From IT to I-It: Digitalization, datafication, automation, and the teacher-student relationship
![](https://ojsdergi.com/ojsicons/gor.png)
![](https://ojsdergi.com/ojsicons/pdf.png)
DOI:
https://doi.org/10.37291/2717638X.202452394Keywords:
Automation, Datafication, Digitalization, Education, RelationalityAbstract
This conceptual article theorises the tensioned interplay between digitalization, datafication and automation and subjectness in education by asking what intensifying datafication and automation means for teacher–student relationships and how we understand and approach education. Theoretically, the paper draws on Buber’s ideas of the dialogical I–Thou and objectified I–It as the key forms of human relationships. The core argument is that increasing datafication and automation steers the teacher–student relationship towards an objectified I–It relationship instead of the dialogical I–Thou relationship, which Buber (and others such as Biesta, another main influencer of the present paper) saw as the ideal. Literature-informed examples of various forms of educational datafication and automation are provided to support and concretise the arguments.
References
Andrejevic, M., & Selwyn, N. (2020). Facial recognition technology in schools: Critical questions and concerns. Learning, Media and Technology, 45(2), 115–128. DOI: https://doi.org/10.1080/17439884.2020.1686014
Aspelin, J. (2020). Teaching as a way of bonding: A contribution to the relational theory of teaching. Educational Philosophy and Theory, 53(6), 588–596. DOI: https://doi.org/10.1080/00131857.2020.1798758
Baer, L., & Norris, D. (2017). Unleashing the transformative power of learning analytics. In C. Lang, G. Siemens, A. Wise, & D. Gašević (Eds.), Handbook of Learning Analytics (pp. 309–318). Society for Learning Analytics Research. DOI: https://doi.org/10.18608/hla17.026
Beerwinkle, A. L. (2021). The use of learning analytics and the potential risk of harm for K-12 students participating in digital learning environments. Educational Technology Research and Development, 69(1), 327–330. DOI: https://doi.org/10.1007/s11423-020-09854-6
Biesta, G. (2016). The rediscovery of teaching: On robot vacuum cleaners, non-egological education, and the limits of the hermeneutical worldview. Educational Philosophy and Theory, 48(4), 374–392. DOI: https://doi.org/10.1080/00131857.2015.1041442
Biesta, G. (2020). Risking ourselves in education: Qualification, socialization, and subjectification revisited. Educational Theory, 70(1), 89–104. DOI: https://doi.org/10.1111/edth.12411
Biesta, G. (2022). World-centred education: A view for the present. Routledge. DOI: https://doi.org/10.4324/9781003098331
Biesta, G. J., & Miedema, S. (2002). Instruction or pedagogy? The need for a transformative conception of education. Teaching and Teacher Education, 18(2), 173–181. DOI: https://doi.org/10.1016/S0742-051X(01)00062-2
Bigum, C., & Kenway, J. (2005). New information technologies and the ambiguous future of schooling—Some possible scenarios. In A. Hargreaves (Ed.), Extending Educational Change (pp. 95–115). Springer. DOI: https://doi.org/10.1007/1-4020-4453-4_5
Bradbury, A., & Roberts-Holmes, G. (2017). The datafication of primary and early years education: Playing with numbers. Routledge. DOI: https://doi.org/10.4324/9781315279053
Buber, M. (1937). I and Thou. T. & T. Clark.
Buber, M. (1968). Between Man and Man. Macmillan.
