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Considering AI in Education: Erziehung but Never Bildung

  • Alex GuilhermeEmail author
Chapter
Part of the Perspectives on Rethinking and Reforming Education book series (PRRE)

Abstract

A defining aspect of our modern age is our tenacious belief in technology in all walks of life, not least in education. It could be argued that this infatuation with technology or ‘techno-philia’ in education has had a deep impact in the classroom changing the relationship between teacher and student, as well as between students. Running parallel to this and perhaps exacerbating the problem is the so-called process of ‘learnification’, which understands that teachers are mere facilitators of the learning process, rather than someone with an expertise who has something to teach others. In this article, I first assess the current technologization of education and the impact it has had in relations within the classroom, leading to an understanding of education as Erziehung rather than Bildung; secondly, I investigate through a thought experiment if the development of AI could one day successfully replace human teachers in the classroom.

Keywords

AI Gert biesta Though experiment Erziehung Bildung 

References

  1. al-Rifaie, M. M., & Bishop, M. (2015). Weak and strong computational creaitivity. In T. R. Besold, M. Schorlemmer & A. Smaill (Eds.), Computational creativity research: Towards creative machines. Amsterdam: Atlantis Press.Google Scholar
  2. Apple, M. (1988). Teachers and texts: A political economy of class and gender relations in education. London: Routledge.Google Scholar
  3. Asimov, I. (1950). I, Robot. New York: Gnome Press.Google Scholar
  4. Baker, R. S. Jd., Mello, S. K. D., Rodrigo, M. M. T., & Graesser, A. C. (2018). Better to be frustrated than bored: The incidence, persistence, and impact of learners’ cognitive-affective states during interactions with three different computer-based learning environments. International Journal of Human-Computer Studies, 68(4), 223–241.CrossRefGoogle Scholar
  5. Biesta, G. J. J. (2002). Bildung and modernity: The future of Bildung in a world of difference. In Studies in philosophy and education (Vol. 21, pp. 343–351).Google Scholar
  6. Biesta, G. J. J. (2010). Good education in an age of measurement: Ethics, politics and democracy. Boulder, CO: Paradigm Publishers.Google Scholar
  7. Biesta, G., and Säfström, C.A. (2011). Manifesto on Education. In Policy Futures in Education, 9(5), 540–547.CrossRefGoogle Scholar
  8. Biesta, G. J. J. (2013). Receiving the gift of teaching: From ‘learning from’ to ‘being taught by. In Studies in philosophy of education (Vol. 32, pp. 449–461).CrossRefGoogle Scholar
  9. Biesta, G. J. J. (2015). What is education For? On good education, Teacher judgement, and educational professionalism. European Journal of Education, 50(1), 75–87.CrossRefGoogle Scholar
  10. Boulay, B., & Luckin, R. (2015). Modelling human teaching tactics and strategies for Tutorimh systems: 14 years on. International Journal of Artificial Intelligence Education (earlyview), 1–12).Google Scholar
  11. Buchanan, R., Holmes, K., Preston, G., & Shaw, K. (2015). The global and the local: Taking account of context in the push for technologization of education. In S. Bulfin, N. F. Johnson, & C. Bigum (Eds.), Critical perspectives on technology and education (pp. 227–244). New York: Palgrave Macmillan.CrossRefGoogle Scholar
  12. Carroll, J., & McKendree, J. (1987). Interface design issues for advice-giving expert systems. Communications of the ACM, 30(1), 14–31.CrossRefGoogle Scholar
  13. Christensen, R. (1997). Effect of technology integration education on the attitudes of teachers and their students (Ph.D. thesis). University of North Texas.Google Scholar
  14. Cole, D. (2014). The Chinese room argument. In Stanford encyclopedia of philosophy. Available on: https://plato.stanford.edu/entries/chinese-room/. Last accessed on 05/02/2019.
  15. Coll, C. (1990). Un marco de referencia psicológico para la educación escolar: la concepción constructivista del aprendizaje y de la enseñanza”. En C. Coll, J. Palacios, A. Marchesi (Comps.), Desarrollo psicológico y educación. II. Psicología de la Educación. Madrid. Alianza.Google Scholar
  16. Flood, M. (1951). Report on a seminar on organizational science. Santa Monica: CA: The RAND Corporation.Google Scholar
