Social Science and Human Research Bulletin

The development of the education market, academic credentials, digital data, and artificial intelligence is widening the gap between knowledge and actual competence, as well as between technical efficiency and human development. This study aims to clarify the humanistic foundation of education, analyze the mechanism of the instrumentalization of knowledge, and establish principles for restructuring education in the context of digital technology. Humanistic scientific methodology is employed in conjunction with the operations of analysis and synthesis, logic and history, abstraction and concretization, criticism and construction. The conceptual material of this study comprises the concepts of life, needs, capabilities, creativity, scientific knowledge, norms, power, the market, qualifications, actual competence, and artificial intelligence. The analysis reveals that education loses its humanistic function when norms, profit, academic credentials, or algorithms occupy the position of the end. Education attains legitimacy when it develops cognitive, creative, self-learning, reflective, and responsible capacities. The study concludes that human beings must retain their position as subjects, while science, the market, and technology must remain means serving life. 

humanistic scientific methodology, education, scientific knowledge, practical competence, artificial intelligence.

1. Achella, S. (2026). Networked humanity: An enactivist paradigm for aligning humans, nonhumans, and machines. Topoi. Advance online publication. https://doi.org/10.1007/s11245-025-10354-6 
2. Aflahah, S., Nisa, K., Aldeia, A. M. S., Marannu, B., Ramli, M., Windyasari, V. S., & Ruhutama, T. S. (2026). AI, ethics, and Islamic higher education: Navigating the tensions between practical risk mitigation and religious normativity. Jurnal Ilmiah Islam Futura, 26(1), 1–24. https://doi.org/10.22373/jiifv26.i1.32978 
3. Aimen, T. (2025). Cognitive freedom and legal accountability: Rethinking the EU AI Act’s theoretical approach to manipulative AI as unacceptable risk. Cambridge Forum on AI: Law and Governance, 1, Article e20. https://doi.org/10.1017/cfl.2025.4 
4. Alamaa, L., Hall, P., & Löfgren, K. (2026). Managers, professionals, or public servants? Organizational professionals in the public sector as hybrid professionals. Public Administration, 104(1), 90–100. https://doi.org/10.1111/padm.70000 
5. Alexander, C. S., & Sudeall, L. (2026). People-first court data. Annual Review of Law and Social Science, 22. Advance online publication. https://doi.org/10.1146/annurev-lawsocsci-042224-090838 
6. Alwali, A. (2026). Between bureaucracy and moral truth: Reclaiming ethical authenticity in contemporary institutional ethics, clinical and AI ethics as emblematic cases. Journal of Information, Communication and Ethics in Society, 1–18. https://doi.org/10.1108/JICES-12-2025-0393 
7. Amaral, E., Naranjo-Zolotov, M., & Bação, F. (2026). Unequal AI readiness: Institutional and digital disparities in e-government across the European Union. Telematics and Informatics, 107, Article 102400. https://doi.org/10.1016/j.tele.2026.102400 
8. Amoore, L. (2023). Machine learning political orders. Review of International Studies, 49(1), 20–36. https://doi.org/10.1017/S0260210522000031
9. Andersson, E., Enqvist, J., Tengö, M., & Aaltonen, V. A. (2026). Transforming the nature of cities: Stewardship and more-than-human agency. Current Opinion in Environmental Sustainability, 80, Article 101628. https://doi.org/10.1016/j.cosust.2026.101628
10. Ashford, S. J. (2026). Angles on agency: A research life betting on human initiative and potential. Annual Review of Organizational Psychology and Organizational Behavior, 13, 1–21. https://doi.org/10.1146/annurev-orgpsych-020625-112038
