Published March 3, 2026 | Version v1
Dataset Open

EVOLUTION AND REVOLUTION IN ARTIFICIAL INTELLIGENCE IN EDUCATION

Authors/Creators

Description

This article examines the evolution and revolutionary transformation of artificial intelligence (AI) in the field of education. It analyzes how AI technologies have gradually developed from simple computer-assisted instruction systems to advanced intelligent learning environments capable of personalization, automation, and predictive analytics. The study highlights the role of AI in reshaping teaching methodologies, learning processes, assessment systems, and educational management. Particular attention is given to adaptive learning platforms, intelligent tutoring systems, learning analytics, and generative AI tools that enhance student engagement and support individualized learning paths. At the same time, the article discusses the challenges associated with AI integration, including ethical considerations, data privacy, digital inequality, and the need for teacher training. The research argues that AI represents not only an evolutionary improvement in educational technology but also a revolutionary shift that redefines the roles of teachers, learners, and institutions in the digital age. The paper concludes that the effective and responsible implementation of AI can significantly improve educational quality, accessibility, and efficiency while fostering lifelong learning skills required in the 21st century.

Files

237-240.pdf

Files (213.5 kB)

Name Size Download all
md5:f77f94d449deb5e7688af5847cbcccf0
213.5 kB Preview Download

Additional details

References

  • 1.Holmes, W., Bialik, M., & Fadel, C. (2019). Artificial intelligence in education: Promises and implications for teaching and learning. Boston, MA: Center for Curriculum Redesign.
  • 2.Luckin, R. (2018). Machine learning and human intelligence: The future of education for the 21st century. London: UCL Institute of Education Press.
  • 3.Russell, S., & Norvig, P. (2021). Artificial intelligence: A modern approach (4th ed.). Pearson.
  • 4.Zawacki-Richter, O., Marín, V. I., Bond, M., & Gouverneur, F. (2019). Systematic review of research on artificial intelligence applications in higher education. International Journal of Educational Technology in Higher Education, 16(39), 1–27.
  • 5.Chen, L., Chen, P., & Lin, Z. (2020). Artificial intelligence in education: A review. IEEE Access, 8, 75264–75278.
  • 6.UNESCO. (2021). AI and education: Guidance for policy-makers. Paris: UNESCO Publishing.
  • 7.Baker, R. S., & Inventado, P. S. (2014). Educational data mining and learning analytics. In J. A. Larusson & B. White (Eds.), Learning analytics (pp. 61–75). Springer.
  • 8.Siemens, G., & Baker, R. S. (2012). Learning analytics and educational data mining: Towards communication and collaboration. Proceedings of the 2nd International Conference on Learning Analytics and Knowledge, 252–254.
  • 9.Woolf, B. P. (2010). Building intelligent interactive tutors: Student-centered strategies for revolutionizing e-learning. Morgan Kaufmann.
  • 10.Graesser, A. C., McNamara, D. S., & VanLehn, K. (2005). Scaffolding deep comprehension strategies through intelligent tutoring technologies. Educational Psychologist, 40(4), 225–234.
  • 11.Holmes, W., Persson, J., Chounta, I. A., Wasson, B., & Dimitrova, V. (2022). Artificial intelligence and education: A critical view through the lens of human rights, democracy and the rule of law. Council of Europe.
  • 12.Popenici, S. A., & Kerr, S. (2017). Exploring the impact of artificial intelligence on teaching and learning. Research and Practice in Technology Enhanced Learning, 12(22), 1–13.
  • 13.Selwyn, N. (2019). Should robots replace teachers? AI and the future of education. Cambridge: Polity Press.
  • 14.Brynjolfsson, E., & McAfee, A. (2017). The second machine age: Work, progress, and prosperity in a time of brilliant technologies. W. W. Norton & Company.