Mineração de dados no Moodle: análise de prazos de entrega de atividades

Detalhes bibliográficos
Ano de defesa: 2011
Autor(a) principal: Conti, Fabieli de
Orientador(a): Não Informado pela instituição
Banca de defesa: Não Informado pela instituição
Tipo de documento: Dissertação
Tipo de acesso: Acesso aberto
dARK ID: ark:/26339/001300000hdwj
Idioma: por
Instituição de defesa: Universidade Federal de Santa Maria
BR
Ciência da Computação
UFSM
Programa de Pós-Graduação em Informática
Programa de Pós-Graduação: Não Informado pela instituição
Departamento: Não Informado pela instituição
País: Não Informado pela instituição
Palavras-chave em Português:
KDD
Kdd
Link de acesso: http://repositorio.ufsm.br/handle/1/5389
Resumo: Virtual Learning Environments became common practice as a course tool for both distance and presence learning courses, as they support the communication among the parties involved. This study describes research carried out on data that were generated by the interaction with the Moodle VLE within an educational institution, with focus on the analysis of due dates and actual submission dates for assignments in the course environment. The objective of this study is to obtain relevant information about how course assignments are posted in the learning environment, to guide actions supporting the reduction of submissions after the due date or close to the deadline, and to propose a transparent and automatic approach to integrating KDD activities to the Moodle environment, where the data mining stage is restricted to the algorithms selected within this study and the results are presented in a simplified manner within the user interface in the Moodle environment. The study considers the time the assignment remained open for posting, the course to which the assignment was proposed and the actual time when the assignment was posted into the environment. It was carried out following the steps of the knowledge discovery process in databases, using the Weka tool. As a result from the KDD process performed in our database, the number of postings that were closer to the final expiry date were higher for assignments longer than 15 days, graduate courses tended to have longer assignments than undergraduate courses, and they also presented a higher number of postings after the due date or close to the expiry date of the assignments. In this context, shorter assignments are recommended, in order to increase postings soon after the opening of assignments and to enable teachers to obtain faster feedback from the learning process undergone by the student. That makes possible to take corrective actions in shorter time in order to avoid student failure or dismissal. The implementation of the KDD process within Moodle enables the experimentation by users in an automatic and simplified manner.
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spelling Mineração de dados no Moodle: análise de prazos de entrega de atividadesAnalysis of assignment submissions deadlines in Moodle: a case study using data miningAmbiente virtual de aprendizagemKDDMineração de dadosVirtual learning environmentMoodleKddData miningCNPQ::CIENCIAS EXATAS E DA TERRA::CIENCIA DA COMPUTACAOVirtual Learning Environments became common practice as a course tool for both distance and presence learning courses, as they support the communication among the parties involved. This study describes research carried out on data that were generated by the interaction with the Moodle VLE within an educational institution, with focus on the analysis of due dates and actual submission dates for assignments in the course environment. The objective of this study is to obtain relevant information about how course assignments are posted in the learning environment, to guide actions supporting the reduction of submissions after the due date or close to the deadline, and to propose a transparent and automatic approach to integrating KDD activities to the Moodle environment, where the data mining stage is restricted to the algorithms selected within this study and the results are presented in a simplified manner within the user interface in the Moodle environment. The study considers the time the assignment remained open for posting, the course to which the assignment was proposed and the actual time when the assignment was posted into the environment. It was carried out following the steps of the knowledge discovery process in databases, using the Weka tool. As a result from the KDD process performed in our database, the number of postings that were closer to the final expiry date were higher for assignments longer than 15 days, graduate courses tended to have longer assignments than undergraduate courses, and they also presented a higher number of