11. Augenstein, I., Baldwin, T., Cha, M., Chakraborty, T., Ciampaglia, G. L., Corney, D., DiResta, R., Ferrara, E., Hale, S., Halevy, A., Hovy, D., Ji, H., Menczer, F., Míguez, R., Nakov, P., Scheufele, D., Sharma, K., Surdeanu, M., & Zhang, A. (2024). Factuality challenges in the era of large language models and opportunities for fact-checking. Nature Machine Intelligence, 6, 852–863. https://doi.org/10.1038/s42256-024-00881-z
12. Aylward, A., Artiles, A. J., Kramarczuk Voulgarides, C., Tefera, A., Alvarado, S. L., & Noguera, P. (2026). Deepening the study of disproportionality in special education: A contextual analysis within suburban school districts. Exceptional Children, 92(4), 377–397. https://doi.org/10.1177/00144029251408685 
13. Azevedo, R. (2026). Using real-time process data of domain-specific learning processes to provide adaptive support for learning and instruction: Challenges and opportunities. Learning and Instruction, 104, Article 102363. https://doi.org/10.1016/j.learninstruc.2026.102363 
14. Baird, E. (2026). Caring for the artist as a human being: Suggestions for the contemporary college dance educator. Dance Education in Practice, 12(2), 9–14. https://doi.org/10.1080/23734833.2025.2570057 
15. Ballesteros, V. (2025). Objectivity, standardization, and epistemic injustice in psychiatry. Synthese, 205, Article 172. https://doi.org/10.1007/s11229-025-05016-4 
16. Bazine, N., Bernaud, J.-L., Guilbert, L., Saint-Germes, È., Pijoan, N., Ruiu-Renard, L., & Pignault, A. (2026). Who is more likely to find a job? A person-centred approach to the study of employability profiles among older jobseekers. Applied Psychology, 75(4), Article e70119. https://doi.org/10.1111/apps.70119 
17. Belsunces Gonçalves, A., & Forlano, L. (2026). World(coin) in the AI future: How sociotechnical fictions are instrumental to the cyberlibertarian transition. AI & Society, 41, 5411–5425. https://doi.org/10.1007/s00146-026-02913-1 
18. Bengtson, A., & Nielsen, L. (2026). Having enough of a say. Economics & Philosophy, 42(1), 91–110. https://doi.org/10.1017/S0266267125000124
19. Bourassa, G. N. (2026). ‘If you love teaching so much …’: Teaching against the injunctions of the capitalist state and refusing the weaponization of love. Critical Studies in Education, 67(2), 280– 297. https://doi.org/10.1080/17508487.2025.2470380 
20. Braeken, J., & van Laar, S. (2026). Reducing calibration bias for person fit assessment by mixture model expansion. Educational and Psychological Measurement, 86(1), 111–134. https://doi.org/10.1177/00131644251364252 
21. Brown, C. A. M. (2026). Science education’s responses to misinformation: A scoping review. Studies in Science Education. Advance online publication. https://doi.org/10.1080/03057267.2026.2654793 
22. Bubikova-Moan, J., Ferguson, L. E., & Andresen, A. (2026). The concept of critical thinking in teacher education: A systematic review. Review of Educational Research. Advance online publication.  https://doi.org/10.3102/00346543261438479
23. Børte, K., & Zeivots, S. (2026). Active learning in higher education: Inheriting pasts and emerging futures. Active Learning in  Higher  Education,  27(2),  207–219. https://doi.org/10.1177/14697874261426575 
24. De Graaf, J. (2026). The “Golden Age of Social Mobility” in postwar Europe: Class relations, educational expansion, and political stability in East and West. Journal of Social History, 59(3), 565–84. https://doi.org/10.1093/jsh/shaf039 
25. Desmond, C., Nowaczyk, M., Currie, S., Watt, K. G., & Richter, L. (2026). A human development framework to maximize returns of early life investments in low-and-middle income countries. Oxford Open Economics, 5, Article odag003. https://doi.org/10.1093/ooec/odag003 
26. Dong, Y., Ma, H., Jing, B., Wang, Q., Zhu, N., & Cao, P. (2026). Effect of computational thinking professional development on in-service teachers’ teaching and their students’ learning. Educational Technology and Society, 29(4), 91–107. https://doi.org/10.30191/ETS.202610_29(4).RP06
27. Ergunova, O., Mukhanova, G., & Somov, A. (2026). AI-supported student skills profiling integrating AI and EdTech into inclusive and adaptive learning. Social Sciences, 15(3), Article 209. https://doi.org/10.3390/socsci15030209 
