La Inteligencia Artificial en la educaciónBig data, cajas negras y solucionismo tecnológico

  1. Giró-Gracia, Xavier 1
  2. Sancho-Gil, Juana María 1
  1. 1 Universidad de Barcelona (España)
Revista:
RELATEC: Revista Latinoamericana de Tecnología Educativa

ISSN: 1695-288X

Año de publicación: 2022

Volumen: 21

Número: 1

Páginas: 129-145

Tipo: Artículo

DOI: 10.17398/1695-288X.21.1.129 DIALNET GOOGLE SCHOLAR lock_openAcceso abierto editor

Otras publicaciones en: RELATEC: Revista Latinoamericana de Tecnología Educativa

Resumen

El uso de la tecnología digital está impregnando y transformando todos los sistemas sociales, y la educación no es una excepción. En la última década, el desarrollo de la Inteligencia Artificial ha dado un nuevo impulso a la esperanza de dotar a los sistemas educativos de soluciones "eficaces" y más personalizadas para la enseñanza y el aprendizaje. Educadores e investigadores en el campo de la educación y responsables políticos, en general, carecen de los conocimientos y la experiencia necesarios para comprender la lógica subyacente a estos nuevos sistemas. Además, no contamos con suficientes evidencias basadas en la investigación para comprender plenamente las consecuencias que tienen para el desarrollo del alumnado, tanto el uso extensivo de las pantallas como la creciente dependencia de los algoritmos en los entornos educativos. Este artículo, dirigido a educadores, académicos del ámbito de la educación y responsables políticos, introduce en primer lugar los conceptos de "Big Data", Inteligencia Artificial (IA), algoritmos de aprendizaje automático y cómo se presentan y despliegan como "cajas negras", así como su posible impacto en la educación. A continuación, se centra en los discursos educativos subyacentes que históricamente han visto a las tecnologías de la información y la comunicación como panacea para resolver los problemas educativos, señalando la necesidad de analizar no solo sus ventajas, sino también sus posibles efectos negativos. Termina con una breve exploración de posibles escenarios futuros y conclusiones.

