Abstract:

In modern e-learning, Learning Content Management Systems (LCMS) are a key piece for the interchange of resources. LCMS are repositories specialized in search and recovery of instruccional resources. These elements are combined to create learning experiences that are published in a Learning Management System (LMS).

Learning Objects Management Systems (LOMS) are LCMS focusing to Learning Objects (LO). LO is a basic unit of information and interchange between e-learning applications. LOMS has specialized tools for tagging features, classification and edition of learning object. These systems can offer tools for collaborative work, especially for certain activities as identification label, classification and objects evaluation.

Nevertheless, the quality in learning objects is a problematic present in many management activities. There are works related to establishment evaluation methods and techniques to define the quality of learning object. Many of these works are focused to technological features while its didactical point of view into the learning objects it remains in the background.
In this work is present a Quality Evaluation Model for Learning Objects (MECOA, from a Spanish acronym that means it). The MECOA is a collaboration product between some Iberoamerican institutions, its aim is to propose a model to evaluate the learning objects from a pedagogical perspective.

MECOA uses indicators collections grouped in five categories: content, representations, competence, self- management, signification and creativity. MECOA defines a linguistic label set for each one of indicators.
An instrument for evaluation was designed to implement MECOA. This instrument is easy to answering for experts into learning objects. The obtained test was incorporated into AGORA platform (from a Spanish acronym that means Help for the Management of Reusable Learning Objects). This LOMS offers services on recommendation and assistance on a given curricular design for building the learning objects.

The obtained results from the MECOA’s implementations into AGORA are source of important pedagogical information, especially in the learning object management process; due that, this quality evaluation information is added to the metadata of the object and could be retrieved along with the OA within LOMS. As example of this, a rule set was obtained by means methodological extraction knowledge. The generated rules are IF-THEN type and can be used for improvement some learning object related task like search, labeled, sequencing from recommending perspective.

Keywords:

learning object, quality, data mining, knowledge extraction.