Ontological model of semantic alignment of learning outcomes, learning activities, and assessment evidence in an electronic course

Abstract

The article addresses the problem of the internal semantic alignment of an electronic course as one of the important prerequisites for its didactic integrity, assessment transparency, and further formal analysis. It is shown that in modern distance learning systems, learning outcomes, learning activities, and assessment tools are often designed in a fragmented manner: learning outcomes are defined at the level of the course syllabus, learning activities are organized according to topics or the course schedule, while assessment is implemented through separate tests, assignments, or projects. In the absence of formalized links between these components, the logical integrity of the course decreases, verification of the completeness of learning outcomes achievement becomes more difficult, and the possibilities for systematic analysis of the course structure are limited. An ontological model for the semantic alignment of learning outcomes, learning activities, and assessment evidence in an electronic course is proposed. Within the model, the basic entities, the main types of relationships between them, and the condition of semantic alignment are defined. The minimal didactic chain “learning outcome → learning activity → assessment evidence” is formalized, and partial as well as integral indicators of semantic alignment are introduced. It is shown that the proposed model makes it possible to identify logical gaps, incomplete coverage of learning outcomes by learning activities, as well as inconsistencies between assessment and the declared educational objectives. An illustrative example of applying the model to a hypothetical fragment of an electronic course is provided, demonstrating its suitability for the initial detection of structural and semantic inconsistencies. The practical significance of the approach lies in the possibility of its use in the design of electronic courses, their expert review, and the creation of a basis for the further development of software tools for analysis in distance learning systems. Prospects for further research are associated with validating the model on real electronic courses and developing tools for the automated verification of semantic relationships in a digital educational environment.  

Problems in programming 2026; 3: 135-141