Referencias bibliográficas

  • Alter, A. (2017). Irresistible: The Rise of Addictive Technology and the Business of Keeping. Penguin Press.
  • Banks, J. A., Au, K. H., Ball, A.F., Bell, P., Gordon, E. W., Gutiérrez, K. D., Heath, S. B., Lee, C. D., Lee, Y., Mahiri, J.,
  • Nasir, N. S., Valdés, G., Zhou, M. (2007). Learning in and out of school in diverse environments. Life-long, Life-wide, Life-deep. The LIFE Center for Multicultural Education, University of Washington. http://lifeslc.org/docs/Banks_etal-LIFE-Diversity-Report.pdf
  • Bernstein, B. (1970). Education cannot compensate for society. New society, 26, 344-345.
  • Bogost, I. (2015, January 15). The Cathedral of Computation. The Atlantic. http://www.theatlantic.com/technology/archive/2015/01/the-cathedral-ofcomputation/384300/
  • Buchanan, R., & McPherson, A. (2019, July 8). Education shaped by big data and Silicon Valley. Is this what we want for Australia? EduResearch Matters, https://www.aare.edu.au/blog/?p=4182
  • Calvet Liñán, L., & Juan Pérez, Á. A. (2015). Educational Data Mining and Learning Analytics: differences, similarities, and time evolution. RUSC. Universities and Knowledge Society Journal, 12(3), 98-112. http://dx.doi.org/10.7238/rusc.v12i3.2515
  • Castells, M. (1996). The Rise of the Network Society (Information Age), vol. 1. 2nd ed. Blackwell Publishers.
  • Chakroun, B., Miao, F., Mendes, V., Domiter, A., Fan, H., Kharkova, I., Holmes, W., Orr, D., Jermol, M., Issroff, K., Park, J., Holmes, K., Crompton, H., Portales, P., Orlic, D., & Rodriguez, S. (2019). Artificial Intelligence for Sustainable Development: Synthesis Report, Mobile Learning Week 2019. UNESCO
  • Cohen, D. K. (1988). Educational Technology and School Organization. In R. S. Nickerson & P. P. Zodhiates (Eds.), Technology in Education: Looking Toward 2020 (pp. 231264). Hillsdale, NJ: Lawrence Erlbaum Associates, Pu.
  • Cuban, L. (1986). Teachers and Machines: The Classroom Use of Technology Since 1920. Teachers College.
  • Cuban, L. (1993). How teachers taught: constancy and change in American classrooms, 1890-1990. Teachers College Press.
  • Delors, J. (1998). Learning: The treasure within. Unesco.
  • Desmurget, M. (2020). La fábrica de cretinos digitales. Península.
  • Dick, S. (2019). Artificial Intelligence. Harvard Data Science Review, 1(1). https://doi.org/10.1162/99608f92.92fe150c
  • Dickson, B. (2021, January 28). Demystifying deep learning. Techtalks. https://bdtechtalks.com/2021/01/28/deep-learning-explainer/
  • European Commission (2021). Regulatory framework proposal on Artificial Intelligence. https://digital-strategy.ec.europa.eu/en/policies/regulatory-framework-ai
  • Finn, E. (2017). What Algorithms Want. Imagination in the Age of Computing. The MIT Press. https://doi.org/10.7551/mitpress/9780262035927.001.0001
  • Fogg, B. J. (2003). Persuasive Technology: Using Computers to Change what We Think and Do. Morgan Kaufmann Publishers.
  • Fogg, B. J. (2009). A Behavior Model for Persuasive Design. Persuasive’09, April 26-29. Claremont, CA. https://doi.org/10.1145/1541948.1541999
  • Gates, B. (1996). The road ahead. Viking.
  • Goldstein, H. (2018). Measurement and Evaluation Issues with PISA. In L. Volante (Ed.), The PISA Effect on Global Educational Governance (pp. 49-58). Routledge.
  • Google (2018). How Google Fights Piracy. https://www.blog.google/documents/25/GO806_Google_FightsPiracy_eReader_fi nal.pdf
  • Hartong, S., & Förschler, A. (2019). Opening the black box of data-based school monitoring: Data infrastructures, flows and practices in state education agencies. Big Data & Society. https://doi.org/10.1177/2053951719853311
  • Hilbert, M., & López, P. (2011). The World’s Technological Capacity to Store, Communicate, and Compute Information. Science, 332(6025), 60-65. https://doi.org/10.1126/science.1200970
  • Isaak, J., & Hanna, M. J. (2018). User Data Privacy: Facebook, Cambridge Analytica, and Privacy Protection. Computer, 51(8), 56-59. https://doi.org/10.1109/MC.2018.3191268.
  • Knox, J., Williamson, B., & Bayne, S. (2020). Machine behaviourism: Future visions of ‘learnification’ and ‘datafication’ across humans and digital technologies. Learning, Media and Technology, 45(1), 31-45. https://doi.org/10.1080/17439884.2019.1623251
  • Lahitou, J. (2018, August 18). Silicon Valley Parents Choose Low & No Tech Schools. What About Your Kid’s School? The Good Man Project. https://goodmenproject.com/uncategorized/silicon-valley-parents-choose-low-notech-schools-thats-probably-not-the-tech-policy-at-your-kids-school/
  • Lennon, T. (2016, August 11). Babylon’s ancient clay tablets made more census than today’s computers. The Daily Telegraph. https://www.dailytelegraph.com.au/news/babylons-ancient-clay-tablets-mademore-census-than-todays-computers/newsstory/3f76510db70c6bfd1185192a2e90badc
  • Lupton, D., & Williamson, B. (2017). The datafied child: The dataveillance of children and implications for their rights. New Media & Society, 19(5), 780-794. https://doi.org/10.1177/1461444816686328
  • MacDonald, B. (1993). Micromundos y mundos reales. Una agenda para la evaluación. Comunicación y Pedagogía-Infodidac. October, 31-41.
  • McClintock, R. O. (1993). El alcance de las posibilidades pedagógicas. In R. O. McClintock, G. Vázquez, M. J. Streibel (Coord.), Comunicación, tecnología y diseños de instrucción: la construcción del conocimiento escolar y el uso de los ordenadores (pp. 104-125). CIDE-MEC.
  • Morozov, E. (2013). To save everything, click here: The folly of technological solutionism. Public Affairs.
