Alfabetización en datos: prácticas y escenarios formativos

  1. Yolanda Martín González 1
  2. Ana Iglesias Rodríguez 1
  1. 1 Universidad de Salamanca
    info

    Universidad de Salamanca

    Salamanca, España

    ROR https://ror.org/02f40zc51

Journal:
EDICIC

ISSN: 2236-5753

Year of publication: 2023

Volume: 3

Issue: 3

Pages: 1-15

Type: Article

More publications in: EDICIC

Abstract

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 prioritywas 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.

Bibliographic References

  • Area-Moreira, M. (2023). La digitalización y el profesorado universitario. Miradas más allá de la experiencia pandémica. En R. Cabello & S. Lago (Eds.), Cultura, ciudadanías y educación en el entorno digital (2015-229). Clacso. https://biblioteca-repositorio.clacso.edu.ar/bitstream/CLACSO/248305/1/Cultura-ciudadanias-educacion.pdf.
  • Beck, J.S., & Nunnaley, D. (2021). A continuum of data literacy for teaching. Studies in Educational Evaluation, 69. https://doi.org/10.1016/j.stueduc.2020.100871.
  • Brodsky, M. (2017). Understanding Data Literacy Requirements for Assignments: A Business School Syllabus Study. International Journal of Librarianship 2(1). https://doi.org/10.23974/ijol.2017.vol2.1.25.
  • Comisión Europea (2020). Comunicación de la Comisión al Parlamento Europeo, el Consejo, el Comité Económico y Social y el Comité de las Regiones. Una Estrategia Europea de Datos. Bruselas, 19.2.2020 Com(2020) 66 final. https://eur-lex.europa.eu/legal-content/ES/TXT/?uri=CELEX:52020DC0066.
  • Deja, M., Januszko-Szakiel, A., Koryciÿska, & Deja, P. (2021). The Impact of Basic Data Literacy Skills on Work-Related Empowerment: The Alumni Perspective. College & Research Libraries, 82(5), 708-729. https://crl.acrl.org/index.php/crl/article/view/25016/32893.
  • D ́Ignazio, C. (2017). Creative data literacy: Bridging the gap between the data-haves and data-have nots. Information Design Journal, 23(1) 6-18. DOI:10.1075/IDJ.23.1.03dig.
  • Hernández-Pérez, T. (2016). En la Era de la web de los datos: primero datos abiertos, después datos masivos. El profesional de la información, 25(4), 517-525. http://dx.doi.org/10.3145/epi.2016.jul.01
  • Hernández Sampieri, R. (2018). Metodología de la investigación: las rutas cuantitativa, cualitativa y mixta. México: Mc Graw Hill.
  • Iglesias, A., Martín, Y., & Hernández, A. (2023). Evaluación de la competencia digital del alumnado de Educación Primaria. Revista de Investigación Educativa, 41(1), 33-50https://doi.org/10.6018/rie.520091.
  • Jacobs, J., Gregory, A., Hoppey, D., & Yendol-Hoppey, D. (2009). Data Literacy: Understanding Teachers’ Data Use in a Context of Accountability and Response to Intervention. Action in Teacher Education, 31(3), 41-55. DOI: 10.1080/01626620.2009.10463527.
  • Kippers, W.B., Poortman, C. L., Schildkamp, K., &Visscher, A. J. (2017). Data literacy: What do educators learn and struggle with during a data use intervention? Studies in Educational Evaluation, 56, 21-31. https://doi.org/10.1016/j.stueduc.2017.11.001.
  • Kouts-Klemm, R. (2019). Data literacy among journalists:A skills-assessment based approach. Central European Journal of Communicatión, 12(3). https://doi.org/10.19195/1899-5101.12.3(24).2
  • Martín-González, Y., & Iglesias-Rodríguez, A. (2022). Alfabetización en Datos en las bibliotecas-CRAI españolas: Análisis descriptivo y propositivo. Revista Española de Documentación Científica, 45(2), e322. https://doi.org/10.3989/redc.2022.2.1857.
  • Martín, Y., & Iglesias, A. (2021). Alfabetização de dados: Projetando um novo cenário de treinamento para o contexto universitário. Revista Ibero-americana de Ciência da Informação, 14(1), 318-330. https://doi.org/10.26512/rici.v14.n1.2021.35521.
