The article examines the pedagogical potential of Artificial Intelligence (AI) in preventing, diagnosing, and resolving conflicts within educational environments. AI-driven systems—such as learning analytics, emotion-recognition tools, intelligent tutoring systems, and automated feedback technologies — support educators in identifying tension points, predicting behavioral risks, and offering timely interventions. The study emphasizes that AI does not replace the teacher’s socio-emotional role; instead, it enhances conflict-resolution processes by providing data-driven insights, reducing subjective biases, and strengthening communication between learners and teachers. The findings highlight the importance of ethical considerations, data privacy, and teacher readiness in implementing AI-supported conflict-management strategies.  

Artificial intelligence, conflict resolution, educational psychology, learning analytics

Holmes W., Bialik M., Fadel C. Artificial Intelligence in Education: Promises and Implications for Teaching and Learning. — Boston: Center for Curriculum Redesign, 2019.

Selwyn N. Should Robots Replace Teachers? AI and the Future of Education. — Cambridge: Polity Press, 2019.

Luckin R., Holmes W., Griffiths M., Forcier L.B. Intelligence Unleashed: An Argument for AI in Education. — London: Pearson, 2016.

Woolf B.P. Building Intelligent Tutoring Systems. — San Francisco: Morgan Kaufmann Publishers, 2009.

Kay, R., Reimann, P., Diebold, E., & Kummerfeld, B. (2013). Learning Analytics and Educational Data Mining in Practice. Journal of Educational Technology & Society, 16(1), 1–11.

VanLehn, K. (2011). The Relative Effectiveness of Human Tutoring, Intelligent Tutoring Systems, and Other Tutoring Systems. Educational Psychologist, 46(4), 197–221.

Nye, B. D., Graesser, A., & Hu, X. (2015). Autotutor and Family: A Review of 17 Years of Natural Language Tutoring. International Journal of Artificial Intelligence in Education, 25, 1–49.

D’Mello S., Graesser A. Multimodal Sentiment Analysis and Affect Detection in Learning Technologies // International Journal of Artificial Intelligence in Education. — 2015. — No. 25(2). — P. 205–210.

Zawacki‑Richter, O., & Latchem, C. Teaching in a Digital Age: Guidelines for Designing Teaching and Learning. — Vancouver: Commonwealth of Learning, 2018.

Ifenthaler, D., & Yau, J. Y.-K. Utilising Learning Analytics for Study Success: Reflections on Current Empirical Findings. — In: Learning Analytics: Fundaments, Applications, and Trends. Springer, 2020.

Baker, R. S., & Inventado, P. S. Educational Data Mining and Learning Analytics. — In: Learning Analytics. Springer, 2014. — P. 61–75.