Submitted by Jos? Henrique Henrique (jose.neves@ufvjm.edu.br) on 2017-05-09T18:11:27Z No. of bitstreams: 2 license_rdf: 0 bytes, checksum: d41d8cd98f00b204e9800998ecf8427e (MD5) edson_batista_sena.pdf: 2251476 bytes, checksum: 028f563476a851ba89cf53a932fe2ba7 (MD5) / Approved for entry into archive by Rodrigo Martins Cruz (rodrigo.cruz@ufvjm.edu.br) on 2017-05-16T18:51:42Z (GMT) No. of bitstreams: 2 license_rdf: 0 bytes, checksum: d41d8cd98f00b204e9800998ecf8427e (MD5) edson_batista_sena.pdf: 2251476 bytes, checksum: 028f563476a851ba89cf53a932fe2ba7 (MD5) / Made available in DSpace on 2017-05-16T18:51:42Z (GMT). No. of bitstreams: 2 license_rdf: 0 bytes, checksum: d41d8cd98f00b204e9800998ecf8427e (MD5) edson_batista_sena.pdf: 2251476 bytes, checksum: 028f563476a851ba89cf53a932fe2ba7 (MD5) Previous issue date: 2016 / Um dos grandes desafios dos dias atuais no desenvolvimento de tecnologias computacionais aplicadas ao processo educacional ? produzir solu??es que sejam capazes de atender corretamente ao processo de ensino e aprendizagem, al?m de definir a forma mais adequada de incorporar esses mecanismos no ambiente escolar. Esta inser??o deve ocorrer de forma que alunos e professores aproveitem ao m?ximo esses instrumentos, e passem a utiliz?-los com o intuito de agregar mais valor aos processos de ensino e aprendizagem. Para que isso ocorra, ? fundamental que os ambientes virtuais forne?am conte?do adequado, objetos de aprendizagem atraentes, al?m de serem din?micos e altamente adapt?veis ?s necessidades e interesses dos estudantes durante as sess?es de aprendizagem, visando a melhoria cont?nua do processo educacional para professores, tutores e estudantes. O presente trabalho tem como objetivo principal apresentar um modelo computacional probabil?stico, que pode ser incorporado ?s estruturas dos ambientes virtuais de aprendizagem, a fim de auxiliar no processo de detec??o autom?tica das tend?ncias e prefer?ncias dos estilos de aprendizagem do estudante, utilizando uma combina??o do modelo proposto por Felder e Silverman para estilos de aprendizagem, o FSLSM, com as t?cnicas de infer?ncia probabil?stica dos modelos ocultos de Markov (HMM). Para a valida??o do modelo, foram realizados experimentos em um simulador computacional capaz de reproduzir parcialmente o processo de intera??o do estudante com o ambiente virtual de aprendizagem, realizando um processo de infer?ncia com base no comportamento do estudante, ao qual foi utilizado o algoritmo de Viterbi para este prop?sito. Ao final, os resultados dos experimentos s?o apresentados e demonstraram um elevado grau de precis?o no processo de infer?ncia do estilo de aprendizagem probabil?stico. / Disserta??o (Mestrado Profissional) ? Programa de P?s-Gradua??o em Educa??o, Universidade Federal dos Vales do Jequitinhonha e Mucuri, 2016. / The great challenges of the present day in the development of computer technologies in educational process is to produce solutions that are able to respond properly to the teaching and learning methods, and define the most appropriate way to incorporate these mechanisms at school. This integration should take place so that students and teachers make the most of these instruments, and start to use them in order to add more value to teaching and learning processes. For this to happen, it is critical that virtual environments provide appropriate content, appealing learning objects, and are dynamic and highly adaptable to the needs and interests of students during the learning sessions, aimed at continuous improvement of the educational process for teachers, tutors and student. This study aims to present a probabilistic computational model, which can be incorporated into the structures of virtual learning environments, auxiliary order in the automatic detection process of the trends and preferences of student learning styles using a combination of the proposed model by Felder and Silverman to learning styles the FSLSM, with the probabilistic inference techniques of hidden Markov models (HMM). To validate the model, experiments were performed on a computer simulator able to partially reproduce the student interaction process with the virtual learning environment, making an inference process based on the student?s behavior, where we used the Viterbi algorithm to this purpose. At the end, the results of the experiments are presented and demonstrated a high degree precision in the process of inference of probabilistic learning style.

