The adaptiveness provides uniquely identifying and monitoring the learner&rsquo / s learning activities according to his/her respective profile. The adaptive intelligent learning management systems (AILMS) help a wide range of students to achieve their learning goals effectively by delivering knowledge in an adaptive or individualized style through online learning settings. This study presents a multi-agent system, called MODA, developed to provide adaptiveness in learning management systems (LMS). A conceptual framework for adaptive learning systems is proposed for this purpose. The framework is based on the idea that adaptiveness is the best matching between the learner profile and the course content profile. The learning styles of learners and the content type of learning material are used to match the learner to the most suitable content. The thesis covers the pedagogical framework applied in MODA, the technical and multi-agent architectures of MODA, the TCP-IP based protocol providing communication between MODA and LMS, and a sample application of the system to an open source learning management system, OLAT. The study also discusses the possibilities of future interests.

abstract: Alternative computation based on neural systems on a nanoscale device are of increasing interest because of the massive parallelism and scalability they provide. Neural based computation systems also offer defect finding and self healing capabilities. Traditional Von Neumann based architectures (which separate the memory and computation units) inherently suffer from the Von Neumann bottleneck whereby the processor is limited by the number of instructions it fetches. The clock driven based Von Neumann computer survived because of technology scaling. However as transistor scaling is slowly coming to an end with channel lengths becoming a few nanometers in length, processor speeds are beginning to saturate. This lead to the development of multi-core systems which process data in parallel, with each core being based on the Von Neumann architecture. The human brain has always been a mystery to scientists. Modern day super computers are outperformed by the human brain in certain computations. The brain occupies far less space and consumes a fraction of the power a super computer does with certain processes such as pattern recognition. Neuromorphic computing aims to mimic biological neural systems on silicon to exploit the massive parallelism that neural systems offer. Neuromorphic systems are event driven systems rather than being clock driven. One of the issues faced by neuromorphic computing was the area occupied by these circuits. With recent developments in the field of nanotechnology, memristive devices on a nanoscale have been developed and show a promising solution. Memristor based synapses can be up to three times smaller than Complementary Metal Oxide Semiconductor (CMOS) based synapses. In this thesis, the Programmable Metallization Cell (a memristive device) is used to prove a learning algorithm known as Spike Time Dependant Plasticity (STDP). This learning algorithm is an extension to Hebb’s learning rule in which the synapses weight can be altered by the relative timing of spikes across it. The synaptic weight with the memristor will be its conductance, and CMOS oscillator based circuits will be used to produce spikes that can modulate the memristor conductance by firing with different phases differences. / Dissertation/Thesis / Masters Thesis Electrical Engineering 2015

Orientador: Elisabete Monteiro de Aguiar Pereira / Dissertação (mestrado) - Universidade Estadual de Campinas, Faculdade de Educação / Made available in DSpace on 2018-08-06T11:24:40Z (GMT). No. of bitstreams: 1 Marchese_Fabrizio_M.pdf: 971439 bytes, checksum: e1c7ef0cb04aea8c6923f71d3abfb4d1 (MD5) Previous issue date: 2006 / Resumo: trabalho procurou Este desenvolver uma reflexão acerca dos problemas curriculares e extra-curriculares vivenciados atualmente pelos cursos de graduação em Ciências Jurídicas e Sociais no Brasil, bem como, apontar possíveis contribuições a serem proporcionadas por um programa educacional com ênfase na Educação Geral. Para isso, desenvolvemos através de pesquisa documental e de legislação um resgate histórico sobre o curso de Direito desde a antiguidade, culminando com a sua introdução no país e seu desenvolvimento até os dias atuais. Por fim, estudamos o posicionamento da Ordem dos Advogados do Brasil, e a atual legislação educacional vinculada ao tema, concluindo através das contribuições que a Educação Geral poderia proporcionar para a formação do profissional do Direito / Abstract: This study developed a reflection concerning the curricular and extra-curricular problems belong currently in the Legal and Social Sciences graduation courses in Brazil, as well as pointing possible contributions to be proportionate for an educational program with emphasis in the General Education. For this, we develop through documentary and legislation research a historical rescue about law¿s course from the antiquity to achieve with its introduction in the country and its development until the current days. Finally, we study the positioning of the Brazil Lawyer Order and the current educational legislation tied with the theme, concluding through the contributions that the General Education could provide for the formation of the law¿s professional / Mestrado / Politicas de Educação e Sistemas Educativos / Mestre em Educação