postings after the due date or close to the expiry date of the assignments. In this context, shorter assignments are recommended, in order to increase postings soon after the opening of assignments and to enable teachers to obtain faster feedback from the learning process undergone by the student. That makes possible to take corrective actions in shorter time in order to avoid student failure or dismissal. The implementation of the KDD process within Moodle enables the experimentation by users in an automatic and simplified manner.Como ferramenta pedagógica, os Ambientes Virtuais de Aprendizagem (AVA) tornaram-se prática comum para o ensino à distância como nos cursos presenciais, por dar apoio à comunicação entre os envolvidos com o ensino. Essa dissertação descreve uma pesquisa realizada sobre os dados gerados pela interação com o AVA Moodle de uma instituição de ensino, focando a análise de prazos e de datas efetivas de submissões de tarefas neste ambiente. O objetivo deste trabalho é identificar padrões relevantes sobre a postagem de tarefas no ambiente, para subsidiar ações em auxílio à postagem muito próximo ao final do período de postagem e propor uma forma transparente e automática de integrar ao Moodle as atividades de KDD. A ferramenta de integração proposta aborta os algoritmos de mineração de dados EM e J.48, selecionados no nosso estudo e os resultados são apresentados de forma simplificada aos usuários na própria interface do Moodle. Para o estudo, são considerados o período em que a tarefa permaneceu aberta para postagem, o curso proveniente da tarefa e o período em que a postagem foi realizada. O estudo foi realizado seguindo as etapas do processo de descoberta de conhecimento, com a utilização da ferramenta Weka. No estudo observou-se a incidência do número de postagens mais próximas ao término do tempo de postagem quando o prazo da mesma era superior a 15 dias. Nos cursos de pós-graduação, observa-se que o tempo para postagem é maior que nos cursos de nível superior e que esse nível apresenta maior quantidade de postagem sendo realizadas no final do prazo de postagem. Nesse contexto, é mais viável a realização de atividades com um prazo menor. Além de um maior número de submissões logo na abertura para postagem, o professor consegue feedback mais rápido do processo de aprendizagem do aluno. Isso possibilita tomar atitudes corretivas em tempo mais adequado a fim de evitar o insucesso ou desistência do aluno. Com a implementação da integração do KDD ao Moodle é possível a realização de experimentos por usuários de forma automática e simplificada.Universidade Federal de Santa MariaBRCiência da ComputaçãoUFSMPrograma de Pós-Graduação em InformáticaCharao, Andrea Schwertnerhttp://lattes.cnpq.br/8251676116103188Dorneles, Ricardo Vargashttp://lattes.cnpq.br/5862460242840326Medina, Roseclea Duartehttp://lattes.cnpq.br/6560346309368052Conti, Fabieli de2012-09-122012-09-122011-12-19info:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/masterThesisapplication/pdfapplication/pdfCONTI, Fabieli de. ANALYSIS OF ASSIGNMENT SUBMISSIONS DEADLINES IN MOODLE: A CASE STUDY USING DATA MINING. 2011. 69 f. Dissertação (Mestrado em Ciência da Computação) - Universidade Federal de Santa Maria, Santa Maria, 2011.http://repositorio.ufsm.br/handle/1/5389ark:/26339/001300000hdwjporinfo:eu-repo/semantics/openAccessreponame:Manancial - Repositório Digital da UFSMinstname:Universidade Federal de Santa Maria (UFSM)instacron:UFSM2022-05-06T14:53:13Zoai:repositorio.ufsm.br:1/5389Biblioteca Digital de Teses e Dissertaçõeshttps://repositorio.ufsm.br/PUBhttps://repositorio.ufsm.br/oai/requestatendimento.sib@ufsm.br||tedebc@gmail.com||manancial@ufsm.bropendoar:2022-05-06T14:53:13Manancial - Repositório Digital da UFSM - Universidade Federal de Santa Maria (UFSM)false
dc.title.none.fl_str_mv Mineração de dados no Moodle: análise de prazos de entrega de atividades
Analysis of assignment submissions deadlines in Moodle: a case study using data mining
title Mineração de dados no Moodle: análise de prazos de entrega de atividades
spellingShingle Mineração de dados no Moodle: análise de prazos de entrega de atividades
Conti, Fabieli de
Ambiente virtual de aprendizagem
KDD
Mineração de dados
Virtual learning environment
Moodle
Kdd
Data mining
CNPQ::CIENCIAS EXATAS E DA TERRA::CIENCIA DA COMPUTACAO
title_short Mineração de dados no Moodle: análise de prazos de entrega de atividades
title_full Mineração de dados no Moodle: análise de prazos de entrega de atividades
title_fullStr Mineração de dados no Moodle: análise de prazos de entrega de atividades
title_full_unstemmed Mineração de dados no Moodle: análise de prazos de entrega de atividades
title_sort Mineração de dados no Moodle: análise de prazos de entrega de atividades
