environment in various universities worldwide. Therefore, this paper will provide several insights of the LMS phenomenon.

/pdf/learning-management-system-lms-among-university-students-phucf3mcht.pdf

Learning Management System (LMS) among university students: does it work?

Moderating effect of learning styles on a learning management system's success

The impact of the Internet on the development and delivery of training programs is real—analysts forecast that corporate spending on e-learning programs will top US$23 billion by 2004. Although the term “e-learning” has now firmly embedded itself into the global corporate vernacular, most executives find themselves doing little more than scattering people and technologies within training programs at random with the hope that one of these programs will work. First generation e-learning systems tend to focus almost entirely on the management and measurement of training processes. They add little or no value to the learning process. Furthermore, they do not provide any means to support internal content production processes, relying instead on commercial courseware. These “learning management systems” (LMS) were seen to be nothing more than launch pads for third party content that the organization would purchase or outsource. Adding to the confusion has been the roar of hype among a growing number of e-learning providers, whose promises and forecasts have left executives wandering on the e-learning path, without a definite direction. In this paper, the author provides an insight into the different types of e-learning systems that can be developed as well as the tasks and activities necessary to build them.

The design of an e-learning system: Beyond the hype

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The design of an e-learning system: Beyond the hype