Una propuesta de sistema de recomendación basado en competencias y modelado del estudiante ontológico

Laburpena

The great advances in the field of Computer Science and Internet have encouraged their application to almost any discipline. One of the most benefited areas is Education in which, thanks to the technological advances, many paradigms, strategies, platforms, communication methods, etc. have emerged. Consequently, the learning has evolved from a teacher-centered perspective to a perspective where the main character is the student. In this new constructivist approach, the competence-based model is increasingly widespread since it provides flexibility, facilitates the self-learning and brings the academic and professional world closer together. Competence, together with assessment instruments (e.g. rubrics) ease a more objective evaluation of the knowledge and skills demonstrated by the student in his/her performance. Recent researches include competences related to meta-domains not used in most popular learning models such as Bloom Taxonomy. The competences, together with student’s properties (student state, profile, preferences, etc.) and their learning, are essential support to the application of multiple processes like monitoring, diagnose, recommendation, or supervision. By means of them, which can be applied at the beginning, during or at the end of an activity, it is possible to infer information concerning the student progress, predict an anomalous situation, help the teacher in tutoring decisionmaking for each student, etc. In order to carry out properly any of these tasks, is essential to provide a suitable student modeling that allows for register all the required information about the student; student profile, knowledge state, student’s learning progress, etc. It would be very beneficial if this modeling, in addition to incorporate such information, employ mechanisms from which it is possible to infer additional information about the student’s knowledge state. In the framework of this PhD thesis, the creation of a competence-based recommender system prototype is proposed. For this, we use an extended ontology network responsible for storing the student learning process information. This network has been built from a previous version, following a methodological guide for the development of ontologies and a set of ontological and non-ontological resources previously analysed. The implemented recommender system prototype has been evaluated by means of three case studies, in which students perform a procedural learning experience by the use of three different environments. As main conclusions of the line of investigation carried out, the following can be extracted: (1) in learning modeling, the flexibility is an essential feature to achieve a balance between dispose of the most rich information about the student to provide adaptive capacities and register the less personal information for security, privacy and speed reasons, (2) competence model should be able to be applied to a wide range of meta-domains in the educational field with the aim of faithfully represent the reality of academic and professional worlds, (3) the application of assessment instruments such as rubrics, properly designed, can help to a more fair evaluation of the student’s knowledge and skills, (4) problems such as the cold start or overexploitation must be taken into account in the requirement analysis of recommender system and, specifically, in those relating to the educational field, (5) it is advisable to follow a methodology for the development of an ontology network focused on the appropriate and easy reuse of resources, evaluation and maintenance of the modular network. Additionally, we contributed to the competence-based recommender system state of the art by means of the reengineering of a modular network so-called Student Ontology, the description of a methodology for the adaptation of the proposed competence-based recommender system, the design of a taxonomy of recommendation criteria and rule patterns, as well as the development of a web application to monitor information about student’s learning process registered in the ontology such as actions, objective states, activities and recommendations. New lines of work related to the ontology network and compentence-based recommender system arise. The ontology network can be extended reusing other models, taxonomies or ontologies linked to the learning area. Other possible future lines are based on recommendations system improvements such as the extension of designed rule patterns in order to increase the type and number of recommendations, or the extension of the recommendation criteria taxonomy established here. Likewise, the application can be improved to allow more functionalities and characteristics such as good accessibility features