Prospects for Integrating Virtual Reality and Artificial Intelligence into University Learning: Approaches to Developing Interactive Educational Environments

Abstract

The study aimed to identify key trends and define a conceptually coherent model for integrating virtual reality and artificial intelligence technologies into the university learning process. The methodology included a comparative method, document content analysis, expert verification, conceptual modelling, and scenario modelling. Three stages of expert verification produced a high level of consistency in evaluations across the criteria of necessity (mean – 4.8; median – 5), feasibility (mean – 4.4; median – 4) and innovation potential (mean – 4.8; median – 5), confirming the conceptual validity, practical feasibility and strong innovative capacity of the interactive educational environment model. This demonstrated the achievement of group consensus: 90% of experts assigned scores of 4-5 points in the second round and 96% in the third round, exceeding the 70% consensus threshold and confirming the model’s conceptual coherence and practical feasibility. The highest level of consistency was recorded in the pedagogical and cognitive-communicative components, which experts identified as essential for maintaining the didactic integrity of virtual reality and artificial intelligence as complementary technologies. The technological component received an average score of 4.4 points, confirming its flexibility but also indicating the need for further adaptation of university infrastructure. The managerial-analytical component had the lowest variability (interquartile range ≤1), reflecting stable expert agreement regarding its internal logic. The synthesis of the results made it possible to formulate three scenarios: an innovation-adaptive scenario, a technology-optimisation scenario and a transformation-forecasting scenario. These scenarios reflected varying levels of institutional readiness for digital transformation and made it possible to outline a gradual trajectory from local initiatives to a comprehensive interactive ecosystem. The practical value of the study lies in the fact that the proposed model can serve as a methodological basis for developing university digital strategies, designing educational programmes, and establishing systems for monitoring the quality of digital learning processes. It enables universities to develop their own strategies for implementing intelligent technologies in accordance with staff readiness, available infrastructure and pedagogical priorities