  17. Freire, P. (1996). Pedagogy or the oppressed. London: Penguin Books.Google Scholar
  18. Guilherme, A. (2014). Reflexions on Buber’s ‘Living-Centre’: Conceiving of the Teacher as ‘the builder’ and teaching as a ‘situational revelation’. Studies in Philosophy and Education, 34(3), 245–262.CrossRefGoogle Scholar
  19. Guilherme, A., Santos, B. S., Spagnollo, C. (2017). Teachers’ lifelong learning: Emerging dialogues from gert biesta’s philosophical views. Policy Futures in Education, 861–873.CrossRefGoogle Scholar
  20. Kuhn, T. (1977). The essential tension (pp. 240–265). Chicago: University of Chicago Press.CrossRefGoogle Scholar
  21. Lacasa, P. (1994). Piaget and Vygotsky: A convergent approach to ‘consciousness’, ‘activity’, and ‘word’. In A. Rosa, & J. Valsiner (Eds.), Explorations in social-cultural studies , Historical and Theoretical Discourse, 2, Madrid: Fundacion Infacia y Aprendizaje.Google Scholar
  22. Laura, R. S., & Chapman, A. (2009). The technologisation of education: Philosophical reflections on being too plugged in. International Journal of Children’s Spirituality, 14, 3, 289–298.Google Scholar
  23. Lepper, M. R., & Woolverton, M. (2002). The wisdom of practice: Lessons learned from the study of highly effective tutors. In J. M. Aronson (Ed.), Improving academic achievement: Impact of psychological factors on education (pp. 135–158). New York: Academic.CrossRefGoogle Scholar
  24. McCorduck, P. (1979). Machines who think: A personal inquiry into the history and prospect of artificial intelligence. San Francisco, CA: Freeman.Google Scholar
  25. McCorduck, P. (1985). The universal machine: Confessions of a technological optimist. New York: McGraw-Hill.Google Scholar
  26. McCorduck, P. (1988). Artificial intelligence: An Aperçu. Daedalus, 177(1), 65–83.Google Scholar
  27. McDevitt, T. M., Ormrod, J. E., Cupit, G., Chandler, M., & Aloa, V. (2013). Child development and education. Frenchs Forest, Australia: Pearson.Google Scholar
  28. Mirowski, P. (2003). McCorduck’s machines who think after twenty-five years—Revisiting the origins of AI. AI Magazine, 135–138.Google Scholar
  29. Ohlsson, S. (1987). Some principles of intelligent tutoring. In R. W. Lawler & M. Yazdani (Eds.), Learning environments and tutoring systems (pp. 203–237). Alex: Norwood.Google Scholar
  30. Olney, A. M., D’Mello, S., Person, N., Cade, W., Hays, P., Williams, C., et al. (2012). Guru: A computer tutor that models expert human tutors intelligent tutoring systems. In Proceedings of the 11th International Conference, ITS 2012, Chania, Crete, Greece, 14th18th June (pp 127–144). Dordrecht: Springer.Google Scholar
  31. Postman, N. (1995). The end of education: Redefining the value of school. New York: Knopf.Google Scholar
  32. Ridgway, J. (1988). Of course ICAI is impossible. Worse though, it might be seditious. In J. Self (Ed.), Aritificial intelligence and human learning. London: Chapman and Hall Computing.Google Scholar
  33. Säfström, C.A. (2004). Den pedagogiska psykologin, differentieringsfrågan och den liberal-demokratiska värlfärdsstaten [Educational psychology, the issue of differentiation and the liberal democratic welfare state]. In J. Bengtsson (Ed.), Utmaningar i filosofisk pedagogik [Challenges in philosophical education]. Lund: Studentlitteratur.Google Scholar
  34. Searle, J. (1980). Minds, brains and programs. Behavioral and Brain Sciences, 3, 417–457.CrossRefGoogle Scholar
  35. Searle, J. (2010). Why dualism (and materialism) fail to account for consciousness. In R. E. Lee (Ed.), Questioning nineteenth century assumptions about knowledge, III: Dualism. NY: SUNY Press.Google Scholar
  36. Selwyn, N. (2010). Looking beyond learning: Notes towards the critical study of educational technology. Journal of Computer Assisted Learning, 26(1), 65–73.CrossRefGoogle Scholar
  37. Turing, A. (1950). Computing machinery and intelligence. Mind, 59, 433–460.CrossRefGoogle Scholar
  38. Vygotsky, L. S. (1995). El desarrollo de los procesos psicológicos superiores. Barcelona: Crítica.Google Scholar
  39. Warschauer, M., Knobel, M., & Stone, L. (2004). Technology and equity in schooling: Deconstructing the digital divide. Educational Policy, 18(4), 562–588.CrossRefGoogle Scholar

Copyright information

© Springer Nature Singapore Pte Ltd. 2019

Authors and Affiliations

  1. 1.Pontifícia Universidade Católica do Rio Grande do SulPorto AlegreBrazil

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