Charmé, S. (1977). The two I–Thou relations in Martin Buber’s philosophy. Harvard Theological Review, 70(1–2), 161–174. DOI: https://doi.org/10.1017/S0017816000017685
Crawford, K. (2021). The Atlas of AI. Yale University Press. DOI: https://doi.org/10.12987/9780300252392
Daliri-Ngametua, R., Hardy, I., & Creagh, S. (2022). Data performativity and the erosion of trust in teachers. Cambridge Journal of Education, 52(3), 391–407. DOI: https://doi.org/10.1080/0305764X.2021.2002811
Eduten. (2021). https://www.eduten.com/
Eynon, R. (2022). Datafication and the role of schooling: Challenging the status quo. In L. Pangrazio & J. Sefton-Green (Eds.), Learning to live with datafication (pp. 17–34). Routledge. DOI: https://doi.org/10.4324/9781003136842-2
Friesen, N. (2017). The pedagogical relation past and present: Experience, subjectivity, and failure. Journal of Curriculum Studies, 49(6), 743–756. DOI: https://doi.org/10.1080/00220272.2017.1320427
Hardy, I., & Lewis, S. (2017). The ‘Doublethink’ of data: Educational performativity and the field of schooling practices. British Journal of Sociology of Education, 38(5), 671–685. DOI: https://doi.org/10.1080/01425692.2016.1150155
Haslam, N. (2006). Dehumanization: An integrative review. Personality and Social Psychology Review, 10(3), 252–264. DOI: https://doi.org/10.1207/s15327957pspr1003_4
Hatt, B. E. (2005). Pedagogical love in the transactional curriculum. Journal of Curriculum Studies, 37(6), 671–688. DOI: https://doi.org/10.1080/00220270500109247
Ifenthaler, D., & Schumacher, C. (2016). Student perceptions of privacy principles for learning analytics. Educational Technology Research and Development, 64(5), 923–938. DOI: https://doi.org/10.1007/s11423-016-9477-y
Jarke, J., & Macgilchrist, F. (2021). Dashboard stories: How narratives told by predictive analytics reconfigure roles, risk, and sociality in education. Big Data & Society, 8(1), 20539517211025561. DOI: https://doi.org/10.1177/20539517211025561
Karjalainen, S. (2021). Doing joy: Performances of joy in children’s relations in early childhood and education settings [Doctoral dissertation, University of Oulu]. University of Oulu Repository. https://oulurepo.oulu.fi/bitstream/handle/10024/36647/isbn978-952-62-2974-4.pdf?sequence=1&isAllowed=y
Kirschner, P. A., & De Bruyckere, P. (2017). The myths of the digital native and the multitasker. Teaching and Teacher Education, 67, 135–142. DOI: https://doi.org/10.1016/j.tate.2017.06.001
Laakso, M. J., Kaila, E., & Rajala, T. (2018). ViLLE–Collaborative education tool: Designing and utilizing an exercise-based learning environment. Education and Information Technologies, 23(4), 1655–1676. DOI: https://doi.org/10.1007/s10639-017-9659-1
Lasky, S. (2005). A sociocultural approach to understanding teacher identity, agency, and professional vulnerability in a context of secondary school reform. Teaching and Teacher Education, 21(8), 899–916. DOI: https://doi.org/10.1016/j.tate.2005.06.003
Learning Analytics. (2019). Example 5: Automating learning analytics. https://en.learninganalytics.fi/analytics#case__4
Lupton, D. (2021). ‘Honestly, no, I’ve never looked at it’: Teachers’ understandings and practices related to students’ personal data in digitised health and physical education. Learning, Media and Technology, 46(3), 281–293. DOI: https://doi.org/10.1080/17439884.2021.1896541
Manolev, J., Sullivan, A., & Slee, R. (2019). The datafication of discipline: ClassDojo, surveillance, and a performative classroom culture. Learning, Media and Technology, 44(1), 36–51. DOI: https://doi.org/10.1080/17439884.2018.1558237
Mayer-Schönberger, V., & Cukier, K. (2013). Big data: A revolution that will transform how we live, work, and think. Houghton Mifflin Harcourt.
Merriam-Webster (n.d.). Automation. https://www.merriam-webster.com/dictionary/automation
Mertala, P. (2020). Paradoxes of participation in the digitalization of education: A narrative account. Learning, Media and Technology, 45(2), 179–192. DOI: https://doi.org/10.1080/17439884.2020.1696362
Mertala, P. (2021). Koulutuksen digitaalinen datafik(s)aatio. Kasvatus & Aika, 15(1), 43–61. DOI: https://doi.org/10.33350/ka.100161
Mertala, P., Lopez, S., Vartiainen, H., Saqr, M. & Tedre, M. (2024). Digital natives in the scientific literature A topic modeling based bibliometric analysis. Computers in Human Behavior, 108076. DOI: https://doi.org/10.1016/j.chb.2023.108076
O’Neill, C., Selwyn, N., Smith, G., Andrejevic, M., & Gu, X. (2022). The two faces of the child in facial recognition industry discourse: Biometric capture between innocence and recalcitrance. Information, Communication & Society, 25(6), 725–767. DOI: https://doi.org/10.1080/1369118X.2022.2044501
O'Neil, C. (2016). Weapons of math destruction: How big data increases inequality and threatens democracy. Penguin Books.
