Data literacy: practices and training scenarios
Autor(a) principal: | |
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Data de Publicação: | 2023 |
Outros Autores: | |
Tipo de documento: | Artigo |
Idioma: | por |
Título da fonte: | Revista EDICIC |
Texto Completo: | https://ojs.edicic.org/revistaedicic/article/view/202 |
Resumo: | Data literacy is considered an emerging concept or a novel line of research that empowers the citizen in today's context of the data-driven society by providing the necessary training to solve real-world problems and make data-driven decisions. The data-literate individual is able to understand, explain, use, interpret, consume and disseminate - critically and effectively - data, and turn it into information and knowledge. This study is characterised as being primarily qualitative in nature. Firstly, an exploratory type of documentary research is carried out to identify and analyse the models and training practices that are being carried out in the university environment on data literacy. The search was carried out through the Google platform, under common research criteria ("data literacy" AND "university", "data literacy training" AND "university"), and in different languages (English, Portuguese, Italian and French). As inclusion criteria, the search was limited to the last 5 years (2018-2022) and priority was given to course-based training models and practices (MOOC, webinar, Blog, etc.). The sample consists of 82 types of training practices from Brazil, Spain, the United States, France, Italy, the United Kingdom and Switzerland. The information was compiled in a file with the following categories: country, name of the instruction (Expert Degree, MOOC, Seminar, etc.), modality (face-to-face, online, etc.) cost, methodology (expository or interactive); learning content, target group (undergraduate, graduate students or teaching and research staff) and duration. The resulting database was analysed quantitatively using SPSS.28 statistical software. The results show that 34.1% of the training options are provided in Spain, 22% in France and 19.5% in the United Kingdom. More than half of the training (53.7%) takes place through seminars, courses or workshops and almost three quarters of the internships are paid (70.7%). Face-to-face training is the most used modality (36.59%), followed by virtual training (34.1%). The main instruction is directed towards data science; data management and Big Data (25.1%; 22.6% and 12.3% respectively). 31.7% of the activities follow an interactive methodology and 30.5% develop an interactive and expository method. 20.7% of the training is aimed at graduates, diploma or degree holders, postgraduate students (17.9%) and other professionals (14.4%). The duration of training is mainly long, ranging from 13 to 24 months (24.39%). Finally, the categories examined offer different results depending on the country in which the apprenticeship is provided. Thus, for example, graduates in Spain, while bearing the cost of the training, have a wide training offer, characterised by face-to-face training, with an interactive/expositive methodology and an extensive duration. |
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Data literacy: practices and training scenariosAlfabetización en datos: prácticas y escenarios formativosCompetência em dados: práticas e cenários de treinamentoAlfabetización en datosEscenarios formativosFormaciónCompetência em DadosCenários de TreinamentoTreinamentoData LiteracyTraining ScenariosTrainingData literacy is considered an emerging concept or a novel line of research that empowers the citizen in today's context of the data-driven society by providing the necessary training to solve real-world problems and make data-driven decisions. The data-literate individual is able to understand, explain, use, interpret, consume and disseminate - critically and effectively - data, and turn it into information and knowledge. This study is characterised as being primarily qualitative in nature. Firstly, an exploratory type of documentary research is carried out to identify and analyse the models and training practices that are being carried out in the university environment on data literacy. The search was carried out through the Google platform, under common research criteria ("data literacy" AND "university", "data literacy training" AND "university"), and in different languages (English, Portuguese, Italian and French). As inclusion criteria, the search was limited to the last 5 years (2018-2022) and priority was given to course-based training models and practices (MOOC, webinar, Blog, etc.). The sample consists of 82 types of training practices from Brazil, Spain, the United States, France, Italy, the United Kingdom and Switzerland. The information was compiled in a file with the following categories: country, name of the instruction (Expert Degree, MOOC, Seminar, etc.), modality (face-to-face, online, etc.) cost, methodology (expository or interactive); learning content, target group (undergraduate, graduate students or teaching and research staff) and duration. The resulting database was analysed quantitatively using SPSS.28 statistical software. The results show that 34.1% of the training options are provided in Spain, 22% in France and 19.5% in the United Kingdom. More than half of the training (53.7%) takes place through seminars, courses or workshops and almost three quarters of the internships are paid (70.7%). Face-to-face training is the most used modality (36.59%), followed by virtual training (34.1%). The main instruction is directed towards data science; data management and Big Data (25.1%; 22.6% and 12.3% respectively). 