Automatic competence leveling of learning objects

A competence is the effective performance in a domain at different levels of proficiency. Educational institutions apply competences to understand whether a person has a particular level of ability or skill. Educational resource enriched with competence information allows learners identifying, on a fine-grained level, which resources to study with the aim to reach a specific competence target. However, the process of annotating learning objects with competence levels is a very time consuming task, ideally, this task should be performed by experts on the subjects of the educational resources. Due to this, most educational resources available online do not enclose competence information. In this paper, we present a method to tackle the problem of automatically assigning an educational resource with competence levels. To solve these problems, we exploit information extracted from external repositories available on the Web, which lead us to a domain independent approach. We demonstrate the quality of the proposed methods through an evaluation on real world data with an additional user study. Results show that the automatic competence level assignment achieves 84% precision on ground truth data. The key implications of our approach are: first, it effectively facilitates experts in the arduous task of competence assignment and second, it directly supports learners to retrieve proper leveled material.