Educational data science: Monitoring learning technologies in primary schools
Resumen:
In recent years, particularly after the COVID-19 pandemic, the use of different learning management systems (LMS) for various objectives has become a key tool for education. A huge volume of student and teacher data are generated by LMS on a daily basis. Transforming these data into relevant information for decision-making and educational public policy is a major challenge due to the complexity of the data structure and the difficulty of summarizing the learning process with registered information. In this work, we combine several computational, statistical, and visualization tools to tackle this challenge with data from primary schools in Uruguay. Plan Ceibal (*) is a universal public policy implemented in Uruguay since 2010, it is part of the global initiative One Laptop per Child (OLPC, 2005). This program consists of providing every student and teacher in kindergarten, primary and middle school with a laptop or tablet and internet access in the school. Plan Ceibal has covered all public schools in the country and it has improved equality of access to technology, as well as ensured internet access in all public schools. This talk is focused on statistical tools for the evaluation and monitoring the use of LMS by students and teachers. We provide indicators of student engagement based on its activity registered by LMS and include these indicators in a web-application designed as a tool that allows monitoring the use of educational platforms in a systematic, standardized, and simple way. This might help to answer questions at different levels of analysis, for different actors in the education system and are key to strengthening both distance and face-to-face education. Daily usage data of CREA (the main LMS of Plan Ceibal) information for teachers and students are available from 2019 to 2021. The data structure, size among others presents a lot of challenges in this project. Most of the challenges are solved using efficient computational tools, for each stage of data analysis. R package data.table is used for data wrangling, Postgres as a SQL engine, and R packages shiny, plotly and ggplot2 are used for interactive visualization development.
2022 | |
ANII | |
Monitoring learning technologies in primary schools Data science in education problems Ciencias Sociales Ciencias de la Educación |
|
Inglés | |
Fundación Ceibal | |
Ceibal en REDI | |
https://hdl.handle.net/20.500.12381/3495 | |
Acceso abierto | |
Reconocimiento-NoComercial 4.0 Internacional. (CC BY-NC) |
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---|---|
author | da Silva, Natalia |
author_facet | da Silva, Natalia |
author_role | author |
bitstream.checksum.fl_str_mv | 74c80cb3911e028fefed9f697e97ff7e 84012f248c74f77d2b2c9dce4d1781cd |
bitstream.checksumAlgorithm.fl_str_mv | MD5 MD5 |
bitstream.url.fl_str_mv | https://redi.anii.org.uy/jspui/bitstream/20.500.12381/3495/2/license.txt https://redi.anii.org.uy/jspui/bitstream/20.500.12381/3495/1/Monitor_ICSDS_22.pdf |
collection | Ceibal en REDI |
dc.creator.none.fl_str_mv | da Silva, Natalia |
dc.date.accessioned.none.fl_str_mv | 2024-04-10T15:00:59Z |
dc.date.available.none.fl_str_mv | 2024-04-10T15:00:59Z |
dc.date.issued.none.fl_str_mv | 2022-12-15 |
dc.description.abstract.none.fl_txt_mv | In recent years, particularly after the COVID-19 pandemic, the use of different learning management systems (LMS) for various objectives has become a key tool for education. A huge volume of student and teacher data are generated by LMS on a daily basis. Transforming these data into relevant information for decision-making and educational public policy is a major challenge due to the complexity of the data structure and the difficulty of summarizing the learning process with registered information. In this work, we combine several computational, statistical, and visualization tools to tackle this challenge with data from primary schools in Uruguay. Plan Ceibal (*) is a universal public policy implemented in Uruguay since 2010, it is part of the global initiative One Laptop per Child (OLPC, 2005). This program consists of providing every student and teacher in kindergarten, primary and middle school with a laptop or tablet and internet access in the school. Plan Ceibal has covered all public schools in the country and it has improved equality of access to technology, as well as ensured internet access in all public schools. This talk is focused on statistical tools for the evaluation and monitoring the use of LMS by students and teachers. We provide indicators of student engagement based on its activity registered by LMS and include these indicators in a web-application designed as a tool that allows monitoring the use of educational