31.7% of the activities follow an interactive methodology and 30.5% develop an interactive and expository method. 20.7% of the training is aimed at graduates, diploma or degree holders, postgraduate students (17.9%) and other professionals (14.4%). The duration of training is mainly long, ranging from 13 to 24 months (24.39%). Finally, the categories examined offer different results depending on the country in which the apprenticeship is provided. Thus, for example, graduates in Spain, while bearing the cost of the training, have a wide training offer, characterised by face-to-face training, with an interactive/expositive methodology and an extensive duration.Se considera la alfabetización en datos un concepto emergente o una línea de investigación novedosa que empodera al ciudadano en el contexto actual de la sociedad datificada al proporcionarle la formación necesaria para resolver problemas del mundo real y tomar decisiones basadas en datos. El individuo alfabetizado en datos es capaz de comprender, explicar, utilizar, interpretar, consumir y difundir -de manera crítica y eficaz- los datos, y convertirlos en información y en conocimiento. Este estudio se caracteriza por tener una naturaleza, fundamentalmente, cualitativa. En primer lugar, se desarrolla un tipo de investigación documental de carácter exploratorio para identificar y analizar los modelos y prácticas formativas que se estén efectuando en el ámbito universitario sobre la alfabetización en datos. La búsqueda se hizo a través de la plataforma Google, bajo unos criterios de investigación comunes ("alfabetización en datos" AND "Universidad", "formación en datos" AND "universidad"), y en distintos idiomas (inglés, portugués, italiano y francés). Como criterios de inclusión, se limitó la búsqueda a los últimos 5 años (2018-2022) y se otorgó prioridad a los modelos y prácticas formativas basados en cursos (MOOC, Webinar, Blog, etc.). La muestra se compone por 82 tipos de prácticas formativas procedentes de Brasil, España, Estados Unidos, Francia, Italia, Reino Unido y Suiza. La información se compiló en una ficha con las siguientes categorías: país, denominación de la instrucción (Título de experto, MOOC, Seminario, etc.), modalidad (presencial, online, etc.) coste, metodología (expositiva o interactiva); contenidos de aprendizaje, colectivo al que se dirige (estudiantes de grado, postgrado o personal docente e investigador) y duración. La base de datos resultante se ha analizado cuantitativamente mediante el software estadístico SPSS.28. En cuanto a los resultados hallados, se registra que el 34,1% de las opciones formativas se imparten desde España, el 22% en Francia y el 19,5% en Reino Unido. Más de la mitad de la formación (53,7%) tiene lugar a través de seminarios, cursos o talleres y casi tres cuartas partes de las prácticas son de pago (70,7%). La presencialidad se rige como la modalidad más utilizada (36,59%), seguida de la formación virtual (34,1%). La principal instrucción se dirige hacia la ciencia de los datos; la gestión de datos y el Big Data (25,1%; 22,6% y 12,3% respectivamente). El 31,7% de las actividades sigue una metodología interactiva y el 30,5% desarrolla un método interactivo y expositivo. El 20,7% de la formación se dirige a personas graduadas, diplomadas o licenciadas; a estudiantes de postgrado (17,9%) y a otros profesionales (14,4%). La duración de la formación es principalmente extensa, de 13 a 24 meses (24,39%). Por último, las categorías examinadas ofrecen diferentes resultados dependiendo del país en el que se imparta el aprendizaje. Así, por ejemplo, los/as titulados/as en España, aun asumiendo el coste de la formación, tienen una oferta formativa amplia, caracterizada por la presencialidad, con una metodología interactiva/expositiva y una duración extensa.A competencia em dados é considerada um conceito emergente ou uma nova linha de pesquisa que capacita os cidadãos no contexto atual da sociedade imersa em dados, proporcionando-lhes a formação necessária para resolver problemas do mundo real e tomar decisões com base em dados. O indivíduo alfabetizado em dados é capaz de compreender, explicar, usar, interpretar, consumir e disseminar -- de forma crítica e eficaz -- dados, e convertê-los em informação e conhecimento. Este estudo caracteriza-se por ser de natureza fundamentalmente qualitativa. Primeiramente, desenvolve-se um tipo de pesquisa documental exploratória para identificar e analisar os modelos e práticas de formação que estão sendo realizados no ambiente universitário em alfabetização em dados. A pesquisa foi realizada através da