Adaptive Artificial Intelligence Algorithms in Chatbots for Personalized Learning Experiences in Higher Education

Authors

  • Oleksandr Mamon PhD in Pedagogical Sciences, Associate Professor of the Department of Mathematical Analysis and Informatics, Faculty of computer sciences, mathematics, physics and economics, Poltava V.G. Korolenko National Pedagogical University, Poltava, Ukraine https://orcid.org/0000-0002-9098-8635
  • Iryna Tkachenko Senior Lecturer of the Department of Philosophy and Pedagogy of Professional Training, Kharkiv National Automobile and Highway University, Faculty of Transport Systems, Kharkiv, Ukraine https://orcid.org/0000-0002-2686-6721
  • Olha Vasylenko Candidate of Art History, Associate Professor, Professor, Head of the Department of Music History, R. Glier Kyiv Municipal Academy of Music, Kyiv, Ukraine https://orcid.org/0000-0003-4431-8515

DOI:

https://doi.org/10.5281/zenodo.15138845

Keywords:

machine learning, higher education, personalized learning, academic success, educational platforms

Abstract

Adaptive artificial intelligence algorithms in chatbots represent an innovative tool for modernizing the educational process in higher education. These technologies enable the personalization of the learning experience by considering the individual needs of learners and contribute to improved academic performance and motivation by adapting learning objectives and continuous real-time interaction. This article aims to explore the potential of adaptive chatbots that use artificial intelligence to optimize the higher education learning process and their impact on learning efficiency and student motivation. Methods. To achieve the set goal, a comprehensive analysis of scientific research and practical application of adaptive chatbots in higher education was conducted. Machine learning algorithms used for creating personalized learning pathways were studied, as well as their integration with learning management systems (LMS), which ensures a more integrated and convenient learning process. Data on the use of chatbots based on large language models, capable of effectively processing large volumes of information and providing students with answers to complex questions, was also considered. Results. Adaptive chatbots demonstrated high effectiveness in personalizing the learning process, allowing automatic material adjustment according to the learner's learning style and knowledge level. They can collect data on students' performance, behavioral characteristics, and needs, optimizing the learning process. Integrating chatbots with LMS ensures convenience for learners and instructors by reducing routine tasks. Conclusions. Adaptive AI-based chatbots have the potential to transform educational approaches in higher education, offering personalized and effective solutions to improve academic success. However, to ensure their effective use, several technical and organizational issues need to be addressed, particularly regarding cybersecurity and integration with existing educational platforms.

Published

2025-04-04

How to Cite

Mamon, O., Tkachenko, I., & Vasylenko, O. (2025). Adaptive Artificial Intelligence Algorithms in Chatbots for Personalized Learning Experiences in Higher Education. Pedagogical Academy: Scientific Notes, (17). https://doi.org/10.5281/zenodo.15138845

Issue

Section

Theory and practice of education