platforms in a systematic, standardized, and simple way. This might help to answer questions at different levels of analysis, for different actors in the education system and are key to strengthening both distance and face-to-face education. Daily usage data of CREA (the main LMS of Plan Ceibal) information for teachers and students are available from 2019 to 2021. The data structure, size among others presents a lot of challenges in this project. Most of the challenges are solved using efficient computational tools, for each stage of data analysis. R package data.table is used for data wrangling, Postgres as a SQL engine, and R packages shiny, plotly and ggplot2 are used for interactive visualization development. |
dc.description.sponsorship.none.fl_txt_mv | ANII |
dc.identifier.anii.es.fl_str_mv | FSDE_2_2020_1_163528 |
dc.identifier.uri.none.fl_str_mv | https://hdl.handle.net/20.500.12381/3495 |
dc.language.iso.none.fl_str_mv | eng |
dc.publisher.es.fl_str_mv | Institute of Mathematical Statistics |
dc.rights.*.fl_str_mv | Acceso abierto |
dc.rights.license.none.fl_str_mv | Reconocimiento-NoComercial 4.0 Internacional. (CC BY-NC) |
dc.rights.none.fl_str_mv | info:eu-repo/semantics/openAccess |
dc.source.es.fl_str_mv | https://sites.google.com/view/icsds2022/home |
dc.source.none.fl_str_mv | reponame:Ceibal en REDI instname:Fundación Ceibal instacron:Fundación Ceibal |
dc.subject.anii.none.fl_str_mv | Ciencias Sociales Ciencias de la Educación |
dc.subject.es.fl_str_mv | Monitoring learning technologies in primary schools Data science in education problems |
dc.title.none.fl_str_mv | Educational data science: Monitoring learning technologies in primary schools |
dc.type.es.fl_str_mv | Documento de conferencia |
dc.type.none.fl_str_mv | info:eu-repo/semantics/conferenceObject |
dc.type.version.es.fl_str_mv | Publicado |
dc.type.version.none.fl_str_mv | info:eu-repo/semantics/publishedVersion |
description | In recent years, particularly after the COVID-19 pandemic, the use of different learning management systems (LMS) for various objectives has become a key tool for education. A huge volume of student and teacher data are generated by LMS on a daily basis. Transforming these data into relevant information for decision-making and educational public policy is a major challenge due to the complexity of the data structure and the difficulty of summarizing the learning process with registered information. In this work, we combine several computational, statistical, and visualization tools to tackle this challenge with data from primary schools in Uruguay. Plan Ceibal (*) is a universal public policy implemented in Uruguay since 2010, it is part of the global initiative One Laptop per Child (OLPC, 2005). This program consists of providing every student and teacher in kindergarten, primary and middle school with a laptop or tablet and internet access in the school. Plan Ceibal has covered all public schools in the country and it has improved equality of access to technology, as well as ensured internet access in all public schools. This talk is focused on statistical tools for the evaluation and monitoring the use of LMS by students and teachers. We provide indicators of student engagement based on its activity registered by LMS and include these indicators in a web-application designed as a tool that allows monitoring the use of educational platforms in a systematic, standardized, and simple way. This might help to answer questions at different levels of analysis, for different actors in the education system and are key to strengthening both distance and face-to-face education. Daily usage data of CREA (the main LMS of Plan Ceibal) information for teachers and students are available from 2019 to 2021. The data structure, size among others presents a lot of challenges in this project. Most of the challenges are solved using efficient computational tools, for each stage of data analysis. R package data.table is used for data wrangling, Postgres as a SQL engine, and R packages shiny, plotly and ggplot2 are used for interactive visualization development. |
eu_rights_str_mv | openAccess |
format | conferenceObject |
id | CEIBAL_883e116d9040161f525d0ffe50924a96 |
identifier_str_mv | FSDE_2_2020_1_163528 |
instacron_str | Fundación Ceibal |
institution | Fundación Ceibal |
instname_str | Fundación Ceibal |
language | eng |
network_acronym_str | CEIBAL |
network_name_str | Ceibal en REDI |
oai_identifier_str | oai:redi.anii.org.uy:20.500.12381/3495 |
publishDate | 2022 |
reponame_str | Ceibal en REDI |
repository.mail.fl_str_mv | mamunoz@fundacionceibal.edu.uy |
repository.name.fl_str_mv | Ceibal en REDI - Fundación Ceibal |
repository_id_str | 9421_1 |
rights_invalid_str_mv | Reconocimiento-NoComercial 4.0 Internacional. (CC BY-NC) Acceso abierto |
