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Auflistung nach Autor:in "Burgos, Daniel"

1 - 3 von 3
  • Konferenzbeitrag
    Meta-rules: Improving Adaptation in Recommendation Systems
    (18th Intl. Workshop on Personalization and Recommendation on the Web and Beyond, 2010) Romero, Vicente; Burgos, Daniel
    Recommendation Systems are central in current applications to help the user find useful information spread in large amounts of post, videos or social networks. Most Recommendation Systems are more effective when huge amounts of user data are available in order to calculate similarities between users. Educational applications are not popular enough in order to generate large amount of data. In this context, rule-based Recommendation Systems are a better solution. Rules are in most cases written a priori by domain experts; they can offer good recommendations with even no application of usage information. However large rule-sets are hard to maintain, reengineer and adapt to user goals an preferences. Meta-rules, rules that generate rules, can generalize a rule-set providing bases for adaptation, reengineering and on the fly generation. In this paper, the authors expose the benefits of meta-rules implemented as part of a meta-rule based Recommendation System. This is an effective solution to provide a personalized recommendation to the learner, and constitutes a new approach in rule-based Recommendation Systems.
  • Konferenzbeitrag
    Pathway recommendation based on a pedagogical ontology and its implementation in moodle
    (DeLFI 2014 - Die 12. e-Learning Fachtagung Informatik, 2014) Henning, Peter A.; Forstner, Alexandra; Heberle, Florian; Swertz, Christian; Schmol, Alexander; Barberi, Alessandro; Verdu, Elena; Regueras, Luisa M.; Verdu, Maria J.; Castro, Juan Pablo De; Burgos, Daniel; Valentin, Luis De La Fuente; Gal, Eran; Parodi, Elisabetta; Schwertel, Uta; Learning, Sven Steudter
    When learners may select among different alternatives, or are guided to do so by an adaptive learning environment (ALE), it is generally meaningful to discuss the concept of different learning pathways. Pedagogically, these learning pathways may either be defined macroscopically, e.g. in terms of desired learning outcomes or competencies, or microscopically in terms of a didactical model for individual knowledge objects. In this contribution we consider such learning pathways from a pedagogical point of view and then establish a mathematical model for their traversal by a learner and for the analysis of his behavior. This model is implemented in a novel ALE provided by the EU FP7 project INTUITEL, introduced in its Moodle version as concrete example.
  • Konferenzbeitrag
    What is wrong with the IMS Learning Design specification? Constraints And Recommendations
    (18th Intl. Workshop on Personalization and Recommendation on the Web and Beyond, 2010) Burgos, Daniel
    The work presented in this paper summarizes the research performed in order to implement a set of Units of Learning (UoLs) focused on adaptive learning processes, using the specification IMS Learning Design (IMS-LD). Through the implementation and analysis of four learning scenarios, and one additional application case, we identify a number of constraints on the use of IMS-LD to support adaptive learning. Indeed, our work in this paper shows how IMS-LD expresses adaptation. In addition, our research presents a number of elements and features that should be improved and-or modified to achieve a better support of adaptation for learning processes. Furthermore, we point out to interoperability and authoring issues too. Finally, we use the work carried out to suggest extensions and modifications of IMS-LD with the final aim of better supporting the implementation of adaptive learning processes.