Automatic Trap Detection: A Debugging Mechanism for Abnormal Specification in the IMS Sequencing Controls

Abstract

Adaptive learning is a challenge trend to distance education. In order to adapt diversified teaching in accordance with individual abilities, educators emphasize on constructing personalized courseware as an Internet-based application. To cope with the drawback of non-supervised blind spot on dynamic navigation of learners, the SCORM 2004 specification adds the concept of sequences into its content delivery. Sequencing rules describe how individual navigation is invoked, what learning objects are delivered during the navigation process, and the potential outputs of the process. However, there is a potential leak of using sequence specification. A sequencing trap results from improper sequence composition, which may block learning activities from a normal navigation. Although the problem can be manually checked with an ordinary SCORM presentation tool, non-systematic debugging can be an unsound solution and time consuming job, since complexity of courseware is usually proportional to the occurrences of traps. We point out the sequencing trap problem and its solution by using a fully automatic mechanism for trap detection. Petri net is used in the computation of sequencing traps. Contribution of this paper can be used as the first technique for automatic sequencing testing in the IMS Simple Sequence Specification and the SCORM 2004.