Ontological modeling of adult learning ecosystem as a personalization tool

J.V. Rogushina, K.Yu. Yurchenko

Abstract


The article is devoted to the development of methods for semantic expansion of adult learners' profiles for per sonalization of education in the context of the digital transformation. We analyse metadata standards used for describing of learners and learning objects and define that these standards have insufficient flexibility for pro filing adults, especially in the andragogical context. We consider some practical situations that demonstrate the need for additional semantic properties of the profile (professional specialisation, educational mobility and multilingualism, the life circumstances of the learner, special needs for inclusive learning, informal education and micro-qualifications, learning under fire in a state of martial law, and psycho-emotional trauma) and de termine the additional semantic properties and the expected effect of their use. On this base an approach to flexible extension of standards based on ontological modelling of the adult learning ecosystem is proposed. This approach uses classification of additional semantic properties of the profile of an adult learner by groups: type of educational activity, learning context, motivation, professional goal, social role, psycho-emotional state, institution. An prototype system for intelligent support of postgraduate students based on Semantic MediaWiki and large language mdels is described. The system implements a generation architecture with advanced search, combining ontologically structured knowledge with the capabilities of generative text analysis. Testing of the approach at the Institute of Software Systems of the National Academy of Sciences of Ukraine confirmed the effectiveness of semantic profiling for building personalised educational trajectories and intelligent search for educational resources.

Prombles in programming 2025; 4: 63-77


Keywords


ontological modeling; semantic profiling; adult learners; personalized learning; Semantic MediaWiki; large language models; digital learning ecosystem

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