This study explores the use of computer simulations to supplement learning in Science lessons, specifically the photoelectric effect. This study uses the Felder and Silverman Learning Style Model (FSLSM) as a theoretical framework to investigate the use of simulations as it provides a useful lens through which to explore the consistent way in which a person learns regardless of the teaching method or content learnt. Using this theoretical framework, this research investigates the experiences of learners with different learning styles when an interactive computer simulation is used to aid teaching the photoelectric effect in Physical Science. This case study used qualitative data collected from 17 computer literate Grade 12 learners in three different classes at a secondary school in Nelspruit, Mpumalanga. Analysis of the data collected in this study shows that when the simulation is used in Science, the learning experience of the learners is enhanced. Positive experiences for all four the Dimensions in the FSLSM could be indentified when the ICS was used and this could be linked to specific learning styles. Sensory and Intuitive learners enjoyed conducting the experiment that would normally require unsafe conditions and that the experiment could be set up quickly and with ease. The different dimension brought about by using the ICS was enjoyed by Intuitive learners. The visualisation of the abstract physical systems enhanced the learning for Visual and Verbal learners, whilst Global and Sequential learners felt that they gained a deeper understanding of the photoelectric phenomenon by using the ICS. Reflective learners enjoyed the precision of their pseudo-experimental data, but the Active learners felt that they did not understand the graphs given in the ICS. The interactive control variables and the fact that the learners had an option to work in either a group or on their own, benefitted both Active and Reflective learners. / Dissertation (MEd)--University of Pretoria, 2014. / gm2014 / Science, Mathematics and Technology Education / unrestricted

This study explores the use of computer simulations to supplement learning in Science lessons, specifically the photoelectric effect. This study uses the Felder and Silverman Learning Style Model (FSLSM) as a theoretical framework to investigate the use of simulations as it provides a useful lens through which to explore the consistent way in which a person learns regardless of the teaching method or content learnt. Using this theoretical framework, this research investigates the experiences of learners with different learning styles when an interactive computer simulation is used to aid teaching the photoelectric effect in Physical Science. This case study used qualitative data collected from 17 computer literate Grade 12 learners in three different classes at a secondary school in Nelspruit, Mpumalanga. Analysis of the data collected in this study shows that when the simulation is used in Science, the learning experience of the learners is enhanced. Positive experiences for all four the Dimensions in the FSLSM could be indentified when the ICS was used and this could be linked to specific learning styles. Sensory and Intuitive learners enjoyed conducting the experiment that would normally require unsafe conditions and that the experiment could be set up quickly and with ease. The different dimension brought about by using the ICS was enjoyed by Intuitive learners. The visualisation of the abstract physical systems enhanced the learning for Visual and Verbal learners, whilst Global and Sequential learners felt that they gained a deeper understanding of the photoelectric phenomenon by using the ICS. Reflective learners enjoyed the precision of their pseudo-experimental data, but the Active learners felt that they did not understand the graphs given in the ICS. The interactive control variables and the fact that the learners had an option to work in either a group or on their own, benefitted both Active and Reflective learners. / Dissertation (MEd)--University of Pretoria, 2013. / gm2014 / Science, Mathematics and Technology Education / unrestricted

