Big Data y la alfabetización posthumana del futuro profesorado

  1. José Miguel Correa Gorospe 1
  2. Daniel Losada Iglesias 1
  3. Aingeru Gutiérrez-Cabello Barragán 1
  1. 1 Universidad del País Vasco/Euskal Herriko Unibertsitatea

    Universidad del País Vasco/Euskal Herriko Unibertsitatea

    Lejona, España


Sociología y tecnociencia: Revista digital de sociología del sistema tecnocientífico

ISSN: 1989-8487

Year of publication: 2021

Volume: 11

Issue: 2

Pages: 102-122

Type: Article

More publications in: Sociología y tecnociencia: Revista digital de sociología del sistema tecnocientífico


SCImago Journal Rank

  • Year 2021
  • SJR Journal Impact: 0.118
  • Best Quartile: Q4
  • Area: Management of Technology and Innovation Quartile: Q4 Rank in area: 247/265
  • Area: Development Quartile: Q4 Rank in area: 247/273
  • Area: Health (social science) Quartile: Q4 Rank in area: 300/320
  • Area: Sociology and Political Science Quartile: Q4 Rank in area: 1129/1327

Índice Dialnet de Revistas

  • Year 2021
  • Journal Impact: 0.110
  • Field: TRABAJO SOCIAL Quartile: C3 Rank in field: 26/51
  • Field: SOCIOLOGÍA Quartile: C4 Rank in field: 57/73


  • Social Sciences: C
  • Human Sciences: C

Scopus CiteScore

  • Year 2021
  • CiteScore of the Journal : 0.3
  • Area: Sociology and Political Science Percentile: 16
  • Area: Development Percentile: 11
  • Area: Health (social science) Percentile: 8
  • Area: Management of Technology and Innovation Percentile: 4

Journal Citation Indicator (JCI)

  • Year 2021
  • Journal Citation Indicator (JCI): 0.09
  • Best Quartile: Q4
  • Area: SOCIOLOGY Quartile: Q4 Rank in area: 194/211


We demand for the future teachers an ethical, informed and reflexive formation that allows to face the challenges of the Big Data. We argue that Big Data has an empowerment problem because of its lack of transparency, extractive collection, technological complexity and lack of control over its impact. These problems can be partially addressed through the education and training of future teachers involved in the formation of citizenship. We propose, from a post-qualitative position, a series of ideas always provisional for learning activities to start building literacy in Data of the future teachers.

