Abstract:

The students´ overcrowding in classrooms and the offer of digital media courses imply the need of new learning objects in education, as these reusable electronic tools allow objective evaluations in large groups by using few resources. The aim of this research is a proposal for a massive assessment in the quality of digital learning tools used in the students´ learning, by using statistical methods (cluster analysis). This method supplies the classification and identification of gaps within the assessment and self-learning instruments from different psychometric indicators. The research corresponds to a study case using a learning virtual platform (moodle) where different digital learning objects were implemented, being used by students as tools for learning and assessment. Teachers analyzed results applied to objective evaluation and self- assessment tests, which determined whether they were properly designed learning activities and their discriminatory properties. In conclusion, the use of statistical methods massively detected failures or errors in the design of objective tests, allowing an important improvement in the quality and reuse of these resources.

Keywords:

Learning Objects, objective tests, moodle, discrimination, cluster analysis.