Abstract:

In the e-Learning area, as a part of its objective of interoperability between different platforms, it is aimed to making contents more portable, reusable and interchangeable between applications. This has led into the so-called learning objects. They are content units with an own meaning, which are constituted by multi-format packages, aimed at achieving specific educational objectives, identified by metadata and composed by resources, activities and assessment.
Considering the important role of learning objects in the development of elearning and its impact on the education, the concept of learning object quality is important in this area. As a consequence, developing appropriate mechanisms for the evaluation of learning objects has gained relevance, in order to ensure the development of learning resources with a certain quality level.
The problem of the study of the learning objects quality primarily lies in how to define the concept of LO. We could define the concept of learning object quality taking into account different perspectives. It could involve different issues, from the fulfilling level of its design requirements to problems of storage, retrieval or use of these LOs. Therefore, it is necessary to exactly define what aspects of LO quality will be considered. It is worth mentioning that another problem of the evaluation of the learning object quality is the subjectivity of any human evaluation. Thus, it is necessary to reduce as much as possible this subjective factor by means of universally accepted measurement scales for quality.
As mentioned above, in this paper we focus our attention on studying the quality of learning objects, and more specifically the quality of its content. This necessitates the use of techniques of content analysis, such as the information extraction techniques, since they provide methods for ascribing values to quality parameters from different information sources (collections of different type of documents: pdf, txt, doc) in a given context. In addition, ontologies will be used as a key resource for organising the extracted information and managing the information extraction processes. They facilitate an automatic evaluation process which will be repository-independent and flexible in the use of quality parameters.
This paper presents progress on this ongoing investigation, whose main objective is the development of LOQEVAL (Learning Object Quality Evaluation), a new proposal for learning object quality evaluation based on ontology.

Keywords:

ontologies, learning object, quality, loqeval.