Digital Educational Tribes: Platform Algorithms and Students’ Academic Identity
DOI:
https://doi.org/10.47451/phi2025-08-01Keywords:
digital educational tribes, algorithms as educators, academic identity, platform-based education, epistemic aesthetics, performative participation, educational fragmentation, cognitive resilience, digital ethnography, self-presentation in educational environments, academic subjectivity, epistemological instabilityAbstract
This article analyzes the mechanisms shaping students’ academic identity in the digital age, with a focus on educational platforms as emerging spaces of socialization. It explores the phenomenon of digital educational tribes — informal student communities formed around algorithmically curated content on learning platforms. The study examines how services such as Coursera, YouTube, and Google Scholar influence the development of academic identity through individualized learning trajectories, self-socialization styles, and content selection. The methodology combines qualitative interviews and digital ethnography. Central to the analysis is the algorithm as a hidden socializing agent that structurally substitutes the educator in the learning process. The theoretical framework draws on Michel Maffesoli’s concept of tribal sociality, Danah Boyd and D. Marwick’s theories of digital identity, and the platform-based epistemologies of Manuel Castells and Shoshana Zuboff. The findings reveal that students engage not only with educational content but also with norms of communication, cognitive styles, and algorithmically structured logics of interaction. The concept of digital educational tribes is introduced as an analytical model of informal online communities where educational participation is structured not around disciplines, but through algorithmic content selection, knowledge aesthetics, and rituals of inclusion. The key notion of algorithms as educators allows for a reconceptualization of technological systems as agents of educational influence, replacing traditional academic institutions in the process of structural interaction. Based on qualitative interviews and digital ethnography, the study shows that students’ educational behavior is increasingly shaped as a performative identity oriented toward public recognition, aesthetic engagement, and communicative visibility. The article articulates a critical stance on the risks of fragmentation and the loss of worldview coherence in platform-based education. It proposes theoretical approaches for integrating digital educational culture into the academic context without sacrificing cognitive depth, analytical resilience, or systemic pedagogy.
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References
Aagaard, J. (2021). The platformization of education: The student as a customer. Learning, Media and Technology, 46(3), 252–263. https://doi.org/10.1080/17439884.2021.1897002
Bonilla, C. A. (2022). Commodification in educational platforms: Learning as a service. Critical Studies in Education, 63(4), 481–499. https://doi.org/10.1080/17508487.2020.1796017
Bourdieu, P. (1984). Distinction: A social critique of the judgment of taste. London: Routledge & Kegan Paul.
Bourdieu, P. (1986). The forms of capital. In J. Richardson (Ed.), Handbook of Theory and Research for the Sociology of Education (pp. 241–258). New York: Greenwood.
Gallagher, M., Breines, M. R., & Blaney, D. (2020). Digital learning in post-pandemic higher education: Algorithmic pedagogies and student agency. Teaching in Higher Education, 25(4), 501–517. https://doi.org/10.1080/13562517.2020.1773308
Hardy, A., Bennett, A., & Robards, B. (Eds.). (2018). Neo-Tribes: Consumption, Leisure and Tourism. Cham: Springer. https://doi.org/10.1007/978-3-319-68207-5
Introna, L. D. (2016). Algorithms, governance, and governmentality: On governing academic writing. Science, Technology, & Human Values, 41(1), 17–49. https://doi.org/10.1177/0162243915587360
Jensen, L. X., Bearman, M., Boud, D., & Konradsen, F. (2022). Digital ethnography in higher education teaching and learning—a methodological review. Higher Education, 84, 1143–1162. https://doi.org/10.1007/s10734-022-00838-4
Kitchin, R. (2017). Thinking critically about and researching algorithms. Information, Communication & Society, 20(1), 14–29. https://doi.org/10.1080/1369118X.2016.1154087
König, R., & Wenzel, F. (2023). Digitalization of higher education: Understanding the role of recommendation systems. European Journal of Education, 58(1), 123–141. https://doi.org/10.1111/ejed.12527
Lawler, S. (2011). Symbolic capital and the construction of social identity. In M. Wetherell & C. T. Mohanty (Eds.), The SAGE Handbook of Identities (pp. 131–146). London: SAGE.
Lebaron, F. (2013). Symbolic capital. In A. Michalos (Ed.), Encyclopedia of quality of life and well-being research (pp. 6537–6543). Dordrecht: Springer. https://doi.org/10.1007/978-94-007-0753-5_2961
Maffesoli, M. (1996). The time of the tribes: The decline of individualism in mass society (D. Smith, Trans.). London: SAGE.
Marwick, D. (2013). Status update: Celebrity, publicity, and branding in the social media age. Yale University Press.
Papacharissi, Z. (2010). A networked self: Identity, community, and culture on social network sites. New York: Routledge. https://doi.org/10.4324/9780203876527
Rush Dreker, M., & Downey, K. J. (2023). Building Your Academic Research Digital Identity: A Step-Wise Guide to Cultivating Your Academic Research Career Online. Springer. https://doi.org/10.1007/978-3-031-50317-7
Ryan, R. M., & Deci, E. L. (2000). Self-determination theory and the facilitation of intrinsic motivation, social development, and well-being. American Psychologist, 55(1), 68–78. https://doi.org/10.1037/0003-066X.55.1.68
Selwyn, N. (2019). Should robots replace teachers? AI and the future of education (1st ed.). Polity Press. https://www.wiley.com/en-gb/Should+Robots+Replace+Teachers%3F%3A+AI+and+the+Future+of+Education-p-9781509528967
Sheldon, K. M., & Gunz, A. (2009). Psychological needs as basic motives, not just experiential requirements. Journal of Personality, 77(5), 1467–1492. https://doi.org/10.1111/j.1467-6494.2009.00589.x
Toquero, C. M. D. (2021). Digital ethnography on students’ authentic engagement in social media platforms during the global online experiment. Journal of Digital Educational Technology, 1(1), ep2104. https://doi.org/10.21601/jdet/11310
Vorobjovas-Pinta, O. (2021). Neo-tribalism through an ethnographic lens: A critical theory approach. In A. Pabel, J. Pryce, & A. Anderson (Eds.), Research paradigm considerations for emerging scholars (pp. 112–129). Bristol: Channel View Publications. https://doi.org/10.21832/9781845418281-011
Williamson, B., & Eynon, R. (2024). The Hidden Curriculum of Algorithms: How Personalization Shapes Learning Pathways. Learning, Media and Technology, 49(1), 22–41. https://doi.org/10.1080/17439884.2023.1964567
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