DOI:
https://doi.org/10.64782/istlj.3184144-171Keywords:
artificial intelligence in education, metacognition, age of transformation, Learning society, cognitive offloading, attention economy, lifelong learningHighlights
- Information abundance in the digital age fosters the illusion of learning rather than deep understanding.
- The classical learning society concept fails to address cognitive fragmentation caused by the attention economy.
- A society that manages its own learning prioritizes metacognition, critical filtering, and meaning-making over information access.
- Teachers must be repositioned as learning designers who foster metacognitive awareness rather than knowledge transmitters.
Highlights
Abstract
This article argues that the classical concept of the learning society has substantially lost its explanatory power in an age of transformation defined by artificial intelligence, digitalisation and the attention economy. Despite the unprecedented ease of access to information in contemporary society, a growing body of empirical research consistently demonstrates that information abundance does not translate into deep learning. Rather, it fosters cognitive fragmentation, measurable decline in critical thinking, and the illusion of learning, understood here as the widespread tendency to conflate exposure to information with genuine understanding. This widening gap between access and comprehension challenges the foundational assumptions upon which the learning society concept has historically rested. Drawing on purposive selection of peer-reviewed studies indexed in Scopus and WoS between 2021-2025, alongside policy documents produced by UNESCO and the OECD, the article offers a conceptual analysis of the epistemological, pedagogical and political limitations of the learning society framework in its classical form. The central thesis advanced is that the quantitative understanding of the learning society, which privileges the sheer volume of information consumed, must give way to the framework of a society that manages its own learning, characterized by critical filtering, metacognition, meaning-making and cognitive resilience as its defining competences. This reorientation fundamentally repositions teachers from transmitters of knowledge to designers of learning experiences. The article concludes by extending this conceptual argument to the policy domain, contending that educational policy frameworks, assessment practices and competence-based curricula must be reconfigured in accordance with this new orientation to adequately meetthechallengesofthedigitaltransformation age.
Listen to the Podcast
Share
How to Cite
Downloads
References
Bastani, H., Bastani, O., Sungu, A., Ge, H., Kabakcı, Ö., & Mariman, R. (2025). Generative AI without guardrails can harm learning: Evidence from high school mathematics. Proceedings of the National Academy of Sciences, 122(26), Article e2422633122. https://doi.org/10.1073/pnas.2422633122
Betthäuser, B. A., Bach-Mortensen, A. M., & Engzell, P. (2023). A systematic review and meta-analysis of the evidence on learning during the COVID-19 pandemic. Nature Human Behaviour, 7(3), 375-385. https://doi.org/10.1038/s41562-022-01506-4
Biesta, G. (2021). World-centred education: A view for the present. (1st ed.). Routledge. https://doi.org/10.4324/9781003098331
Bouckaert, M. (2023). The assessment of students’ creative and critical thinking skills in higher education across OECD countries: A review of policies and related practices (OECD Education Working Papers No. 293). OECD Publishing. https://doi.org/10.1787/35dbd439-en
Bozkurt, A., Hamutoğlu, N. B., Liman Kaban, A., Taşçı, G., & Aykul, M. (2021). Dijital bilgi çağı: Dijital toplum, dijital dönüşüm, dijital eğitim ve dijital yeterlilikler. Açıköğretim Uygulamaları ve Araştırmaları Dergisi, 7(2), 35-63. https://doi.org/10.51948/auad.911584
Cervin-Ellqvist, M., Larsson, D., Adawi, T., Stöhr, C., & Negretti, R. (2020). Metacognitive illusion or self-regulated learning? Assessing engineering students’ learning strategies against the backdrop of recent advances in cognitive science. Higher Education, 82, 477-498. https://doi.org/10.1007/s10734-020-00635-x
Chan, C. K. Y., & Hu, W. (2023). Students’ voices on generative AI: Perceptions, benefits, and challenges in higher education. International Journal of Educational Technology in Higher Education, 20(43). https://doi.org/10.1186/s41239-023-00411-8
Cogavin, D. (2024). Labour-power production and the skills agenda in lifelong learning: A critical policy analysis of the Skills and Post-16 Education Act 2022. Policy Futures in Education, 22(5), 774-792. https://doi.org/10.1177/14782103231183282
Council of Europe. (2025). Artificial intelligence and education: Regulating the use of AI systems in education: 2nd working conference, 24–25 October 2024, Council of Europe Headquarters, Strasbourg. https://rm.coe.int/prems-019925-gbr-2511-artificial-intelligence-and-education-a4-web-bat/1680b6c970
Davenport, T. H., & Beck, J. C. (2001, May). The attention economy. Ubiquity, 2001(1), Article 1. https://doi.org/10.1145/376625.376626
Erol, N. (2011). Toplumsal Değişme ve Eğitim: “Temel İlişkiler, Çelişkiler, Tartışmalar”. Gazi Akademik Bakış, 5(9), 109-122. https://izlik.org/JA54RS84XT
Fan, Y., Tang, L., Le, H., Shen, K., Tan, S., Zhao, Y., Li, X., & Gašević, D. (2024). Beware of metacognitive laziness: Effects of generative artificial intelligence on learning motivation, processes, and performance. British Journal of Educational Technology, 56(2), 489-530. https://doi.org/10.1111/bjet.13544
Floridi, L. (2023). The ethics of artificial intelligence: Principles, challenges, and opportunities. Oxford University Press. https://doi.org/10.1093/oso/9780198883098.001.0001
Gerlich, M. (2025). AI tools in society: Impacts on cognitive offloading and the future of critical thinking. Societies, 15(1), Article 6. https://doi.org/10.3390/soc15010006
Güner, O. (2022). Avrupa Birliği’nde dijital medya okuryazarlığına dair bir değerlendirme. Dicle Üniversitesi Sosyal Bilimler Enstitüsü Dergisi, (29), 473–499. https://izlik.org/JA42BR93PS
Haliti-Sylaj, T., & Sadiku, A. (2024). Impact of short reels on attention span and academic performance of undergraduate students. Eurasian Journal of Applied Linguistics, 10(3), 60-68.