  • Merka, S., Pointl, S., Wurster, S., &Böhl, T. (2020). Fostering asects of pre-service teachers ́data literacy: Results of a randoizedcontrolled trial. Teaching and Teacher Education, 91. https://doi.org/10.1016/j.tate.2020.103043.
  • Miller-Bains, K., Cohen, J., & Wong, V.C. (2021). Developing data literacy: Investigating the effects of a pre-service data use intervention. Teaching and Teacher Education, 109. https://doi.org/10.1016/j.tate.2021.103569.
  • Papamitsiou, Z., Filippakis, M.E., Poulou, M., Sampson, D., Ifenthaler, D. &Giannakos, M. (2021). Towards an educational data literacy framework enhacing the profiles of instructional designers and e-tutors of online and blended courses with new competences. Smart Learning Environment 8 (18). https://doi.org/10.1186/s40561-021-00163-w.
  • Raffaghelli, J. E. (2020). Is Data Literacy a catalyst of social justice? A response from nine data literacy initiatives in HigherEducation. Education Sciences, 10(9) 233. https://doi.org/10.3390/educsci10090233.
  • Resolución de 4 de mayo de 2022, de la Dirección General de Evaluación y Cooperación Territorial, por la que se publica el Acuerdo de la Conferencia Sectorial de Educación, sobre la actualización del marco de referencia de la competencia digital docente. BOE núm. 116, de 16 de mayo de 2022, páginas 67979 a 68026 (48 págs.). https://www.boe.es/eli/es/res/2022/05/04/(5).
  • Reeves, T.D., & Honig, S.L. (2015). A classroom data literacy intervention for preservice teachers. Teaching and Teacher Education, 50, 90-101. http://dx.doi.org/10.1016/j.tate.2015.05.007.
  • Rivas-Rebaque, B., Gértrudix-Barrio, F., & de Cisneros de Britto, J.C. (2019). La percepción del docente universitario ante el uso y valor de los datos abiertos. Educación XX1, 22(2), 141-163. https://doi.org/10.5944/educxx1.21317
  • Robertson, J., & Tisdall, K. E. M. (2020). The importance of consulting children and young people about data literacy. Journal of Media Literacy Education, 12(3), 58-74. https://doi.org/10.23860/JMLE-2020-12-3-6.
  • Schildkamp, K., & Lai, M. K. (2013). Conclusions and a data use framework. In K. Schildkamp, M. K. Lai, & L. Earl (Eds.), Data-based decision making in education: Challenges and opportunities (pp. 177–192). Springer.
  • Trantham, P.S., Sikorski, J., de Ayala, R.J., & Doll, B. (2021). An item response theory and Rasch analysis of the NUDKS: a data literacy scale. Educ Asse Eval Acc, 34, 113-135. https://doi.org/10.1007/s11092-021-09372-w.
  • UNESCO-IESALC. (2019). Plan de Acción 2018-2028. III Conferencia Regional de Educación Superior para América Latina y el Caribe. UNESCO-IESALC. https://www.iesalc.unesco.org/wp-content/uploads/2019/02/PlandeAccionCRES2018-2028-Def.pdf.
  • UNESCO. (2021). Reimaginar juntos nuestros futuros. Un nuevo contrato social para la educación. Resumen ejecutivo. UNESCO. https://unesdoc.unesco.org/ark:/48223/pf0000379381_spa.
  • Unión Europea. (2022). Directrices éticas sobre el uso de la inteligencia artificial (IA) y los datos en la educación y formación para los educadores. Oficina de Publicaciones de la Unión Europea. https://bit.ly/3UrRUj5.
  • Usova, T., & Laws, R. (2021). Teaching a one-credit course on data literacy and data visualisation. Journal of information Literacy, 15(1), 84-95. https://doi.org/10.11645/15.1.2840.
  • Verdi, U. (2023). Quelle(s) réponse(s) à l ́enjeu d ́acculturation aux données? Un état de l ́art des caractéristiques de la data literacy. Revues française des Sciences de l ́Information et de la Communication, 26. https://doi.org/10.4000/rfsic.14589.