Browsing by Author "Quaresma, Rui"
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- Estratégia hibrida de recomendações sobre um gestor de conteúdos ampliado em ensino formalPublication . Madeira, Filipe; Quaresma, Rui; Abreu, SalvadorEste artigo tem por objetivo apresentar um Modelo para Recomendação Personalizada de conteúdos de aprendizagem, baseado numa estratégia de recomendação híbrida e no perfil de cada aluno. Incluímos uma proposta para a similaridade entre alunos que reflete os seus interesses em termos das avaliações pretendidas e da proximidade das sequências de atividades de aprendizagem dos diversos alunos. Este modelo prevê, igualmente, a inclusão de novos conteúdos por parte dos alunos e a definição de relacionamentos com os conteúdos existentes. São abordadas as motivações que nos levaram à presente proposta, alguns conceitos e trabalhos relacionados, assim como a arquitetura e desenho da solução, entretanto alvo de protótipo. Por fim são tecidas algumas conclusões.
- A hybrid recommender strategy on an expanded content manager in formal learningPublication . Madeira, Filipe; Quaresma, Rui; Abreu, S.The main topic of this paper is to find ways to improve learning in a formal Higher Education Area. In this environment, the teacher publishes or suggests contents that support learners in a given course, as supplement of classroom training. Generally, these materials are pre-stored and not changeable. These contents are typically published in learning management systems (the Moodle platform emerges as one of the main choices) or in sites created and maintained on the web by teachers themselves. These scenarios typically include a specific group of students (class) and a given period of time (semester or school year). Contents reutilization often needs replication and its update requires new edition and new submission by teachers. Normally, these systems do not allow learners to add new materials, or to edit existing ones. The paper presents our motivations, and some related concepts and works. We describe the concepts of sequencing and navigation in adaptive learning systems, followed by a short presentation of some of these systems. We then discuss the effects of social interaction on the learners’ choices. Finally, we refer some more related recommender systems and their applicability in supporting learning. One central idea from our proposal is that we believe that students with the same goals and with similar formal study time can benefit from contents' assessments made by learners that already have completed the same courses and have studied the same contents. We present a model for personalized recommendation of learning activities to learners in a formal learning context that considers two systems. In the extended content management system, learners can add new materials, select materials from teachers and from other learners, evaluate and define the time spent studying them. Based on learner profiles and a hybrid recommendation strategy, combining conditional and collaborative filtering, our second system will predict learning activities scores and offers adaptive and suitable sequencing learning contents to learners. We propose that similarities between learners can be based on their evaluation interests and their recent learning history. The recommender support subsystem aims to assist learners at each step suggesting one suitable ordered list of LOs, by decreasing order of relevance. The proposed model has been implemented in the Moodle Learning Management System (LMS), and we present the system’s architecture and design.