Abstract
As the cloud technologies are largely studied and mobile technologies are evolving, new directions for development of mobile learning tools deployed on cloud are proposed.. MLearning is treated as part of the ubiquitous learning paradigm and is a pervasive extension of E-Learning technologies. Development of such learning tools requires specific development strategies for an effective abstracting of pedagogical principles at the software design and implementation level. Current paper explores an interdisciplinary approach for designing and development of cloud based M-Learning tools by mapping a specific development strategy used for educational programs to software prototyping strategy. In order for such instruments to be user effective from the learning outcome point of view, the evaluation process must be rigorous as we propose a metric model for expressing the trainee’s overall learning experience with evaluated levels of interactivity, content presentation and graphical user interface usability.
Highlights
What do you think about installing mobile applications?Very unsecure/ Little unsecure / Neutral / I trust some vendors / I don’t Little unsecure – 23%
Extends the list of service model delivery in cloud computing, a Learning as a Service (LaaS) model could be considered for cloudenabled learning tools including cloud Elearning systems and cloud M-learning systems
6 Conclusions M-Learning is an extension of E-learning and it represents a complementary tool for virtual learning process
Summary
Very unsecure/ Little unsecure / Neutral / I trust some vendors / I don’t Little unsecure – 23%. Do you think that having mobile access to educational content would be in Absolutely no – 2%. Would you install mobile applications to gain mobile access to educational Probably NO – 2%. Would you buy a new mobile device with higher performances in order to NO – 9%. Do you think that usage of a Mobile Learning solution could improve your NO – 4% YES – 12%. In which context would you use such M-Learning application? The overall experience, interactivity, content presentation and user interface was evaluated using 1 to 10 scales. We will concentrate on data analysis especially on the four data distributions which evaluates the M-learning experience, calculating the reliability and correlations between them in order to build a metric for expressing the overall M-Learning experience provided by the prototype
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