Keywords
continuous learning
digital educational ecosystems
learning analytics
educational data integration
personalized learning
higher education institutions
How to Cite
Abstract
Abstract. The article examines digital pedagogy as a conceptual foundation for continuous learning in higher education within the context of digital transformation. The study is motivated by the need to reconsider traditional approaches to teaching and learning, which no longer fully meet the demands of the digital economy, rapid technological development, and individualized educational pathways. Although higher education institutions actively implement digital learning platforms, learning management systems, artificial intelligence, and learning analytics, educational data remains fragmented across different information systems, limiting their effective use for evidence-based pedagogical decision-making, personalized learning, and lifelong learning support.
The purpose of the study is to develop a conceptual model of digital pedagogy that ensures continuous learning through the integration of learner-centred pedagogical principles, digital educational ecosystems, learning analytics, and educational data integration. Particular attention is paid to the relationships among digital technologies, pedagogical design, learning analytics, and personalized learning trajectories.
The study demonstrates that digital pedagogy should be understood not merely as the use of digital technologies but as a learner-centred pedagogical paradigm focused on students' individual needs, learning activities, and continuous professional development. Effective continuous learning requires integrated digital educational ecosystems capable of consolidating information from multiple educational services into a unified data environment. Educational data integration provides the basis for learning analytics, early identification of learning difficulties, personalization of learning, and informed pedagogical decision-making.
The proposed conceptual framework may serve as a methodological basis for designing digital educational environments, improving learner support systems, and implementing learning analytics in higher education. Future research should focus on developing integrated learner profile models and evaluating their effectiveness in supporting personalized and continuous learning.
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