plataforma Google, sob critérios comuns de pesquisa (“competência em dados” AND “Universidade”, “formação de dados” AND “universidade”), e em diferentes idiomas (inglês, português, italiano e francês). Como critérios de inclusão, a pesquisa limitou-se aos últimos 5 anos (2018-2022) e foi dada prioridade a modelos e práticas de formação baseadas em cursos (MOOC, Webinar, Blog etc.). A amostra é composta por 82 tipos de práticas de formação do Brasil, Espanha, Estados Unidos, França, Itália, Reino Unido e Suíça. As informações foram compiladas em um arquivo com as seguintes categorias: país, nome da instrução (Título de Especialista, MOOC, Seminário, etc.), modalidade (presencial, online etc.), custo, metodologia (expositiva ou interativo); conteúdo de aprendizagem, público-alvo (alunos de graduação, pós-graduação ou docentes e pesquisadores) e duração. A base de dados resultante foi analisada quantitativamente utilizando o software estatístico SPSS.28. Relativamente aos resultados encontrados, regista-se que 34,1% das opções de formação são ministradas a partir da Espanha; 22% na França; e 19,5% no Reino Unido. Mais de metade da formação (53,7%) realiza-se através de seminários, cursos ou workshops e quase três quartos dos estágios são remunerados (70,7%). O treinamento presencial é a modalidade mais utilizada (36,59%), seguido do treinamento virtual (34,1%). A instrução principal é direcionada à Ciência de Dados; gestão de dados e Big Data (25,1%, 22,6% e 12,3% respectivamente). 31,7% das atividades seguem metodologia interativa e 30,5% desenvolvem método interativo e expositivo. 20,7% da formação destina-se a licenciados, diplomados ou licenciados; a estudantes de pós-graduação (17,9%) e outros profissionais (14,4%). A duração da formação é maioritariamente longa, de 13 a 24 meses (24,39%). Finalmente, as categorias examinadas oferecem resultados diferentes dependendo do país em que a aprendizagem ocorre. Assim, por exemplo, os licenciados na Espanha, mesmo assumindo o custo da formação, dispõem de uma ampla oferta formativa, caracterizada por uma formação presencial, com uma metodologia interativa/expositiva e uma extensa duração.Asociación de Educación e Investigación en Ciencia de la Información de Iberoamérica y el Caribe2023-12-21info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionResearch PaperArtículo de InvestigaciónArtigo de Pesquisaapplication/pdfhttps://ojs.edicic.org/revistaedicic/article/view/20210.62758/re.v3i3.202Revista EDICIC; Vol. 3 No. 3 (2023): Special Issue: Information Literacy, digital humanities and gender studies: trends and challenges; 1-15Revista EDICIC; Vol. 3 Núm. 3 (2023): Número especial: Alfabetización informacional, humanidades digitales y estudios de género: tendencias y desafíos; 1-15Revista EDICIC; v. 3 n. 3 (2023): Número Especial: Competência em Informação, humanidades digitais e estudos de gênero: tendencias e desafíos ; 1-152236-575310.62758/re.v3i3reponame:Revista EDICICinstname:Asociación de Educación e Investigación en Ciencia de la Información de Iberoamérica y el Caribe (EDICIC)instacron:EDICICporhttps://ojs.edicic.org/revistaedicic/article/view/202/218Derechos de autor 2023 Revista EDICIChttps://creativecommons.org/licenses/by/4.0info:eu-repo/semantics/openAccessMartín-González, YolandaIglesias-Rodríguez, Ana2024-04-26T11:27:44Zoai:ojs.pkp.sfu.ca:article/202Revistahttp://ojs.edicic.org/index.php/revistaedicicPRIhttp://ojs.edicic.org/index.php/revistaedicic/oaiedicic@edicic.org2236-57532236-5753opendoar:2024-04-26T11:27:44Revista EDICIC - Asociación de Educación e Investigación en Ciencia de la Información de Iberoamérica y el Caribe (EDICIC)false |
dc.title.none.fl_str_mv |
Data literacy: practices and training scenarios Alfabetización en datos: prácticas y escenarios formativos Competência em dados: práticas e cenários de treinamento |
title |
Data literacy: practices and training scenarios |
spellingShingle |
Data literacy: practices and training scenarios Martín-González, Yolanda Alfabetización en datos Escenarios formativos Formación Competência em Dados Cenários de Treinamento Treinamento Data Literacy Training Scenarios Training |
title_short |
Data literacy: practices and training scenarios |
title_full |
Data literacy: practices and training scenarios |
title_fullStr |
Data literacy: practices and training scenarios |
title_full_unstemmed |
Data literacy: practices and training scenarios |
title_sort |
Data literacy: practices and training scenarios |
author |
Martín-González, Yolanda |
author_facet |
Martín-González, Yolanda Iglesias-Rodríguez, Ana |
author_role |
author |
author2 |
Iglesias-Rodríguez, Ana |
author2_role |
author |
dc.contributor.author.fl_str_mv |
Martín-González, Yolanda Iglesias-Rodríguez, Ana |
dc.subject.por.fl_str_mv |
Alfabetización en datos Escenarios formativos Formación Competência em Dados Cenários de Treinamento Treinamento Data Literacy Training Scenarios Training |
topic |
Alfabetización en datos Escenarios formativos Formación Competência em Dados Cenários de Treinamento Treinamento Data Literacy Training Scenarios Training |
description |