Hardman, P. (2025, January 24). The impact of Gen AI on human learning: A research summary. Dr Phil’s Newsletter. https://drphilippahardman.substack.com/p/the-impact-of-gen-ai-on-human-learning
Hatipoğlu, Z., & Akduman, G. (2025). Yapay Zeka Çağında Çalışanların Sahip Olması Gereken Yetkinlikler. Journal of Sustainable Education Studies, Kongre Özel Sayısı (Ö4), 59-67. https://izlik.org/JA67HN55WX
Hutchins, R. M. (1969). The learning society. Frederick A. Praeger.
Jose, J., Cherian, J., Verghis, A. M., Varghise, S. M., S, M., & Joseph, S. (2025). The cognitive paradox of AI in education: Between enhancement and erosion. Frontiers in Psychology, 16, Article 1550621. https://doi.org/10.3389/fpsyg.2025.1550621
Kinnari, H., & Mikkonen, S. (2023). Subjectivities of the lifelong learner in ‘humanistic generation’: Critical policy analysis of lifelong learning policies among discourses of UNESCO, the Council of Europe and the OECD. International Journal of Lifelong Education, 42(4), 424-440. https://doi.org/10.1080/02601370.2023.2234089
Kosmyna, N., Hauptmann, E., Yuan, Y. T., Situ, J., Liao, X.-H., Beresnitzky, A. V., Braunstein, I., & Maes, P. (2025). Your brain on ChatGPT: Accumulation of cognitive debt when using an AI assistant for essay writing. MIT Media Lab. https://doi.org/10.48550/arXiv.2506.08872
Romö, M. B. (2024). Untangling ideologies in lifelong learning discourse. Journal of Education and Work, 37(5-6), 309-324. https://doi.org/10.1080/13639080.2024.2407764
Lee, H.-P., Sarkar, A., Tankelevitch, L., Drosos, I., Rintel, S., Banks, R., & Wilson, N. (2025). The impact of generative AI on critical thinking: Self-reported reductions in cognitive effort and confidence effects from a survey of knowledge workers. In Proceedings of the 2025 CHI Conference on Human Factors in Computing Systems (pp. 1-22). Association for Computing Machinery. https://doi.org/10.1145/3706598.3713778
Lee, U., & Park, S. (2024). Empowering ChatGPT with guidance mechanism in blended learning: Effect of self-regulated learning, higher-order thinking skills, and knowledge construction. International Journal of Educational Technology in Higher Education, 21(1), Article 16. https://doi.org/10.1186/s41239-024-00447-4
Lodge, J. M., & Loble, L. (2026). Artificial intelligence, cognitive offloading and implications for education [Report]. University of Technology Sydney. https://doi.org/10.71741/4pyxmbnjaq.31302475.v2
Ma, X., Liu, Q., & Zhang, W. (2025). The impact of multidimensional excessive social media use on academic performance: the moderating role of mindfulness. Frontiers in Psychology, 16, 1579509. https://doi.org/10.3389/fpsyg.2025.1579509
Mondal, P. K. (2024). Exploring the impact of digital distraction on learning: A qualitative analysis of university students experiences and strategies. International Journal of Emerging Knowledge Studies, 3(9), 625-632. https://doi.org/10.70333/ijeks-03-09-023
Nair, G. (2025). Tarım Devrimi’nden Yapay Zekaya Bilginin Toplumsallığı Bağlamında Sanayi 4.0 ve Bilgi Toplumu Tartışmaları. Politik Ekonomik Kuram, 9(3), 1338-1350. https://doi.org/10.30586/pek.1645266
Nasr, L., Abou-Zeid, H., & Atoui, M. (2025). Exploring the impact of generative AI ChatGPT on critical thinking in higher education: Passive AI-directed use or human-AI supported collaboration? Education Sciences, 15(9), Article 1198. https://doi.org/10.3390/educsci15091198
Novak, E., Daday, J., & McDaniel, K. (2023). A longitudinal study of preservice teachers’ digital distraction behaviors in computer-based learning environments. Computers & Education, 196, Article 104744. https://doi.org/10.1016/j.compedu.2023.104744
OECD. (2019). OECD Learning Compass 2030: A series of concept notes. OECD Publishing. https://www.oecd.org/education/2030-project/
Olssen, M. (2021). Constructing Foucault’s ethics: A poststructuralist moral theory for the twenty-first century. Manchester University Press. http://www.jstor.org/stable/j.ctv1p6hpfr