Submitted by Jos? Henrique Henrique (jose.neves@ufvjm.edu.br) on 2017-01-09T12:21:59Z No. of bitstreams: 2 license_rdf: 0 bytes, checksum: d41d8cd98f00b204e9800998ecf8427e (MD5) andre_vinicius_gon?alves.pdf: 1266538 bytes, checksum: 42c3fe90b9d66c8cb7b901a10e548f1b (MD5) / Approved for entry into archive by Rodrigo Martins Cruz (rodrigo.cruz@ufvjm.edu.br) on 2017-01-31T13:56:36Z (GMT) No. of bitstreams: 2 license_rdf: 0 bytes, checksum: d41d8cd98f00b204e9800998ecf8427e (MD5) andre_vinicius_gon?alves.pdf: 1266538 bytes, checksum: 42c3fe90b9d66c8cb7b901a10e548f1b (MD5) / Made available in DSpace on 2017-01-31T13:56:36Z (GMT). No. of bitstreams: 2 license_rdf: 0 bytes, checksum: d41d8cd98f00b204e9800998ecf8427e (MD5) andre_vinicius_gon?alves.pdf: 1266538 bytes, checksum: 42c3fe90b9d66c8cb7b901a10e548f1b (MD5) Previous issue date: 2016-06 / Nos ?ltimos dez anos muitos pesquisadores t?m realizado estudos sobre assist?ncia personalizada e inteligente em Ambientes Educacionais a Dist?ncia, baseada na identifica??o dos Estilos de Aprendizagem. Sabe-se que o aprendizado ? algo extremamente particular, pois cada estudante possui estilos pr?prios e pode sofrer mudan?as diante de situa??es diversas como, por exemplo, objetivo, motiva??o, personalidade, etc. Por isso, o conceito de adaptabilidade do conte?do did?tico tem se tornado de grande import?ncia na personaliza??o do Sistema de Gerenciamento de Aprendizagem (SGA). Diante desse fato, Dor?a (2012) prop?e uma abordagem de Sistema Adaptativo e Inteligente para Educa??o (SAIE), utilizando t?cnicas probabil?sticas e Intelig?ncia Artificial (IA), capaz de detectar e adaptar, de maneira din?mica e autom?tica, os estilos de aprendizagem do estudante, considerando o Modelo de Estilo de Aprendizagem Felder-Silverman?s. Ap?s pesquisa detalhada, foram propostas algumas adapta??es baseadas na abordagem original, alterando o funcionamento de dois componentes espec?ficos: o M?dulo Pedag?gico e o Componente de Modelagem do Estudante. Al?m disso, prop?e-se uma nova estrutura do Modelo Estudante, contemplando o hist?rico de desempenho do aluno nos processos avaliativos. Por conseguinte, realizaram-se testes para avaliar os impactos de tais mudan?as por meio uma compara??o estat?stica utilizando o m?todo T-Pareado. Pelos resultados obtidos, as ideias deste trabalho proporcionaram uma melhora m?dia de 6,07% no desempenho avaliativo do estudante e uma redu??o m?dia de 68,27% nos problemas de aprendizagem, demonstrando efici?ncia e efic?cia da proposta. / Disserta??o (Mestrado Profissional) ? Programa de P?s-Gradua??o em Educa??o, Universidade Federal dos Vales do Jequitinhonha e Mucuri, 2015. / Since last decade many researchers have been conducting studies on personalized and intelligent assistance in distance education based on identification of learning styles. It is known that learning is something very particular because each student has their own styles and are subject to change on a variety of situations such as goal, motivation, personality, etc. Therefore, this study discusses the concept of adaptability of educational content as a way to provide customization of Learning Management System (LMS). Through probabilistic techniques and Artificial Intelligence (AI), Dor?a (2012) proposed a approach Adaptive and Intelligent System for Education (AIES) able to dynamically and automatically detect, select and adapt learning objects based on the student?s profile through Felder-Silverman Learning Styles Model (FSLSM). After detailed study, it has been proposed some adaptations based on this approach, thereby altering the operation of two specific components: the Pedagogical Module and the Student Modeling Component. In addition, it is proposed a new structure Model Student, considering learner performance history in the evaluation processes. Therefore, it carried out tests to assess the impacts of such changes through a statistical comparison by T-Paired method. From the results, the ideas in this work provides an average improvement of 6.07% in the performance evaluation of the student and an average reduction of 68.27% in the learning problems, demonstrating proposal of efficiency and effectiveness.