Philosophiae Doctor - PhD / This study attempts to understand how distance education practices influence the learning of calculus. Understanding student learning in a distance education environment is an important factor to consider in improving the learning experiences of those students who for one reason or the other opt not to study in conventional institutions of higher education. On one hand, understanding student learning may illuminate the influences that the learning environment has on student learning and on the other hand, it may inform on how learning experiences can be improved. The aim of this study is to acquire a deeper understanding of the diverse manner in which distance students learn calculus. Specific focus is also placed on how the distance education context of the Zimbabwe Open University (ZOU) influences student learning. The study describes a group of students' experiences of learning calculus in the ZOU distance education environment. The study also describes the students' learning styles and relates these to their mathematical understanding of certain calculus concepts. The specific content topics of "limit of function" and "derivative of function" are used to view achievement and performance, thereby indicating the distance students' mathematical understanding. The information processing learning theory is used as the theoretical framework for this study. The constructs of learning styles and mathematical understanding are used to illuminate the student's learning processes. The study used the Felder-Silverman learning styles model and Hiebert and Carpenter's notion of mathematical understanding to expound these constructs. The distance education environment of the B.Sc. Mathematics and Statistics (BSMS) programme at the ZOU provided the context of the study and an interpretive case study approach was adopted. A group of students registered in a first year first semester calculus course were studied. Data were collected from students based in four ZOU regional centres; namely Harare, Mashonaland Central, Mashonaland West, and Masvingo. These regional centres were conveniently selected for the study on the basis of proximity and accessibility. A total sample of twenty six students was involved and data for the in-depth part of the study emanated from five students who were purposively selected to participate in interviews. The interviewees were selected on the basis of their performance in a written calculus test. Data for this study were collected through use of learning journals, learning styles preference questionnaires, calculus tests and interviews. The data on students' learning experiences were predominantly qualitative in nature though supported by some quantitative data. The data on learning styles and mathematical understanding were also qualitatively analysed and presented case by case for the five interviewees. The study established that in a distance education system, the type of learning environment has the potential to influence students' learning, both positively and negatively, of which the main contributing factor is the learning support system. The study found that the learning support system provided by the institution and distance educators can have an impact on student learning. With reference to the calculus course in the BSMS programme, the study identified specific aspects where the environment facilitated or deterred learning. The study also revealed that students have varied learning style preferences, and that the learning environment has the potential to impact on students' learning styles. Since learning styles occupy a central place when it comes to improving distance learning materials, the study further explored the relationship between the constructs of learning styles and mathematical understanding. The study revealed that students' learning styles can influence the students' mathematical understanding. Improving students' learning in a distance education environment rests mainly on improving the learning materials and the support systems. A carefully designed and well supported instructional distance learning package can facilitate learning. Implications of the findings point towards the improvement of the distance teaching processes through the improvement of learning materials and the learning support systems for the BSMS distance education programme.

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.