Name
Abstract | ||
|---|---|---|
Medical learning objects deviates,from traditional notion of learning object in that it is always in a digital form and relates to medication. They may include text, images, sound and video. They are introduced in order to facilitate the employees of healthcare sector and patients. In this article, we illustrate how medical learning objects can be personalized according to the user knowledge and adapted according to the working process in which the learning object is invoked. We believe that by introducing personalized and adapted medical learning objects we can optimally develop e-learning processes for healthcare sector that are just-in-time and are tailored to their specific needs. A problem of this approach is that the system has to support many variations of a medical learning object. We have solved this problem by producing the variations by the XSL T-transformations of the learning objects, which are processed when the learning object is invoked. |
Year | DOI | Venue |
|---|---|---|
2007 | 10.1109/ICALT.2007.183 | 7TH IEEE INTERNATIONAL CONFERENCE ON ADVANCED LEARNING TECHNOLOGIES, PROCEEDINGS |
Keywords | Field | DocType |
technology management,information retrieval,biomedical imaging,continuing professional development,diabetes,ontologies,health care,electronic learning,communications technology,taxonomy | Robot learning,Computer aided instruction,Biomedical education,Active learning (machine learning),Computer science,Continuing professional development,Knowledge management,User knowledge,Learning object,Error-driven learning,Multimedia | Conference |
Citations | PageRank | References |
3 | 0.51 | 3 |
Authors | ||
2 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Juha Puustjärvi | 1 | 111 | 22.64 |
| Leena Puustjärvi | 2 | 37 | 11.86 |