Flexible Learning Object Metadata

By far the most popular specification for learning objects is the IEEE Learning Object Metadata (LOM) standard. In it are outlined 76 different elements that correspond to pedagogical, technical, and administrative aspects of learning objects. This standard, however, has proven to be ineffective for creating computer adapted dynamic courseware. This paper outlines some initialr esear ch we ar e d oing in acquir ing, descr ibing, and using lear ning object metadata. Instead of the IEEE LOM, we ar gue for a mor e flexible appr oach to both defining and associating metadata with lear ning objects. By cr eating domain, educational, and lear ner char acter istic ontologies, content can be dynamically linked to those competencies that ar e o bser ved in ar unning e-lear ning system. This pr ovides for a set of evolutionar y me tadata, wher e softwar e agents can inspect multiple metadata instances for a given lea r ning object andr eason over them for a par ticular goal. As more metadata instances are added to the system, agents are expected to be able to provide more accurate reasoning, eventually leading to the dynamic delivery of personalized course content.