Submitted by Marlene Santos (marlene.bc.ufg@gmail.com) on 2016-08-29T17:06:54Z No. of bitstreams: 2 Dissertação - Angélica Alves Bueno - 2016.pdf: 2143205 bytes, checksum: aea1150716e8689bae1d94aeafd6b556 (MD5) license_rdf: 0 bytes, checksum: d41d8cd98f00b204e9800998ecf8427e (MD5) / Approved for entry into archive by Luciana Ferreira (lucgeral@gmail.com) on 2016-08-30T11:24:14Z (GMT) No. of bitstreams: 2 Dissertação - Angélica Alves Bueno - 2016.pdf: 2143205 bytes, checksum: aea1150716e8689bae1d94aeafd6b556 (MD5) license_rdf: 0 bytes, checksum: d41d8cd98f00b204e9800998ecf8427e (MD5) / Made available in DSpace on 2016-08-30T11:24:14Z (GMT). No. of bitstreams: 2 Dissertação - Angélica Alves Bueno - 2016.pdf: 2143205 bytes, checksum: aea1150716e8689bae1d94aeafd6b556 (MD5) license_rdf: 0 bytes, checksum: d41d8cd98f00b204e9800998ecf8427e (MD5) Previous issue date: 2016-08-15 / Fundação de Amparo à Pesquisa do Estado de Goiás - FAPEG / This research aims to question elements of the Brazilian school system. The main source of questioning involves the analysis of a set of changes that the school field Catalão (GO), from 2013. We seek to understand / seize their organization and provision, establishing the relationship with the formation of the historical consciousness of the subjects it entered. The focus of our analysis was a priori the changes, the continuities and the deviations observed in the touchy and complex municipal education system. From there, it was necessary to extend the investigation to the Brazilian educational scenario, seeking to understand the formation of subjects, the proposals, the various approximations and differentiations that allowed us dialogues and comparisons, as well as to help us understand what has been the training model the new generation offered by the Brazilian government. / Esta pesquisa tem como objetivo principal problematizar elementos do sistema escolar brasileiro. A principal fonte de problematização passa pela análise de um conjunto de mudanças verificadas no campo escolar do município de Catalão (GO), a partir de 2013. Buscamos compreender/apreender sua organização e disposição, estabelecendo a relação com a formação da consciência histórica dos sujeitos nele inseridos. O foco da nossa análise foi, a priori, nas mudanças, nas permanências e nos desvios observados no melindroso e complexo sistema de educação do município. A partir daí, foi necessário alargar a investigação para o cenário educacional brasileiro, buscando apreender a formação de sujeitos, as propostas, as diversas aproximações e diferenciações que nos permitiram diálogos e comparações, além de nos ajudar a entender qual tem sido o modelo de formação das novas gerações oferecido pelo governo brasileiro.

This master thesis focuses on an exploration of digital technologies and systems used for learning interaction, specifically learning of foreign languages (FLA) and second languages acquisition (SLA) and investigates the use of autonomy-based virtual environment systems for knowledge acquisition. The study describes an enhancement of multimodal language learning practices and deployment of teaching material in an autonomous setup operated by language students. The master thesis project culminated with the creation of a language learning virtual reality system called "VR wor(l)ds" supporting oral training and vocabulary acquisition in a contextual learning environment. The VR system is intended to compensate for the loss of equal opportunities among students interacting in the traditional classroom setup. Furthermore, this concept aims to explore new opportunities for knowledge acquisition and opens up an argument for using virtual reality systems for encouraging students to actively engage with oral training and vocabulary acquisition in their language learning process. Last but not least, this project aims to open up a cross discussion between the field of interaction design (IxD) and language learning for possible collaboration on solutions to create playful environments for learning and improve learning outcomes.

Today, climate change, has become one of the greatest societal challenges of our time. This challenge requires an accurate understanding of climate change for making informed decisions regarding the environmental issues. The carbon cycle is one of the earth’s complicated cycles that has a critical role in the planet’s climate. Developing a thorough perception about this complex cycle uncovers how human activities impact the planet and reveals the connection between multiple environmental issues.Perceiving this complex cycle requires systems thinking skills that enable students to recognize components of the carbon cycle and understand the interrelating dynamic relationship between them. Establishing systems thinking skills and developing a thorough perception about the carbon cycle is a difficult matter for students. Adaptive visualisation-based tutoring systems have a great potential for facilitating teaching and learning cyclical models and systems thinking in schools. Such systems consider the students’ needs and provide personalised feedback that can guide individuals more effectively throughout the learning process. This thesis project intends to use diagrammatic visualizations, systems thinking, and adaptive tutoring systems as three technical approaches for conceptualising a learning system that aims to teach the carbon cycle. The framework of this thesis project is formed in relation to a research project called ‘Tracing Carbon’ focusing on science education for pupils on grade 7-9.