Pierlejewski, M. (2020). The data-doppelganger and the cyborg-self: Theorising the datafication of education. Pedagogy, Culture & Society, 28(3), 463–475. DOI: https://doi.org/10.1080/14681366.2019.1653357
Prensky, M. (2001). Digital natives, digital immigrants part 2: Do they really think differently? On the Horizon, 9(6), 1–6. DOI: https://doi.org/10.1108/10748120110424843
Sefton-Green, J., & Pangrazio, L. (2022). The death of the educative subject? The limits of criticality under datafication. Educational Philosophy and Theory, 54(12), 2072–2081. DOI: https://doi.org/10.1080/00131857.2021.1978072
Selwyn, N. (2003). ‘Doing IT for the kids’: Re-examining children, computers, and the information society. Media, Culture & Society, 25(3), 351–378. DOI: https://doi.org/10.1177/0163443703025003004
Selwyn, N. (2015). Data entry: Towards the critical study of digital data and education. Learning, Media and Technology, 40(1), 64–82. DOI: https://doi.org/10.1080/17439884.2014.921628
Selwyn, N. (2019). Should robots replace teachers? AI and the future of education. John Wiley & Sons.
Selwyn, N. (2022). Less work for teacher? The ironies of automated decision-making in schools. In S. Pink, M. Berg, D. Lupton, & M. Ruckenstein (Eds.), Everyday automation: Experiencing and anticipating automated decision-making (pp. 73–86). Routledge. DOI: https://doi.org/10.4324/9781003170884-6
Selwyn, N., Campbell, L., & Andrejevic, M. (2023). Autoroll: Scripting the emergence of classroom facial recognition technology. Learning, Media and Technology, 48(1), 166–179. DOI: https://doi.org/10.1080/17439884.2022.2039938
Selwyn, N., Hillman, T., Bergviken Rensfeldt, A., & Perrotta, C. (2021). Digital technologies and the automation of education—Key questions and concerns. Postdigital Science and Education, 5, 15–24. DOI: https://doi.org/10.1007/s42438-021-00263-3
Viatech. (2018, August). Maximizing classroom performance with facial recognition technology. https://www.viatech.com/en/2018/08/maximizing-classroom-performance-frt/
Viberg, O., Hatakka, M., Bälter, O., & Mavroudi, A. (2018). The current landscape of learning analytics in higher education. Computers in Human Behavior, 89, 98–110. DOI: https://doi.org/10.1016/j.chb.2018.07.027
Watters, A. (2021). Teaching machines: The history of personalized learning. MIT Press. DOI: https://doi.org/10.7551/mitpress/12262.001.0001
Williamson, B. (2016). Coding the biodigital child: The biopolitics and pedagogic strategies of educational data science. Pedagogy, Culture & Society, 24(3), 401–416. DOI: https://doi.org/10.1080/14681366.2016.1175499
Winter, P. (2011). Coming into the world uniqueness and the beautiful risk of education: An interview with Gert Biesta. Studies in Philosophy and Education, 30(5), 537–542. DOI: https://doi.org/10.1007/s11217-011-9254-7
Yu, J., & Couldry, N. (2022). Education as a domain of natural data extraction: Analysing corporate discourse about educational tracking. Information, Communication & Society, 25(1), 127–144. DOI: https://doi.org/10.1080/1369118X.2020.1764604
Downloads
Published
How to Cite
Issue
Section
License
Copyright (c) 2024 Journal of Childhood, Education & Society
![Creative Commons License](http://i.creativecommons.org/l/by-nc-nd/4.0/88x31.png)
This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.
Attribution: You must give appropriate credit, provide a link to the license, and indicate if changes were made. You may do so in any reasonable manner, but not in any way that suggests the licensor endorses you or your use.
NonCommercial: You may not use the material for commercial purposes.
NoDerivatives: If you remix, transform, or build upon the material, you may not distribute the modified material.
Author(s) must confirm that the Journal of Childhood, Education & Society retains all the copyrights unconditionally and indefinitely to publish articles.
Funding data
-
Research Council of Finland
Grant numbers 355523