Risko, E. F., & Gilbert, S. J. (2016). Cognitive offloading. Trends in Cognitive Sciences, 20(9), 676-688. https://doi.org/10.1016/j.tics.2016.07.002
Rozenblit, L., & Keil, F. (2002). The misunderstood limits of folk science: An illusion of explanatory depth. Cognitive Science, 26(5), 521-562. https://doi.org/10.1207/s15516709cog2605_1
Said, S. A., & Abdallah, W. (2024). Lifelong learning for sustainable development: Aligning adult education with Sustainable Development Goal 4. In B. Alareeni & A. Hamdan (Eds.), Navigating the intersection of business, sustainability, and technology (pp. 259–269). Springer. https://doi.org/10.1007/978-3-031-62106-2_21
Selwyn, N. (2024). On the limits of artificial intelligence (AI) in education. Nordisk Tidsskrift for Pedagogikk og Kritikk, 10, 3-14. https://doi.org/10.23865/ntpk.v10.6062
Şahin, M., & Yıldız, S. (2024). 21. yüzyıl becerileri kapsamında ilkokul öğrencilerinin eleştirel düşünme ile dijital okuryazarlık becerileri arasındaki ilişki. Ordu Üniversitesi Sosyal Bilimler Araştırmaları Dergisi, 14(2), 1428-1442. https://doi.org/10.48146/odusobiad.1428634
Thornhill-Miller, B., Camarda, A., Mercier, M., Burkhardt, J.-M., Morisseau, T., Bourgeois-Bougrine, S., Vinchon, F., El Hayek, S., Augereau-Landais, M., Mourey, F., Feybesse, C., Sundquist, D., & Lubart, T. (2023). Creativity, critical thinking, communication, and collaboration: Assessment, certification, and promotion of 21st century skills for the future of work and education. Journal of Intelligence, 11(3), 54. https://doi.org/10.3390/jintelligence11030054
Toftness, A. R., Carpenter, S. K., Geller, J., Lauber, S., Johnson, M., & Armstrong, P. I. (2018). Instructor fluency leads to higher confidence in learning, but not better learning. Metacognition and Learning, 13(1), 1-14. https://doi.org/10.1007/s11409-017-9175-0
UNESCO. (2021). Reimagining our futures together: A new social contract for education. UNESCO Publishing. https://unesdoc.unesco.org/ark:/48223/pf0000379381
UNESCO Institute for Lifelong Learning. (2022). Making lifelong learning a reality: A handbook. UIL. https://unesdoc.unesco.org/ark:/48223/pf0000381857
UNESCO. (2024, February 15). Fostering a culture of lifelong learning in the digital era. https://www.unesco.org/en/articles/fostering-culture-lifelong-learning-digital-era
UNESCO Institute for Lifelong Learning. (2024). UIL annual report 2024. UIL. https://unesdoc.unesco.org/ark:/48223/pf0000394082
Xu, Y., Li, Y., Zhang, X., Gao, Q., Wen, Y., & Hwang, G.-J. (2025). Enhancing self-regulated learning and learning experience in generative AI environments: The critical role of metacognitive support. British Journal of Educational Technology, 56(4), 1842–1863. https://doi.org/10.1111/bjet.13599
Yan, L., Greiff, S., Teuber, Z., & Gašević, D. (2024). Promises and challenges of generative artificial intelligence for human learning. Nature Human Behaviour, 8(10), 1839-1850. https://doi.org/10.1038/s41562-024-02004-5
Yan, L., Sha, L., Zhao, L., Li, Y., Martinez-Maldonado, R., Chen, G., Li, X., Jin, Y., & Gašević, D. (2025). Practical and ethical challenges of large language models in education: A systematic scoping review. British Journal of Educational Technology, 56(1), 90-112. https://doi.org/10.1111/bjet.13370
Yılmaz, B., & Yiğit, E. Ö. (2024). 21. yüzyıl becerileri kapsamında 3. ve 4. sınıf öğrencilerinin eleştirel düşünme ile dijital okuryazarlık becerileri arasındaki ilişki. Ordu Üniversitesi Sosyal Bilimler Enstitüsü Sosyal Bilimler Araştırmaları Dergisi, 14(3), 903-922. https://doi.org/10.48146/odusobiad.1428634
Zimmerman, B. J. (2011). Motivational sources and outcomes of self-regulated learning and performance. In B. J. Zimmerman & D. H. Schunk (Eds.), Handbook of self-regulation of learning and performance (pp. 49–64). Routledge/Taylor & Francis Group.
Downloads
Published
License
Copyright (c) 2026 International Society that Learn Journal
This work is licensed under a Creative Commons Attribution 4.0 International License.