No / An adaptive iterative learning control approach is proposed for a class of single-input single-output uncertain nonlinear systems with completely unknown control gain. Unlike the ordinary iterative learning controls that require some preconditions on the learning gain to stabilize the dynamic systems, the adaptive iterative learning control achieves the convergence through a learning gain in a Nussbaum-type function for the unknown control gain estimation. This paper shows that all tracking errors along a desired trajectory in a finite time interval can converge into any given precision through repetitive tracking. Simulations are carried out to show the validity of the proposed control method.

Les problèmes de la classification ont reçu une attention considérable dans des différents champs d'ingénierie comme traitement des images biomédicales, identification a partir de la voix, reconnaissance d'empreinte digitale etc. Les techniques d'intelligence artificielles, incluant les réseaux de neurones artificiels, permettent de traiter des problèmes de ce type. En particulier, les problèmes rencontrés nécessitent la manipulation de bases de données de tailles très importantes. Des structures de traitement adaptatives et exploitant des ensembles de classificateurs sont utilisées. Dans cette thèse, nous décrivons principalement le développement et des améliorations apportées à un outil de classification désigné par le terme Tree-like Divide to Simplify ou T-DTS. Nos efforts se sont portés sur l'un des modules de cet outil, le module d'estimation de complexité. L'architecture de l'outil T-DTS est très flexible et nécessite le choix d'un nombre important de paramètres. Afin de simplifier l'exploitation de T-DTS, nous avons conçu et développé une procédure automatique d'optimisation d'un de ces plus importants paramètres, le seuil de décision associé à la mesure de complexité. La contribution principale de cette thèse concerne le développement de modules pouvant s'implanté sur une architecture de calcul matérielle parallèle. Ceci permet de se rapprocher d'une implantation purement matérielle de l'outil T-DTS / Classification problems deal with separating group of objects into sets of smaller classes; this set of problems have received considerable attention in diverse engineering fields such as biomedical imaging, speaker identification, fingerprint recognition, etc. Several effective approaches for automated classification were suggested based on artificial intelligence techniques, including neural networks. Still, one of the major challenges faced by these approaches is a large scale of data required for successful classification. In this thesis, we explore a possible solution to this problem based on a module-based Tree-like Divide to Simplify (T-DTS) classification model. We focus on enhancing the key module of this approach - complexity estimation module. Furthermore, we provide an automated procedure for optimizing key complexity estimation parameters of the T-DTS model; this considerably improves usability and allows for a more effective configuration of decomposition reasoning of the approach. Another major contribution of this work employs further development of T-DTS modules that could be implemented using parallel computer architecture, thereby allowing T-DTS to utilize an underlying hardware to the fullest extent

This thesis studies the learning process between foreign and local knowledge in a community of organic farmers by the name Atitlán Organics in Tzununa, rural Guatemala. Foreign settlers with formal education and contemporary farming experience work alongside indigenous local Guatemalan farmers in this community, which also takes on international volunteer workers. These people of various background and differing intentions cooperate to develop the community and its business of organic food production while learning from each other. The foreigners bring global theories that relate to farming such as permaculture designs and scientific knowledge while the Guatemalans know the local land and how to work with it. This thesis outlines the learning process between these different competencies and presents a nuanced discussion on how these types of knowledge exchange can be beneficial for the people and the community. Diverse competencies can complement each other and enhance collaborative work but limitations can also occur due to difficulties of understanding other socio-cultural contexts, while risks of neo-colonial tendencies and western knowledge hegemony lure in these situations. The discussion in this thesis highlights the importance of mutual consciousness about this process in the community and what that can be done to enhance collaborative learning while avoiding such risks.