spelling | Reconocimiento-NoComercial 4.0 Internacional. (CC BY-NC)Acceso abiertoinfo:eu-repo/semantics/openAccess2024-04-10T15:00:59Z2024-04-10T15:00:59Z2022-12-15https://hdl.handle.net/20.500.12381/3495FSDE_2_2020_1_163528In recent years, particularly after the COVID-19 pandemic, the use of different learning management systems (LMS) for various objectives has become a key tool for education. A huge volume of student and teacher data are generated by LMS on a daily basis. Transforming these data into relevant information for decision-making and educational public policy is a major challenge due to the complexity of the data structure and the difficulty of summarizing the learning process with registered information. In this work, we combine several computational, statistical, and visualization tools to tackle this challenge with data from primary schools in Uruguay. Plan Ceibal (*) is a universal public policy implemented in Uruguay since 2010, it is part of the global initiative One Laptop per Child (OLPC, 2005). This program consists of providing every student and teacher in kindergarten, primary and middle school with a laptop or tablet and internet access in the school. Plan Ceibal has covered all public schools in the country and it has improved equality of access to technology, as well as ensured internet access in all public schools. This talk is focused on statistical tools for the evaluation and monitoring the use of LMS by students and teachers. We provide indicators of student engagement based on its activity registered by LMS and include these indicators in a web-application designed as a tool that allows monitoring the use of educational platforms in a systematic, standardized, and simple way. This might help to answer questions at different levels of analysis, for different actors in the education system and are key to strengthening both distance and face-to-face education. Daily usage data of CREA (the main LMS of Plan Ceibal) information for teachers and students are available from 2019 to 2021. The data structure, size among others presents a lot of challenges in this project. Most of the challenges are solved using efficient computational tools, for each stage of data analysis. R package data.table is used for data wrangling, Postgres as a SQL engine, and R packages shiny, plotly and ggplot2 are used for interactive visualization development.ANIIengInstitute of Mathematical Statisticshttps://sites.google.com/view/icsds2022/homereponame:Ceibal en REDIinstname:Fundación Ceibalinstacron:Fundación CeibalMonitoring learning technologies in primary schoolsData science in education problemsCiencias SocialesCiencias de la EducaciónEducational data science: Monitoring learning technologies in primary schoolsDocumento de conferenciaPublicadoinfo:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/conferenceObjectFacultad de Ciencias Económicas y de AdministraciónInstituto de EstadisticaUniversidad de la República//Ciencias Sociales/Ciencias de la EducaciónMonitoreo y evaluaciónMetodologías innovadoras de monitoreo y evaluación de proyectos y políticas digitalesda Silva, NataliaLICENSElicense.txtlicense.txttext/plain; charset=utf-85168https://redi.anii.org.uy/jspui/bitstream/20.500.12381/3495/2/license.txt74c80cb3911e028fefed9f697e97ff7eMD52ORIGINALMonitor_ICSDS_22.pdfMonitor_ICSDS_22.pdfPresentación realizada en IMS International Conference on Statistics and Data Science 2022, Florenciaapplication/pdf1502571https://redi.anii.org.uy/jspui/bitstream/20.500.12381/3495/1/Monitor_ICSDS_22.pdf84012f248c74f77d2b2c9dce4d1781cdMD5120.500.12381/34952024-04-15 12:50:04.703oai:redi.anii.org.uy:20.500.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en REDI - Fundación Ceibalfalse |
spellingShingle | Educational data science: Monitoring learning technologies in primary schools da Silva, Natalia Monitoring learning technologies in primary schools Data science in education problems Ciencias Sociales Ciencias de la Educación |
status_str | publishedVersion |
title | Educational data science: Monitoring learning technologies in primary schools |
title_full | Educational data science: Monitoring learning technologies in primary schools |
title_fullStr | Educational data science: Monitoring learning technologies in primary schools |
title_full_unstemmed | Educational data science: Monitoring learning technologies in primary schools |
title_short | Educational data science: Monitoring learning technologies in primary schools |
title_sort | Educational data science: Monitoring learning technologies in primary schools |
topic | Monitoring learning technologies in primary schools Data science in education problems Ciencias Sociales Ciencias de la Educación |
url | https://hdl.handle.net/20.500.12381/3495 |