Ontology Learning in Educational Systems

E-learning content and participants in the learning process are usually annotated with metadata. Complicated metadata models are necessary for organizing personalized learning, so an ontological metadata representation is used. Since ontologies represent static knowledge, changes in e-learning systems and related description metadata require frequent changes to corresponding ontologies. Only a few professionals in the educational domain have some expertise in ontology development. So, maximal possible automation is of great importance for the development and maintenance of knowledge models, needed for intelligent e-learning environments. Ontology learning is an approach for automatic ontology development and evolution, affected significantly by recent advances in Artificial Intelligence and Language Models. The main objective of this study is to explore and analyze ontology learning approaches and techniques and the specifics of their use in an intelligent e-learning environment. It examines and summarizes recent scientific research to reveal the degree of development and the extent to which ontology learning is applied to support personalized tutoring. The paper outlines trends and challenges of ontology learning from textual e-learning content and comprehensively discusses ontology learning and its applications in intelligent e-learning. It also describes a use case concerning the implementation and practical usage of ontology learning.