Uma arquitetura computacional para autoria e personalização de objetos de aprendizagem em ambientes educacionais ubíquos

• Autor(a) principal: Araújo, Rafael Dias
• Data de Publicação: 2017
• Tipo de documento: Tese
• Idioma: eng
• Título da fonte: Repositório Institucional da UFU
• Texto Completo: https://repositorio.ufu.br/handle/123456789/20375; http://dx.doi.org/10.14393/ufu.te.2018.9
• topic: Aprendizado Enriquecido por Tecnologia; Hipermídia Educacional Adaptativa; Objetos de Aprendizagem; Ambientes Educacionais Ubíquos; Technology Rich Classrooms; Adaptive Educational Hypermedia; Learning Objects; Ubiquitous Learning Environments; CNPQ::CIENCIAS EXATAS E DA TERRA::CIENCIA DA COMPUTACAO

Computers have become everyday tools in the contemporary classroom. Laptops, tablets, smartphones, interactive whiteboards, and other electronic devices are constantly used to support both instructors, while teaching, and students in the learning process. In both cases, they can access educational content and activities anywhere and anytime they wish. In this way, Ubiquitous Learning Environments (ULEs) – or Technology Rich Classrooms – are created to combine real and virtual learning environments in order to produce richer study artifacts. However, it produces a huge volume of Learning Objects (LOs), often unstructured, which makes retrieving and presenting such content a challenge for this type of computing system, especially because it should happen in a clear and organized way and considering users’ needs. In this work, we explore the concept of Adaptive Educational Hypermedia (AEH) which have appeared to deal with the issue of educational content personalization in Web environments together with ULEs for generating and providing personalized LOs to students. Thereby, this research proposal tackles this issue by designing a computational architecture grounded on ULEs and Intelligent Tutoring Systems (ITSs) concepts, capable of structuring LOs captured in classrooms and their metadata through a collaborative approach, and offering content personalization and recommendation features to students. In this work, the term architecture is related to a computational infrastructure which takes into account a mix of data of different natures, such as social and collaborative interactions, devices’ contextual constraints, and personal preferences and traits. Such architecture is composed of specialized modules which have been integrated to a real multimedia capture platform, named Classroom eXperience (CX), currently used as a complementary learning tool. Experiments using this environment have been conducted in the context of courses offered by the Faculty of Computing at the Federal University of Uberlândia to evaluate different parts of the architecture. Results pointed out to the feasibility of the LOs authoring approach in ULEs. In addition, statistically significant differences were found in students’ performance while experiencing the content personalization based on learning styles. Also, social and collaborative resources were the ones that most attracted students' attention. Finally, a LO repository with metadata in the IEEE Learning Object Metadata (IEEE-LOM) format generated by the CX platform was created to be available to the research community in Informatics in Education.