Distance learning, electronic learning, and mobile learning offer content, methods, and technologies that decrease the limitations of traditional education. Mobile learning (m-learning) is an extension of distance education, supported by mobile devices equipped with wireless technologies. It is an emerging learning model and process that requires new forms of teaching, learning, contents, and dynamics between actors. In order to ascertain the current state of knowledge and research, an extensive review of the literature in m-learning has been undertaken to identify and harness potential factors and gaps in implementation. This article provides a critical analysis of m-learning projects and related literature, presenting the findings of this aforementioned analysis. It seeks to facilitate the inquiry into the following question: “What is possible in m-learning using recent technologies?” The analysis will be divided into two main parts: applications from the recent online mobile stores and operating system standalone applications.

No abstract

No abstract

Abstract-Wireless sensor networks span from military applications into everyday life. Body sensor networks greatly benefit from wireless sensor networks to answer the biofeedback challenges in healthcare applications. In such applications, data is of fundamental importance, it must be reliable and within easy reach. However, most solutions rely on a personal computer to process and display sensor data. In this paper we propose a mobile solution that draws on three-tier body sensor networks to dramatically improve data accessibility, through the use of a Java and Bluetooth-enabled mobile phone. The mobile tool features data monitoring and presentation. This approach allows data visualization by the patient or medical staff without a portable computer or specific monitoring hardware. We hope to contribute to the adoption of biofeedback for early detection of health abnormalities and lower the budget that governments spend each year in healthcare.