Data literacy is considered an emerging concept or a novel line of research that empowers the citizen in today's context of the data-driven society by providing the necessary training to solve real-world problems and make data-driven decisions. The data-literate individual is able to understand, explain, use, interpret, consume and disseminate - critically and effectively - data, and turn it into information and knowledge. This study is characterised as being primarily qualitative in nature. Firstly, an exploratory type of documentary research is carried out to identify and analyse the models and training practices that are being carried out in the university environment on data literacy. The search was carried out through the Google platform, under common research criteria ("data literacy" AND "university", "data literacy training" AND "university"), and in different languages (English, Portuguese, Italian and French). As inclusion criteria, the search was limited to the last 5 years (2018-2022) and priority was given to course-based training models and practices (MOOC, webinar, Blog, etc.). The sample consists of 82 types of training practices from Brazil, Spain, the United States, France, Italy, the United Kingdom and Switzerland. The information was compiled in a file with the following categories: country, name of the instruction (Expert Degree, MOOC, Seminar, etc.), modality (face-to-face, online, etc.) cost, methodology (expository or interactive); learning content, target group (undergraduate, graduate students or teaching and research staff) and duration. The resulting database was analysed quantitatively using SPSS.28 statistical software. The results show that 34.1% of the training options are provided in Spain, 22% in France and 19.5% in the United Kingdom. More than half of the training (53.7%) takes place through seminars, courses or workshops and almost three quarters of the internships are paid (70.7%). Face-to-face training is the most used modality (36.59%), followed by virtual training (34.1%). The main instruction is directed towards data science; data management and Big Data (25.1%; 22.6% and 12.3% respectively). 31.7% of the activities follow an interactive methodology and 30.5% develop an interactive and expository method. 20.7% of the training is aimed at graduates, diploma or degree holders, postgraduate students (17.9%) and other professionals (14.4%). The duration of training is mainly long, ranging from 13 to 24 months (24.39%). Finally, the categories examined offer different results depending on the country in which the apprenticeship is provided. Thus, for example, graduates in Spain, while bearing the cost of the training, have a wide training offer, characterised by face-to-face training, with an interactive/expositive methodology and an extensive duration. |
publishDate |
2023 |
dc.date.none.fl_str_mv |
2023-12-21 |
dc.type.driver.fl_str_mv |
info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion Research Paper Artículo de Investigación Artigo de Pesquisa |
format |
article |
status_str |
publishedVersion |
dc.identifier.uri.fl_str_mv |
https://ojs.edicic.org/revistaedicic/article/view/202 10.62758/re.v3i3.202 |
url |
https://ojs.edicic.org/revistaedicic/article/view/202 |
identifier_str_mv |
10.62758/re.v3i3.202 |
dc.language.iso.fl_str_mv |
por |
language |
por |
dc.relation.none.fl_str_mv |
https://ojs.edicic.org/revistaedicic/article/view/202/218 |
dc.rights.driver.fl_str_mv |
Derechos de autor 2023 Revista EDICIC https://creativecommons.org/licenses/by/4.0 info:eu-repo/semantics/openAccess |
rights_invalid_str_mv |
Derechos de autor 2023 Revista EDICIC https://creativecommons.org/licenses/by/4.0 |
eu_rights_str_mv |
openAccess |
dc.format.none.fl_str_mv |
application/pdf |
dc.publisher.none.fl_str_mv |
Asociación de Educación e Investigación en Ciencia de la Información de Iberoamérica y el Caribe |
publisher.none.fl_str_mv |
Asociación de Educación e Investigación en Ciencia de la Información de Iberoamérica y el Caribe |
dc.source.none.fl_str_mv |
Revista EDICIC; Vol. 3 No. 3 (2023): Special Issue: Information Literacy, digital humanities and gender studies: trends and challenges; 1-15 Revista EDICIC; Vol. 3 Núm. 3 (2023): Número especial: Alfabetización informacional, humanidades digitales y estudios de género: tendencias y desafíos; 1-15 Revista EDICIC; v. 3 n. 3 (2023): Número Especial: Competência em Informação, humanidades digitais e estudos de gênero: tendencias e desafíos ; 1-15 2236-5753 10.62758/re.v3i3 reponame:Revista EDICIC instname:Asociación de Educación e Investigación en Ciencia de la Información de Iberoamérica y el Caribe (EDICIC) instacron:EDICIC |
instname_str |
Asociación de Educación e Investigación en Ciencia de la Información de Iberoamérica y el Caribe (EDICIC) |
instacron_str |
EDICIC |
institution |
EDICIC |
reponame_str |
Revista EDICIC |
collection |
Revista EDICIC |
repository.name.fl_str_mv |
Revista EDICIC - Asociación de Educación e Investigación en Ciencia de la Información de Iberoamérica y el Caribe (EDICIC) |
repository.mail.fl_str_mv |
edicic@edicic.org |
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1809218353984700416 |