Márcia A. Fernandes

A multiagent architecture for distance education systems

We describe a multiagent architecture for Web-based distance education systems that presents characteristics of intelligence and adaptability. This architecture is based on techniques of distributed artificial intelligence, planning and intelligent tutoring systems. As a result, the system allows adaptation of a given course to different types of students.

Automatic student modeling in adaptive educational systems through probabilistic learning style combinations: a qualitative comparison between two innovative stochastic approaches

Considering learning and how to improve students’ performances, adaptive educational systems must know the way in which an individual student learns best. In this context, this work presents a comparison between two innovative approaches to automatically detect and precisely adjust students’ learning styles during an adaptive course. These approaches take into account the nondeterministic and nonstationary aspects of learning styles. They are based upon two stochastic techniques: Markov chains and genetic algorithms. We found that the genetic algorithm (GA) based approach detects learning styles earlier and consequently provides personalized content earlier, making the learning process easier. The Markov based approach produces more fine-tuned results, taking into account strengths of learning styles.

Adaptative Instructional Planning Using Workflow and Genetic Algorithms

Many systems of distance learning do not consider the particular characteristics of the student and the same pedagogical strategies and content sequences are used for every student. But, the course can be customized by the introduction of adaptability in these systems. In order to develop adaptative systems of distance learning, it is necessary to consider the problems: instructional planning and the student model. The first problem allows to generate a specific sequence of content for each student and the second one provides the necessary information to cope with adaptativity.Planning techniques in Artificial Intelligence have been successfully used for determining the sequence of instructional actions. The Workflow technology has been used for the management of these systems. Then, this paper presents an adaptative instructional planning and a student model based on theories of cognitive levels and learning styles.

Detecção e Correção Automática de Estilos de Aprendizagem em Sistemas Adaptativos para Educação

Um dos aspectos mais importantes em sistemas adaptativos para educacaoe a capacidade de prover personalizacao de acordo com as necessidades especificasde cada estudante. Neste contexto, este trabalho apresenta uma abordagem promissorapara deteccao e correcao automatica de estilos de aprendizagem (EA) baseadaem cadeias de Markov. A maioria dos trabalhos nesta area apresentam abordagenscomplexas e ineficientes em algum aspecto. Alem disto, a abordagem apresentadaneste trabalho tem como vantagem tornar possivel aos estudantes o desenvolvimentode novas capacidades cognitivas, sendo baseada na combinacao de estilos de aprendizagem(CEA) e na correcao dinâmica de possiveis inconsistencias no modelo do estudante(ME), levando em consideracao o forte aspecto nao-deterministico do processode ensino-aprendizagem. Resultados promissores foram obtidos nos testes realizadoscom esta abordagem e sao discutidos neste trabalho.

Development of Learning Styles and Multiple Intelligences through Particle Swarm Optimization

Adaptivity is an important aspect in computer based educational environments and one where the building of automated and intelligent systems that support it has been a challenge. In fact, the automatic detection of the pedagogical traits in order to construct a student model that allows inference of the next step in the learning process has been one of the main goals when producing adaptive systems. Learning styles and multiple intelligence theories have been widely used in student modeling to show how a student ad quires knowledge and highlights special learning abilities. Through the bringing together of these two areas of learning a picture of an individual student can be made. This information therefore becomes useful for a tutor to adapt the learning process to the student. It is therefore within this context that this study proposes an innovative method that is driven by the Kolb learning process in order to improve the intelligence percentages by bringing out in each individual those areas in which they excel, but also help in the improvement of the learning process where deficiency is detected. Thus, this method is able to detect and correct automatically the initial self-evaluation. The selection of learning objects during the learning process is carried out by a particle swarm algorithm.

Experimental and theoretical analyses of memory allocation algorithms

In this paper, we present an experimental study to compare six user-level memory allocators. In addition, we compare the experimental results with the asymptotic analyses of the evaluated algorithms. The experimental results show that parallelism affects negatively the investigated allocators. The theoretical analysis of the execution time demonstrated that all evaluated allocators show linear complexity with respect to the number of allocations.

Adaptivity and interoperability in e-learning using ontologies

Adaptive systems in the field of e-learning are those capable of adapting the content and mode of presentation according to the profile of a particular user or user group. These systems generally remain in the context of academic research and are rarely used in real situations. Moreover, the e-learning environments that present a complete platform of tools and resources available are largely used by educational institutions, but are not adaptive. We propose to integrate these two types of systems, aiming to take advantage of both - adaptivity coupled with the scope of use of e-learning environments. Therefore, we describe the implementation of an agent that integrates an intelligent adaptive system with the e-learning environment Moodle. Furthermore, we design and implement an adaptive system based on ontologies and e-learning standards. We hope to contribute to making e-learning environments best suited to provide meaningful learning, as well as to facilitate the creation of courses.

