Mobile learning for just-in-time applications

Author(s):  
Tia G. Tucker ◽  
Woodrow W. Winchester
Keyword(s):  
Author(s):  
Mohamed Sarrab ◽  
Ibtisam Al Shibli ◽  
Nabeela Badursha

<p class="2">Mobile learning (M-learning) provides a new learning channel in which learners can access content and just in time information as required irrespective of the time and location. Even though M-learning is fast evolving in many regions of the world, research addressing the driving factors of M-learning adoption is in short supply. This article focuses on the driving factors in adoption of M-learning and the learner’s perceptions and willingness towards M-learning adoption. Technology Acceptance Model (TAM) has been shown to be a valid and powerful model in mobile and other learning technologies research. Based on Technology Acceptance Model theory, this paper analyzes the influencing factors on M-learning adoption and measure the acceptance of M-learning in Oman. The data collected from 806 participants in 17 different Omani higher education institutions using a survey questionnaire. Some factors of perceived innovative characteristics, such as ease of use, usefulness, enjoyment, suitability, social, and economic were found to have more influence on learners’ adoption of M-learning which help to facilitate and promote future empirical research. This effort is part of funded research project that investigate the development, adoption, and dissemination of M-learning in Oman.</p>


Author(s):  
John Traxler

The ideas of learning with mobiles in their current forms date back to roughly the turn of the century. Since then, there has been considerable change, not only in the technologies being developed and deployed and the education being delivered and supported but more importantly in the societies in which the technologies and education are embedded. The chapter describes learning with mobiles and mobile learning as two paradigms in the understanding of mobiles and learning. The notion of paradigms allows the authors to draw in not only the underlying axioms but also the chronological development, the geographical distribution, the evolving research agenda, the external environment, the practical and practitioner impact, and the emerging fractures and discrepancies at the periphery of each paradigm. One paradigm, the established one, was essentially a project situated among academics, universities, and countries in a handful of mobile learning “hotspots” in parts of the world’s developed regions, a project intended to enhance and extend institutional e-learning, to deliver on the promise of learning “anywhere, anytime,” and perhaps to develop and deliver learning “just-in-time, just-for-me.” This dates back to the turn of the century and is the established “mobile learning” paradigm. The other paradigm, the emergent one, more recent and less coherent, is driven by the ways in which increasingly pervasive, ubiquitous personal mobile technologies are transforming the ways in which people and communities everywhere generate, discuss, transform, discard, and store ideas, opinions, identities, images, and information and, in effect, become each other’s teachers.


Author(s):  
Kristine Peters

Mobile learning is variously viewed as a fad, a threat, and an answer to the learning needs of time-poor mobile workers, so does it have a place in delivering ‘mainstream’ learning? Based on a 2005 comparative research project, commissioned by the Australian Flexible Learning Framework, the paper reports on research into web-based information about the use of mobile technologies for commerce and learning, which was then tested through 29 interviews with manufacturers of mobile devices, businesses and education providers. The research found that mobile technologies were in common use in some commercial sectors but use purely for learning was rare. However m-learning lends itself to new methods of delivery that are highly suited to the ‘just enough, just in time, and just for me’ demands of twenty-first century learners.


Author(s):  
F. Jacob Seagull ◽  
Danny Ho ◽  
James Radcliffe ◽  
Yan Xiao ◽  
Peter Hu ◽  
...  

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