THE ROLE OF ADAPTIVE AI AGENTS IN SHAPING INDIVIDUAL LEARNING TRAJECTORIES IN HIGHER EDUCATION: DESIGN, IMPLEMENTATION, AND EMPIRICAL EVALUATION

Authors

  • Iskandarova Ziyoda Abdumajidovna Iskandarova Ziyoda Abdumajidovna Author
  • Iskandarova Marjona Shuxrat qizi Iskandarova Marjona Shuxrat qizi Author

Keywords:

Adaptive AI agents, personalized learning, higher education, learning analytics, individualized learning trajectories, intelligent tutoring systems.

Abstract

The transformation of higher education toward competency-based and student-centered paradigms necessitates scalable mechanisms for personalized learning. Adaptive Artificial Intelligence (AI) agents provide dynamic, data-driven solutions for constructing individualized learning trajectories based on continuous learner modeling and predictive analytics. This study designs and experimentally validates an adaptive AI agent architecture implemented within an undergraduate academic environment. Using a quasi-experimental design with control and experimental groups (N = 124), the impact of the adaptive system on academic achievement, engagement, and self-regulated learning was measured. Statistical analysis demonstrates significant improvements in performance outcomes (p < 0.001) and engagement metrics among students supported by adaptive AI agents. The results confirm that trajectory-level personalization through intelligent agents enhances learning efficiency and institutional adaptability.

Author Biographies

  • Iskandarova Ziyoda Abdumajidovna, Iskandarova Ziyoda Abdumajidovna

    Senior Lecturer, Department of Computer and Software Engineering,

    Jizzakh Polytechnic Institute,

  • Iskandarova Marjona Shuxrat qizi, Iskandarova Marjona Shuxrat qizi

    Bachelor’s student at Tashkent State University of Economics

References

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Published

2026-02-26

Issue

Vol. 3 No. 1 (2026): ADVANCES IN RESEARCH AND INNOVATION SOLUTIONS

Section

Articles