In the multimedia documents authoring systems the management of spatial and temporal inter-objects relations is the most delicate task. Spatial relations management refers to the appropriate means to express relations between the document objects and guarantee their consistency. Usually it is represented by spatial model which performances depend on its expressivity degree, on its positioning precision and on the ability to express a desired overlap. One of the most important factor that affects performnaces is the distance associated to the relations. To enhance the expressivity and precision degrees and to allow the specification of desired overlap, we introduce, in this paper, the flexible distance concept
Providing high-quality courses is of utmost importance to drive successful learning. This compels course authors to continuously review their contents to meet learners' needs. However, it is challenging for them to detect the reading barriers that learners face with content, and to identify how their courses can be improved accordingly. In this paper, we propose a learning analytics approach for assisting course authors performing these tasks. Using logs of learners' activity, a set of indicators related to course reading activity are computed and used to detect issues and to suggest content revisions. The results are presented to authors through CoReaDa, a learning dashboard empowered with assistive features. We instantiate our proposals using the logs of a major European e-learning platform, and validate them through a study. Study results show the effectiveness of our approach providing authors with more awareness and guidance in improving their courses, to better suit learners' requirements.
A multimedia document should be presented on different platforms, for this adaptation of its content is necessary. In this contribution, we make some proposals to improve and extend the semantic approach based on conceptual neighborhoods graphs in order to best preserve the proximity between the adapted and the original documents and to deal with models that define delays and distances.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.