An Architecture for Dynamic Generation of QTI 2.1 Assessments for Mobile Devices Using Flash Lite

With the advent of m-learning, efficient rendition of XML-based assessments such as the QTIv2.1 is increasingly important. However, XML processing requires significant resources on resource-limited mobile devices. This paper presents an approach and architecture that bypass this problem by automatically generating self-contained Flash-Lite assessments from QTIv2.1 packages. A specialized object model of the QTIv2.1 is used in conjunction with open-source tools to generate assessments that are approximately five times smaller than those manually generated using macromedia learning interactions.