author Conti, Fabieli de
author_facet Conti, Fabieli de
author_role author
dc.contributor.none.fl_str_mv Charao, Andrea Schwertner
http://lattes.cnpq.br/8251676116103188
Dorneles, Ricardo Vargas
http://lattes.cnpq.br/5862460242840326
Medina, Roseclea Duarte
http://lattes.cnpq.br/6560346309368052
dc.contributor.author.fl_str_mv Conti, Fabieli de
dc.subject.por.fl_str_mv Ambiente virtual de aprendizagem
KDD
Mineração de dados
Virtual learning environment
Moodle
Kdd
Data mining
CNPQ::CIENCIAS EXATAS E DA TERRA::CIENCIA DA COMPUTACAO
topic Ambiente virtual de aprendizagem
KDD
Mineração de dados
Virtual learning environment
Moodle
Kdd
Data mining
CNPQ::CIENCIAS EXATAS E DA TERRA::CIENCIA DA COMPUTACAO
description Virtual Learning Environments became common practice as a course tool for both distance and presence learning courses, as they support the communication among the parties involved. This study describes research carried out on data that were generated by the interaction with the Moodle VLE within an educational institution, with focus on the analysis of due dates and actual submission dates for assignments in the course environment. The objective of this study is to obtain relevant information about how course assignments are posted in the learning environment, to guide actions supporting the reduction of submissions after the due date or close to the deadline, and to propose a transparent and automatic approach to integrating KDD activities to the Moodle environment, where the data mining stage is restricted to the algorithms selected within this study and the results are presented in a simplified manner within the user interface in the Moodle environment. The study considers the time the assignment remained open for posting, the course to which the assignment was proposed and the actual time when the assignment was posted into the environment. It was carried out following the steps of the knowledge discovery process in databases, using the Weka tool. As a result from the KDD process performed in our database, the number of postings that were closer to the final expiry date were higher for assignments longer than 15 days, graduate courses tended to have longer assignments than undergraduate courses, and they also presented a higher number of postings after the due date or close to the expiry date of the assignments. In this context, shorter assignments are recommended, in order to increase postings soon after the opening of assignments and to enable teachers to obtain faster feedback from the learning process undergone by the student. That makes possible to take corrective actions in shorter time in order to avoid student failure or dismissal. The implementation of the KDD process within Moodle enables the experimentation by users in an automatic and simplified manner.
publishDate 2011
dc.date.none.fl_str_mv 2011-12-19
2012-09-12
2012-09-12
dc.type.status.fl_str_mv info:eu-repo/semantics/publishedVersion
dc.type.driver.fl_str_mv info:eu-repo/semantics/masterThesis
format masterThesis
status_str publishedVersion
dc.identifier.uri.fl_str_mv CONTI, Fabieli de. ANALYSIS OF ASSIGNMENT SUBMISSIONS DEADLINES IN MOODLE: A CASE STUDY USING DATA MINING. 2011. 69 f. Dissertação (Mestrado em Ciência da Computação) - Universidade Federal de Santa Maria, Santa Maria, 2011.
http://repositorio.ufsm.br/handle/1/5389
dc.identifier.dark.fl_str_mv ark:/26339/001300000hdwj
identifier_str_mv CONTI, Fabieli de. ANALYSIS OF ASSIGNMENT SUBMISSIONS DEADLINES IN MOODLE: A CASE STUDY USING DATA MINING. 2011. 69 f. Dissertação (Mestrado em Ciência da Computação) - Universidade Federal de Santa Maria, Santa Maria, 2011.
ark:/26339/001300000hdwj
url http://repositorio.ufsm.br/handle/1/5389
dc.language.iso.fl_str_mv por
language por
dc.rights.driver.fl_str_mv info:eu-repo/semantics/openAccess
eu_rights_str_mv openAccess
dc.format.none.fl_str_mv application/pdf
application/pdf
dc.publisher.none.fl_str_mv Universidade Federal de Santa Maria
BR
Ciência da Computação
UFSM
Programa de Pós-Graduação em Informática
publisher.none.fl_str_mv Universidade Federal de Santa Maria
BR
Ciência da Computação
UFSM
Programa de Pós-Graduação em Informática
dc.source.none.fl_str_mv reponame:Manancial - Repositório Digital da UFSM
instname:Universidade Federal de Santa Maria (UFSM)
instacron:UFSM
instname_str Universidade Federal de Santa Maria (UFSM)
instacron_str UFSM
institution UFSM
reponame_str Manancial - Repositório Digital da UFSM
collection Manancial - Repositório Digital da UFSM
repository.name.fl_str_mv Manancial - Repositório Digital da UFSM - Universidade Federal de Santa Maria (UFSM)
repository.mail.fl_str_mv atendimento.sib@ufsm.br||tedebc@gmail.com||manancial@ufsm.br
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