Mineração de dados no Moodle: análise de prazos de entrega de atividades
Ano de defesa: | 2011 |
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Autor(a) principal: | |
Orientador(a): | |
Banca de defesa: | , |
Tipo de documento: | Dissertação |
Tipo de acesso: | Acesso aberto |
Idioma: | por |
Instituição de defesa: |
Universidade Federal de Santa Maria
|
Programa de Pós-Graduação: |
Programa de Pós-Graduação em Informática
|
Departamento: |
Ciência da Computação
|
País: |
BR
|
Palavras-chave em Português: | |
Palavras-chave em Inglês: | |
Área do conhecimento CNPq: | |
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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2012-09-122012-09-122011-12-19CONTI, 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/1/5389Virtual 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.application/pdfporUniversidade Federal de Santa MariaPrograma de Pós-Graduação em InformáticaUFSMBRCiência da ComputaçãoAmbiente virtual de aprendizagemKDDMineração de dadosVirtual learning environmentMoodleKddData miningCNPQ::CIENCIAS EXATAS E DA TERRA::CIENCIA DA COMPUTACAOMineração de dados no Moodle: análise de prazos de entrega de atividadesAnalysis of assignment submissions deadlines in Moodle: a case study using data mininginfo:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/masterThesisCharao, Andrea Schwertnerhttp://lattes.cnpq.br/8251676116103188Dorneles, Ricardo Vargashttp://lattes.cnpq.br/5862460242840326Medina, Roseclea Duartehttp://lattes.cnpq.br/6560346309368052http://lattes.cnpq.br/3996506468479772Conti, Fabieli de100300000007400300300300300aac57e3e-0ef6-44db-8eb8-463a52aa902d7bb60bd6-acb6-46de-b92f-393afe71de4dc98b9438-d958-4839-a7a9-1bbc1db90e42ab954bac-27b8-46ae-a94d-e65ff0299dfeinfo:eu-repo/semantics/openAccessreponame:Biblioteca Digital de Teses e Dissertações do UFSMinstname:Universidade Federal de Santa Maria (UFSM)instacron:UFSMORIGINALDE CONTI, FABIELI.pdfapplication/pdf2595798http://repositorio.ufsm.br/bitstream/1/5389/1/DE%20CONTI%2c%20FABIELI.pdf5ae22c90e517c74561d7154d8a9ca1b5MD51TEXTDE CONTI, FABIELI.pdf.txtDE CONTI, FABIELI.pdf.txtExtracted texttext/plain109366http://repositorio.ufsm.br/bitstream/1/5389/2/DE%20CONTI%2c%20FABIELI.pdf.txte3bd0349e1d01a4534f65ba3bd529573MD52THUMBNAILDE CONTI, FABIELI.pdf.jpgDE CONTI, FABIELI.pdf.jpgIM Thumbnailimage/jpeg4578http://repositorio.ufsm.br/bitstream/1/5389/3/DE%20CONTI%2c%20FABIELI.pdf.jpg6e1266c62f413a59522b23eb116df2cbMD531/53892022-05-06 11:53:13.703oai:repositorio.ufsm.br:1/5389Biblioteca Digital de Teses e Dissertaçõeshttps://repositorio.ufsm.br/ONGhttps://repositorio.ufsm.br/oai/requestatendimento.sib@ufsm.br||tedebc@gmail.comopendoar:2022-05-06T14:53:13Biblioteca Digital de Teses e Dissertações do UFSM - Universidade Federal de Santa Maria (UFSM)false |
dc.title.por.fl_str_mv |
Mineração de dados no Moodle: análise de prazos de entrega de atividades |
dc.title.alternative.eng.fl_str_mv |
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.advisor1.fl_str_mv |
Charao, Andrea Schwertner |
dc.contributor.advisor1Lattes.fl_str_mv |
http://lattes.cnpq.br/8251676116103188 |
dc.contributor.referee1.fl_str_mv |
Dorneles, Ricardo Vargas |
dc.contributor.referee1Lattes.fl_str_mv |
http://lattes.cnpq.br/5862460242840326 |
dc.contributor.referee2.fl_str_mv |
Medina, Roseclea Duarte |
dc.contributor.referee2Lattes.fl_str_mv |
http://lattes.cnpq.br/6560346309368052 |
dc.contributor.authorLattes.fl_str_mv |
http://lattes.cnpq.br/3996506468479772 |
dc.contributor.author.fl_str_mv |
Conti, Fabieli de |
contributor_str_mv |
Charao, Andrea Schwertner Dorneles, Ricardo Vargas Medina, Roseclea Duarte |
dc.subject.por.fl_str_mv |
Ambiente virtual de aprendizagem KDD Mineração de dados |
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 |
dc.subject.eng.fl_str_mv |
Virtual learning environment Moodle Kdd Data mining |
dc.subject.cnpq.fl_str_mv |
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.issued.fl_str_mv |
2011-12-19 |
dc.date.accessioned.fl_str_mv |
2012-09-12 |
dc.date.available.fl_str_mv |
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.citation.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. |
dc.identifier.uri.fl_str_mv |
http://repositorio.ufsm.br/handle/1/5389 |
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. |
url |
http://repositorio.ufsm.br/handle/1/5389 |
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UFSM |
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Ciência da Computação |
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Universidade Federal de Santa Maria |
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