28. Fawns, T., Boud, D., & Dawson, P. (2026). Identifying what our students have learned: A framework for practical assessment validation. Assessment & Evaluation in Higher Education. Advance online publication. https://doi.org/10.1080/02602938.2026.2620053 
29. Flannery, S., Keaveney, K., Wesselink, R., & Murphy, F. (2026). From theory to practice: Using the exploratory sequential design to develop a continuous professional development framework. Journal of Mixed Methods Research. Advance online publication. https://doi.org/10.1177/15586898261424023 
30. Hasanein, A. M., & Al-Romeedy, B. S. (2026). ChatGPT-assisted learning effectiveness and academic achievement: A mechanism-based model in higher education. Information, 17(3), Article 303. https://doi.org/10.3390/info17030303 
31. Heltai, J. I., Jani-Demetriou, B., Schmidt, I., Szabó, G., & Tarsoly, E. (2026). Pathways to ethical subjectivity: Participant transformation in tripartite collaborative research. Critical Inquiry in Language Studies, 23(2), 97–114. https://doi.org/10.1080/15427587.2025.2503708 
32. Karamizadeh, S., Shojae Chaeikar, S., & Salarian, H. (2026). Educational poverty and academic achievement: A meta-analysis exploring contextual moderators and policy implications. Education Sciences, 16(7), Article 1083. https://doi.org/10.3390/educsci16071083
33. Kennedy, J. V., & Michelfelder, D. P. (2026). Envisioning online learning spaces in higher education as spaces of radical openness: A philosophical scaffold for design. Journal of Philosophy of Education, 60(3), 503–521. https://doi.org/10.1093/jopedu/qhaf066 
34. Kovalova, E., Durana, P., Zvarikova, K., & Trulikova, I. (2026). From theory to debt decisions: Evidence on financial literacy among university students. Economies, 14(3), Article 100. https://doi.org/10.3390/economies14030100 
35. Parker-McLeod, J. (2026). Moving towards a professional police workforce: A scoping review of reflective, experiential and authentic learning in initial education. Policing: A Journal of Policy and Practice, 20, Article paag006. https://doi.org/10.1093/police/paag006 
36. Rachevski, I., & Gal, C. (2026). The educational foundations of entrepreneurial development: Comparing academic, certification and no formal entrepreneurship education pathways. International Social Science Journal. Advance online publication. https://doi.org/10.1111/issj.70059 
37. Roberts, D. (2026). Epistemic injustice, neurodivergence, and inclusive pedagogy: Dyslexia and augmentative communication in higher education. Disability & Society, 41(7), 1788–1809. https://doi.org/10.1080/09687599.2026.2659094
38. Santhosh, L., & Witt, L. J. (2026). AI won’t save us…yet: Reimagining AI’s potential to prioritize people. ATS Scholar, 7(2), 103–106. https://doi.org/10.1093/atsscholar/aapag009 
39. Sejdiu, S., & Ramadani, R. (2026). Catalytic communication in sustainability education: Bridging the knowledge–action gap through affective engagement and strategic praxis. Education Sciences, 16(3), Article 494. https://doi.org/10.3390/educsci16030494 
40. Shchyttsova, T., & Korablyova, V. (2024). Decolonizing knowledge production in Belarus and Ukraine. Topos, (2), 5–17. https://doi.org/10.61095/815-0047-2024-2-5-17 
41. Slonim, D. A., Penedo, J. M. G., & Lutz, W. (2023). Leveraging novel technologies and artificial intelligence to advance practice-oriented research. Administration and Policy in Mental Health and Mental Health Services Research, 51, 1–12. https://doi.org/10.1007/s10488-023-01309-3 
42. Vinson, B. (2026). Reflections on our times: Higher education in focus. The American Historical Review, 131(1), 1–26. https://doi.org/10.1093/ahr/rhaf788 
43. Wang, S., Prestridge, S., Forbes, D., & Wang, Y. (2026). Beyond access alone: Distance education in an AI and  open  knowledge era. Distance Education, 47(2), 181–184. https://doi.org/10.1080/01587919.2026.2681755