Bibliographic References

  • Alter, A. (2018). Irresistible. ¿Quién nos ha convertido en yonquis tecnológicos? Barcelona: Paidos.
  • BBC (2017). AltSchool. Recuperado de
  • Ben-Porath, S., & Ben Shahar, T. H. (2017). Introduction: Big data and education: ethical and moral challenges. Theory and Research in Education, 15(3), 243–248.
  • Bhargava, R. (2019). Data Literacy. In The International Encyclopedia of Media Literacy.
  • Bhargava, R., Kadouaki, R., Bhargava, E., Castro, G., & D’Ignazio, C. (2016). Data Murals: Using the Arts to Build Data Literacy. The Journal of Community Informatics, 12(3).
  • Boyd, D., & Crawford, K. (2012). Critical Questions For Big Data: Provocations for a cultural, technological, and scholarly phenomenon. Information, Communication & Society, 15(5), 662–679.
  • Bowker, G. C. (2013). Data flakes: An afterword to ‘raw data’ is an oxymoron. In L. Gitelman (Ed.), ‘Raw data’ is an oxymoron (pp. 167–171). Cambridge, MA: MIT Press.
  • Braidotti, R. (2015). Lo Posthumano. Barcelona: Gedisa.
  • Braunack-Mayer, A. J., Street, J. M., Tooher, R., Feng, X., & Scharling-Gamba, K. (2020). Student and Staff Perspectives on the Use of Big Data in the Tertiary Education Sector: A Scoping Review and Reflection on the Ethical Issues. Review of Educational Research, 90(6).
  • Buitrago-Ropero, M. E., Ramírez-Montoya, M. S., & Laverde, A. C. (2020). Digital footprints (2005-2019): a systematic mapping of studies in education. Interactive Learning Environments, 1-14.
  • Cano, I. (2019). Sobre las limitaciones de Big Data en ciencias sociales. Sociología y tecnociencia, 9(2), 77-99.
  • Correa, J. M., & Aberasturi-Apraiz, E. (2015). Redes sociales e identidad digital docente. Experiencias de aprendizaje de futuras maestras de educación infantil a partir de la exposición artística Big Bang Data. Opción, 31, 311-333.
  • Correa Gorospe, J. M., Aberasturi-Apraiz, E., & Gutierrez-Cabello, A. (2016). Ciudadanía digital, activismo docente y formación de futuras maestras de educación infantil. Revista Latinoamericana de Tecnología Educativa, 15(2), 39-54.
  • Correa, J. M., Aberasturi-Apraiz, E., Gutierrez-Cabello, A., & Guerra, R. (2017). Usos críticos de las tecnologías digitales para el aprendizaje dentro y fuera de los contextos institucionales de formación. En H. Arancibia, P. Castillo y J. Saldaña (Eds.), Innovación educativa: perspectivas y desafíos (pp. 175-208). Valparaiso: Ediciones Universidad de Valparaíso.
  • Chan K. S., & Zary N. (2019). Applications and challenges of implementing artificial intelligence in medical education: Integrative review. JMIR Medical Education. 5(1).
  • Crawford, K. (2013, April 1). The hidden biases in big data. HBR Blog Network. Retrieved from
  • D’Ignazio, C., & Bhargava, R. (2015). Approaches to Building Big Data Literacy [Paper presentation]. Bloomberg Data for Good Exchange Conference, New York.
  • D’Ignazio, C., & Bhargava, R. (2018). Cultivating a Data Mindset in the Arts and Humanities. Public, 4(2).
  • 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.
  • D'Ignazio, C. (2020). Art and Cartography. In A. Kobayashi (Ed.), International Encyclopedia of Human Geography (Second Edition) (pp. 189-207). Elsevier.
  • D’Iganzio, K. & Klein, L. (2020). Data Feminism. Cambridge, MA: MIT Press.
  • Daniel, B. K. (2017). Big Data and data science: A critical review of issues for educational research. British Journal of Educational Technology, 50(1). 10.1111/bjet.12595
  • Dourish, P. (2016). Algorithms and their others: Algorithmic culture in context. Big Data & Society.
  • Dyke, E., & Meyerhoff, E. (2018). Radical imagination as pedagogy. Transformations: The Journal of Inclusive Scholarship and Pedagogy, 28(2), 160–180.
  • Eynon, R. (2013). The rise of Big Data: what does it mean for education, technology, and media research? Learning Media and Technology, 38(3), 237-240.
  • Eubanks, V. (2018). Automating Inequality: How High-Tech Tools Profile, Police, and Punish the Poor. New York: St. Martin’s Press.
  • Fotopoulou, A. (2020): Conceptualising critical data literacies for civil society organisations: agency, care, and social responsibility. Information, Communication & Society.
  • Franco, P. D., Matas, A., & Leiva, J. J. (2020). Big Data Irruption in Education. Pixel-Bit. Revista de Medios y Educación, 57, 59-90.
  • Freire, P. (1970). Pedagogía del Oprimido. Montevideo: Tierra Nueva.
  • Gallagher, M., Breines, M., & Blaney, M. (2020). Ontological Transparency, (In)visibility, and Hidden Curricula: Critical Pedagogy Amidst Contentious Edtech. Postdigit Sci Educ.