  • Muhammad, S.S., Dey, B.L., & Weerakkody, V. (2018). Analysis of Factors that Influence
  • Customers’ Willingness to Leave Big Data Digital Footprints on Social Media: A Systematic Review of Literature. Information Systems Frontiers, 20(3), 559-576. https://doi.org/10.1007/s10796-017-9802-y
  • Negroponte, N. (1995). Being Digital. Alfred A. Knopf.
  • Noble, D. D. (1991). The Classroom Arsenal: Military Research, Information Technology, and Public Education. The Falmer Press.
  • O’Neil, C. (2016). Weapons of Math Destruction: How Big Data Increases Inequality and Threatens Democracy. Crown Publishing Group, USA.
  • OECD-CERI (2006). Personalising Education. OECD. http://dx.doi.org/10.1787/9789264036604-en
  • OECD (2015). Students, Computers and Learning: Making the Connection, PISA. OECD. http://dx.doi.org/10.1787/9789264239555-en
  • OECD (2019). OECD Principles on Artificial Intelligence. https://www.oecd.org/goingdigital/ai/principles/
  • Papert, S. (1993). The Children's machine. Basic Books.
  • Peirano, M. (2019). El enemigo conoce el sistema. Manipulación de ideas, personas, influencias después de la economía de la atención. Debate.
  • Perelman, L. J. (1992). Schools Out. Hyperlearning, the New Technology, and the end of Education. William Morrow and Company, Inc.
  • Phillips, D. C. (2014). Research in the Hard Sciences, and in Very Hard “Softer” Domains. Educational Researcher, 43(1), 9-11. https://doi.org/10.3102/0013189X13520293
  • Pigott, T. D., Tocci, C., Ryan, A. M., & Galliher, A. (2021). Quality of Research Evidence in Education: How Do We Know? Review of Research in Education, 45(1), vii-xii. https://doi.org/10.3102/0091732X211001824
  • Pinar Saygin, A., Cicekli, I. & Akman, V. (2000). Turing Test: 50 Years Later. Minds and Machines 10, 463-518. https://doi.org/10.1023/A:1011288000451
  • Popkewitz, T. (2018, September 6). The Paradox of Research: The Good Intentions of Inclusion that Excludes and Abjects. ECER 2018. Bolzano, Italy. https://cutt.ly/pk6dwqQ
  • Ray S., & Saeed M. (2018). Applications of Educational Data Mining and Learning Analytics Tools in Handling Big Data in Higher Education. In M. Alani, H. Tawfik., M. Saeed & O. Anya (eds), Applications of Big Data Analytics. Springer, Cham. https://doi.org/10.1007/978-3-319-76472-6_7
  • Rittel, H. W. J., & Webber, M. M. (1984). Planning Problems are Wicked Problems. Developments. In N. Gross (ed.),
  • Design Methodology (pp. 135-144). John Wiley and Sons.
  • Saettler, P. (1990). The Evolution of American Educational Technology. Libraries Unlimited, Inc.
  • Sancho-Gil, J. M. (1995). Looking for the 'Right' Answers or Raising the 'Right' Questions? A Dialogical Approach to Automating Instructional Design. In R. D. Tennyson & A. E. Barron (Ed.), Automating Instructional Design: Computer-Based Development and Delivery Tools (pp. 79-99). Springer-Verlag. NATO ASI Series F: Computer and Systems Sciences, Vol. 140.
  • Sancho-Gil, J. M. (1998). Enfoques y funciones de las nuevas tecnologías para la información y la educación: lo que es no es lo que parece. In J. de Pablos & J. Jiménez (Eds.), Nuevas Tecnologías, Comunicación Audiovisual y Educación (pp. 71-102). Cedecs.
  • Sancho-Gil, J. M. (2020). Digital technology as a trigger for learning promises and realities. Digital Education Review, 37, 195-207. https://doi.org/10.1344/der.2020.37.191-203
  • Sancho-Gil, J. M., Rivera-Vargas, P. & Miño-Puigcercós, R (2020). Moving beyond the predictable failure of Ed-Techinitiatives. Learning, Media and Technology, 45(1), 61-75. https://doi.org/10.1080/17439884.2019.1666873
  • Sancho-Gil, J. M. (2021, 23 febrero). No abandonamos, vosotros nos abandonasteis. El Diario de la Educación. https://cutt.ly/ZIMWpME
  • Greg Thompson (2017) Computer adaptive testing, big data and algorithmic approaches to education, British Journal of Sociology of Education, 38:6, 827-840, DOI: 10.1080/01425692.2016.1158640
  • Trendacosta, K. (2020, December 10). Unfiltered: How YouTube’s Content ID Discourages Fair Use and Dictates What We See Online. Electronic Frontier Foundation.
  • https://www.eff.org/wp/unfiltered-how-youtubes-content-id-discourages-fair-useand-dictates-what-we-see-online
  • Turkle, S. (1995). Life on the Screen: Identity in the Age of the Internet. Shuster and Shuster.
  • Warzel, Ch. (2019, July 2). Welcome to the K-12 Surveillance State. Is tech really the solution to student safety? New York Times. https://www.nytimes.com/2019/07/02/opinion/surveillance-state-schools.html
  • Weizenbaum, J. (1966). ELIZA--A Computer Program for the Study of Natural Language Communication Between Man and Machine. Communications of the ACM, 9(1), 36-45. https://doi.org/10.1145/365153.365168
  • Weller, C. (2018, February 18). Silicon Valley parents are raising their kids tech-free — and it should be a red flag. Buisiness Insider. https://www.businessinsider.com/siliconvalley-parents-raising-their-kids-tech-free-red-flag-2018-2
  • Williamson, B. (2017). Big Data in Education: The Digital Future of Learning, Policy and Practice. SAGE Publications. https://doi.org/10.4135/9781529714920
  • Williams, J. (2018). Stand out of our Light: Freedom and Resistance in the Attention Economy. Cambridge University Press. https://doi.org/10.1017/9781108453004
  • Zuboff, S. (2019). The age of surveillance capitalism: The fight for a human future at the new frontier of power: Barack Obama's books of 2019. Profile books.
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