Consistent Evolution of Student Models by Automatic Detection of Learning Styles

One of the most important features of adaptative e-learning systems is the personalisation according to specific requirements of each individual student. In considering learning and how to improve student learning, these systems must know the way in which an individual learns. In this context, we introduce a new approach for consistent evolution of student models by automatic detection of student learning styles. Most of the work in this field presents complex and inefficient approachs. Our approach is based on learning styles combination and dynamic correction of inconsistencies in the student model, taking into account the non-deterministic aspect of the learning process. Promising results were obtained from tests, and some of them are discussed in this paper.

Uma proposta de um modelo computacional que usa PSO para a escolha de Objetos de Aprendizagem baseado na Espiral de Kolb e nas Inteligências Múltiplas

The keynotes goal is to reflect on emergent opportunities for human Discovery (in science), Creativity (in art & industry), and Learning (in education) as processes often occurring serendipitously in individuals and in communities empowered by dynamic Web connections in the global village. These reflections seem to fit best with the mandate of the CBIE Conference: sustainable education.Este trabalho apresenta uma evolucao do assistente inteligente SAE para inferir e fornecer orientacao pedagogica coerente com varias metodologias educacionais, superando uma dificuldade tradicional para este tipo de software, alem de fornecer mais apoio ao ensino-aprendizagem personalizado.O artigo fundamenta-se nos resultados do processo de desenvolvimento de um ambiente web de aprendizagem, ja modelado em dissertacao de mestrado (CABRAL,2006). O sistema tem por objetivo facilitar o acompanhamento das atividades que envolvem a definicao e a elaboracao de pre-projetos de Trabalhos de Conclusao de Curso (TCC). Para atingir tal objetivo o sistema e baseado em uma camada de agentes inteligentes que atuam como colaboradores para execucao de todas as atividades necessarias ao desenvolvimento do TCC. Para que esses agentes atuem de forma satisfatoria no ambiente e necessario o estabelecimento de um processo de comunicacao que possibilite aos agentes agirem em um nivel conceitual mais proximo do ser humano. Dessa forma, este artigo expoe os resultados obtidos ao longo do desenvolvimento dos agentes computacioniais e seus mecanismos de comunicacao.Este artigo descreve o projeto de desenvolvimento de jogo educativo baseado em metodologias participativas, pelas quais estudantes da rede publica de ensino medio idealizam, projetam e desenvolvem prototipos de um jogo sobre Sistema Imunologico e virus da Dengue. O objetivo da pesquisa e verificar os impactos do processo sobre a aprendizagem dos estudantes.O objetivo deste artigo e apresentar resultados de estudo de um caso exploratorio, realizado junto aos alunos de uma Instituicao de Ensino Superior. Como resultados, foram levantados indicadores de avaliacao do Sistema de EaD e identificados problemas, segundo a percepcao dos alunos. A partir dos resultados destaca-se que a Universidade desconhece a metodologia ITIL® e que seria fundamental que fosse implantada uma estrategia do servico (fase inicial da ITIL®), conduzindo a melhoria continua do servico e da infra-estrutura da Universidade.O facil acesso as informacoes devido a difusao da internet possibilita o enriquecimento intelectual, mas por vezes acaba por ser um meio de usufruir do conhecimento de outrem sem mencionar seus creditos/direitos autorais, o que por fim acaba na configuracao do plagio. O plagio no meio academico e uma tarefa dificil de ser controlada, devido o grande numero de trabalhos que sao feitos por uma vasta quantidade de alunos e tambem pelo excesso de tarefas dos professores e pelo pouco tempo que conseguem dedicar para o controle da qualidade e autenticidade dos trabalhos. Com isso, e importante contar com softwares que auxiliem no processo de verificacao de indicios de plagio, desta maneira o presente trabalho vislumbra desenvolver uma nova ferramenta de analise de indicios de plagio bem como aprimorar o metodo DIP – Detector de Indicios de Plagio para auxiliar o docente na verificacao da autenticidade dos trabalhos.A Neuropedagogia promove o confronto sucessivo e simultâneo entre concepcoes tacitas, crencas e valores normativos com esquemas inovadores, criando um espaco entropico e poetico no âmbito da experiencia humana. A natureza da ciencia neuropedagogica exige um modelo fractal de construcao de mundo, sustentado pelo prazer da perplexidade. Busca-se a geratriz e as leis de formacao para atingir a unanimidade sobre o conceito de educacao de pessoas com alta dotacao humana, impossivel de se concretizar, sem o recurso das ideologias filosoficas, cientificas e tecnologias aliadas as eticas.In this talk I will elaborate on the development, implementation and evaluation of the use of online tools for learning, with special attention to games and gamification, sharing and collaboration.

A Comprehensive Complexity Analysis of User-Level Memory Allocator Algorithms

Memory allocations are one of the most frequently used operations in computer programs. The performance of memory allocation operations is a critical factor in software design; however, it is very often neglected. In this paper, we present a comprehensive complexity analysis of widely adopted user-level memory allocator algorithms. We consider time and space complexity, as well as the allocator overhead. The results show that the Ptmalloc family of memory allocator algorithms outperformed all other investigated allocators in terms of theoretical time complexity and space overhead. All allocators showed the same space complexity.