  • Garg, T. (2020). Artificial intelligence in medical education. The American Journal of Medicine. 133(2).
  • Guillemin, M., & Gillam, L. (2004). Ethics, Reflexivity, and “Ethically Important Moments” in Research. Qualitative Inquiry, 10(2), 261–280.
  • Goldsman, F. (2020). La distopia llegó: pensar las tecnologías del reconocimiento de personas desde la periferia.
  • Goldsman, F. (2018). Defender los territorios (digitales) sin dejar huella.
  • Gray, J., Gerlitz, C., & Bounegru, L. (2018). Data infrastructure literacy. Big Data & Society, 5(2).
  • Grzymek, V., & Puntschuh, M. (2019). Was Europa über Algorithmen weiß und denkt. Ergebnisse einer repräsentativen Bevölkerungsumfrage. Bertelsmann Stiftung.
  • Gutiérrez-Cabello, A., Correa Gorospe, J. M., & Aberasturi-Apraiz, E. (2020). Disidencia artística frente al control digital en la formación de maestras. Revista Izquierdas 49, 2127-2145.
  • Hernando, A. (2020). Catherine D'Ignazio, coautora del libro ‘Data Feminism’.
  • Hintz, A., Dencik, L., & Wahl-Jorgensen, K. (2018). Digital citizenship in a datafied society. Medford, USA: Polity Press.
  • Jandrić, P., Ryberg, T., Knox, J., Lacković, N., Hayes, S., Suoranta, J., Smith, M., Steketee, A.,Peters, M. A., McLaren, P., Ford, D. R., Asher, G., McGregor, C., Stewart, G., Williamson, B., & Gibbons, A. (2018). Postdigital Dialogue. Postdigital Science and Education, 1(1), 163–189.
  • Leander, K. M. & Burriss, S. K. (2020), Critical literacy for a posthuman world: When people read, and become, with machines. British Journal of Educationa Technoly, 51, 1262-1276.
  • Marín, V. I., Carpenter, J. P., & Tur, G. (2020). Pre-service teachers' perceptions of social media data privacy policies. British Journal of Educational Technology.
  • Myers, F, Collins H, Glover H, & Watson M. (2019). The automation game: Technological retention activities and perceptions on changes to tutors’ roles and identity. Teaching in Higher Education, 24(4), 545–562.
  • Ofcom (2019). Adults: Media use and attitudes report [Report].
  • Ofcom (2020). Adults: Media use and attitudes report [Report].
  • Ochoa-Aizpurua, B., Correa Gorospe, J.M., & Gutierrez-Cabello Barragan, A. (2019). Las Tic en la atención a la diversidad educativa: El caso de la comunidad Autónoma Vasca. Revista de Educación a Distancia. 61, 1-21
  • O´Neil, C. (2017). Armas de destrucción matemática. Cómo el Big Data aumenta la desigualdad y amenaza la democracia. Madrid: Capitán Swing.
  • Pangrazio, L., & Selwyn, N. (2019). ‘Personal data literacies’: A critical literacies approach to enhancing understandings of personal digital data. New Media & Society, 21(2), 419–437.
  • Redden J (2018) Democratic governance in an age of datafication: lessons from mapping government disurses and practices. Big Data & Society 5(2), 1-13.
  • Sander, I. (2020). Critical Big Data Literacy Tools – Engaging Citizens and Promoting Empowered Internet Usage. ORCA.
  • Sandu, N., & Gide, E. (2019). Adoption of AI-Chatbots to enhance student learning experience in higher education in India. 18th International Conference on Information Technology Based Higher Education and Training (ITHET) (pp. 1-5).
  • Southerton C. (2020) Datafication. In: Schintler L., McNeely C. (eds) Encyclopedia of Big Data. Springer, Cham.
  • Stewart GT, St. Pierre E, Devine N, & Kirloskar-Steinbach M.(2020). The End of the Dream: Postmodernism and Qualitative Research. Qualitative Inquiry. November 2020.
  • Turow, J., Hennessy, M., & Draper, N. A. (2015). The tradeoff fallacy: How marketers are misrepresenting American consumers and opening them up to exploitation [Report]. Annenberg School for Communication.
  • Turow, J., Hennessy, M., & Draper, N. (2018). Persistent Misperceptions: Americans’ Misplaced Confidence in Privacy Policies, 2003–2015. Journal of Broadcasting & Electronic Media, 62(3), 461–478.
  • Williamson, B. (2019). El future del curriculum. La educación y el conocimiento en la era digital. Madrid: Morata
  • Williamson, B. (2018). Big Data en la Educación. El futuro digital del aprendizaje, la política y la práctica. Madrid: Morata
  • Worledge, M., & Bamford, M. (2019). Adtech: Market Research Report. Information Commissioner’s Office. Ofcom.
  • Zuboff, S. (2015). Big other: Surveillance capitalism and the prospects of an information civilization. Journal of Information Technology, 30(1), 75–89.
  • Zuboff, S. (2019). The age of surveillance capitalism: The fight for a human future at the new frontier of power. New York, NY: PublicAffairs.