Sistemas de Aprendizagem Adaptativos e Inteligentes, tema de pesquisa recente no mundo, são ambientes com arquitetura e algoritmos específicos, que consideram as características individuais de cada estudante para selecionar o objeto de aprendizagem mais adequado a ser oferecido ao aluno. O rápido desenvolvimento da infraestrutura sem fio e o amplo uso de dispositivos móveis na vida diária das pessoas motivam as pesquisas relativas ao uso desses dispositivos na educação, proporcionando o m-learning. Assim, relacionado a essas linhas de pesquisa, este trabalho propõe a arquitetura AdaptMLearning, elaborada para prover a aprendizagem em plataformas móveis e não móveis, considerando a seleção de objetos de aprendizagem que melhor se adaptam a diversos aspectos, tais como: dados sobre a tecnologia utilizada para acesso; informações sobre o estilo de aprendizagem de um estudante; desempenho e tempo associados à interação do estudante com o objeto de aprendizagem; conhecimentos adquiridos pelo estudante em consonância ao conteúdo do curso; e a garantia de que não só o professor possa configurar as adaptações a serem oferecidas ao seu curso, como também o aluno tenha a possibilidade de informar sua preferência pelos tipos de mídia. Essa arquitetura é baseada no modelo de referência AHAM para sistemas adaptativos AEHS, contemplando a quádrupla: espaço do conhecimento, modelo do usuário, observações e modelo de adaptação, referente à definição lógica desses sistemas. Na AdaptMLearning, foram desenvolvidos alguns algoritmos, utilizando-se o modelo FSLSM, relacionado aos estilos de aprendizagem de um estudante e o padrão IEEE 1484 para catalogação dos objetos de aprendizagem e uso de alguns atributos de suas categorias, associados às dimensões dos estilos de aprendizagem do modelo FSLSM. O algoritmo calcula um peso para um objeto catalogado em cada dimensão e permite uma busca pelo objeto mais adequado ao estilo do estudante, além de usar a computação fuzzy, para avaliar se o estudante pode sofrer mudanças no seu estilo, deve receber reforço ou necessita de um reestudo em determinado assunto de um curso, por meio de resultados obtidos com o tempo de estudo e desempenho. Também, este trabalho apresenta o desenvolvimento e a avaliação de um simulador para a arquitetura AdaptMLearning e seus algoritmos, realizada utilizando diversos cenários de simulação, envolvendo estudantes, cursos e tecnologias com diferentes configurações. Assim sendo, com base nos resultados obtidos por meio da avaliação, foi possível discutir, analisar e identificar o potencial de uso da AdaptMLearning e de seus algoritmos em uma situação real para elaboração de um ambiente de aprendizagem ou agregação a um ambiente existente. / Intelligent and Adaptive Learning Systems, subject of recent research in the world, are environments with specific architectures and algorithms, designed considering the individual characteristics of each student. The rapid development of wireless infrastructures and wide use of mobile devices in people\'s everyday life encourage research about the use of these devices in education, providing the mlearning. In the context of such research, this work proposes the AdaptMLearning architecture that was designed to be a learning infrastructure for mobile and nonmobile platforms. This architecture provides a selection of learning objects that takes into account as adaptation criteria the following data: the mobile device\'s technological specification; the student\'s learning style information, his/her performance and spent time associated to the student\'s interaction with the learning object; previously acquired knowledge by the student related to the course\'s content. In addition, it also allows the teacher to interfere in the adaptation criteria used during the study simulation, and allows the student to indicate his/her preferences for media types. This architecture is based on AHAM reference model for adaptive systems AEHS and uses the quadruple: the knowledge space, the user model, the observations and the model adaptation, referring to the logical definition of these systems. To implement the AdaptMLearning architecture some algorithms using the FSLSM model related to the student\'s learning styles were developed. The algorithms use the IEEE 1484 for cataloging learning objects and some of its categories and attributes associated with dimensions of learning styles FSLSM model, are used to compute a weight of an object in each dimension allowing a search of the most appropriate object according to the student\'s learning styles; and the use of fuzzy computing, considering that the student\'s learning style can change, determines if the student has to receive reinforcement or need a new study in a particular subject of a course, when the student gets unsatisfactory results in terms of timing and performance in a course\'s subject. Also, this work also presents the development and evaluation of a simulator for the AdaptMLearning architecture and their algorithms. The evaluation of the simulator was done by means of many simulations scenarios, considering students, courses and technologies with different settings. Based on the results obtained from the evaluation it was possible to discuss, analyze and identify the potential use of AdaptMLearning architecture and their algorithms in a real situation for developing a learning environment or its aggregation to an existing environment.