Using presentations in an m-Learning environment enables delivery of rich content to a mobile phone learner. This study investigated how to prepare and stream presentations from a desktop computer to a mobile phone in near-realtime. It also addressed communication between users using interactive text chat in the same environment. Our analysis of text/podcast-based m-Learning applications revealed limited interactivity and lack of diversity in content streamed. To address this, we developed a mobile-based application that uses a task-timer model to synchronize with a server every n units of time to enable near-realtime streaming of presentation slides between mobile and desktop users. The application included text-based instant messenger. Laboratory experiments investigated the use OpenOffice and PowerPoint presentations and techniques used to convert these presentations into mobile phone compatible formats. Experiments were carried out with smart mobile phones running on a third generation cellular network. We employed transaction-logging techniques in addition to automated image analysis techniques to observe and record data. Analysis of the results revealed using presentations enabled more rich content than text-based models such as short message service-based frameworks and podcasts. Although m-Learning is not yet widely adopted, applications such as the one developed in the study offer high hopes for m-Learning because of the use of rich content and interactivity between users.

Using presentations in an m-Learning environment enables delivery of rich content to a mobile phone learner. This study investigated how to prepare and stream presentations from a desktop computer to a mobile phone in near-realtime. It also addressed communication between users using interactive text chat in the same environment. Our analysis of text/podcast-based m-Learning applications revealed limited interactivity and lack of diversity in content streamed. To address this, we developed a mobile-based application that uses a task-timer model to synchronize with a server every n units of time to enable near-realtime streaming of presentation slides between mobile and desktop users. The application included text-based instant messenger. Laboratory experiments investigated the use OpenOffice and PowerPoint presentations and techniques used to convert these presentations into mobile phone compatible formats. Experiments were carried out with smart mobile phones running on a third generation cellular network. We employed transaction-logging techniques in addition to automated image analysis techniques to observe and record data. Analysis of the results revealed using presentations enabled more rich content than text-based models such as short message service-based frameworks and podcasts. Although m-Learning is not yet widely adopted, applications such as the one developed in the study offer high hopes for m-Learning because of the use of rich content and interactivity between users.

Masters of Science / Using presentations in an m-Learning environment enables delivery of rich content to a mobile phone learner. This study investigated how to prepare and stream presentations from a desktop computer to a mobile phone in near-realtime. It also addressed communication between users using interactive text chat in the same environment. Our analysis of text/podcast-based m-Learning applications revealed limited interactivity and lack of diversity in content streamed. To address this, we developed a mobile-based application that uses a task-timer model to synchronize with a server every n units of time to enable near-real time streaming of presentation slides between mobile and desktop users. The application included text-based instant messenger. Laboratory experiments investigated the use Open Office and PowerPoint presentations and techniques used to convert these presentations into mobile phone compatible formats. Experiments were carried out with smart mobile phones running on a third generation cellular network. We employed transaction-logging techniques in addition to automated image analysis techniques to observe and record data. Analysis of the results revealed using presentations enabled more rich content than text-based models such as short message service-based frameworks and podcasts. Although m-Learning is not yet widely adopted, applications such as the one developed in the study offer high hopes for m-Learning because of the use of rich content and interactivity between users. / South Africa