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Chronic diseases patients often require constant dietary control that involves complicated interaction among factors such as the illness stage, the patient's physical condition, the patient's activity level, the amount of food intake, and key nutrient restrictions. This study aims to integrate multiple knowledge sources for problem solving modeling and knowledge-based system (KBS) development. A chronic kidney disease dietary consultation system is constructed by using Web Ontology Language (OWL) and Semantic Web Rule Language (SWRL) to demonstrate how a KBS approach can achieve sound problem solving modeling and effective knowledge inference. For system evaluation, information from 84 case patients is used to evaluate the performance of the system in recommending appropriate food serving amounts from different food groups for balanced key nutrient ingestion. The results show that, excluding interference factors, the OWL-based KBS can achieve accurate problem solving reasoning while maintaining knowledge base shareability and extensibility.

In recent years, flipped learning has received tremendous attention from educational practitioners and researchers. However, this study argues that existing e‐learning systems mainly serve for learning management and content delivery purposes, although they lack support for flipped learning. As an innovative educational approach, flipped learning requires more pedagogical elements, such as integrated instructional design and adaptive content delivery, to achieve effective direct instruction. This study aims to create a learning adaptivity design to support effective learning in the flipped individual learning space in which the teacher is absent. Because teaching involves various pedagogical and content knowledge sources, we propose a conceptual model of teaching as a function of the knowledge triad of Guideline (G), Teaching Activity (T), and Material (M). To realize this conceptualization, an ontological problem‐solving approach is used for knowledge‐based systems development to integrate the relevant knowledge sources. The knowledge model is created using the Protégé platform to develop OWL‐based domain ontology, task ontology, and SWRL‐based semantic rules to enable inference in the GTM triad for learning adaptivity. The case illustration shows that the knowledge‐based system prototype can adaptively guide student learning in the flipped individual learning space with the knowledge sources integrated.

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