Two-Layer Ontology-Based Knowledge Framework for Blended Learning: A Case Study in Higher Education

Abstract

Blended learning has gained increasing prominence in higher education institutions for its flexibility and potential to enhance instructional effectiveness. However, the absence of a structured and integrated knowledge representation often hinders its systematic development and intelligent innovation. This study proposes a novel two-layer knowledge framework developed using knowledge engineering methods. The first layer models the instructional process using unified modeling language with the plan-do-check-act cycle, including analyze, design, develop, implement, and evaluate phase. The second layer adopts an ontology-based approach to represent the key components of blended learning, including human, pedagogical, technological, and institutional support domains, along with their semantic relationships throughout the instructional phases. The concepts and properties were extracted through thematic analysis, natural language processing, and text mining. Ontology construction was performed in the Protégé environment, supporting semantic interoperability and structured knowledge reuse. The consistency and soundness of the framework were evaluated through formal concept analysis, a property-based quality measurement approach. This research presents a reusable and extensible knowledge engineering solution that integrates instructional process modelling with domain-level semantics, enabling future applications in intelligent tutoring systems, curriculum design, and organizational support in higher education.