Effective Tutorial Ontology Modeling on Organic Rice Farming for Non-Science & Technology Educated Farmers Using Knowledge Engineering

Abstract

Knowledge of the appropriate technologies for sustainable development projects has encouraged grass roots development, which has in turn promoted sustainable and successful community development, which a requirement is to share and reuse this knowledge effectively. This research aims to propose a tutorial ontology effectiveness modeling on organic rice farming as an appropriate technology based on sustainable development projects for non-science and technology educated farmers using knowledge engineering approach, using Phrao District in Chiang Mai Province, Thailand as a case study. The effective tutorial ontology model focuses on social science and technology ontologies based on Thai's curriculum of lower secondary school which provides biology, chemistry, math and physics concepts in order to effectively represent knowledge of the organic rice farming. The additional social science ontology knowledge developed in this research provides such a support to vocational learning and used by rural community in the case study to effectively navigate and utilize the appropriate technological knowledge of the sustainable development project knowledge to enhance their communities. The effectiveness of tutorial social science ontology in learning process was measured by counting and validating the average throughput of organic rice farming domain knowledge in learning process in terms of practicing domain knowledge, appropriate domain knowledge with their community and acquiring knowledge by themselves in both control and experimental groups. This study concludes by emphasizing the benefits of effective tutorial ontology modeling on organic rice farming for supporting knowledge transfer technique for non-science and technology educated farmers using knowledge engineering in the community of the case study to enhance their vocational lifelong learning. Ultimately, the tutorial ontology modeling in appropriate technology provides a knowledge transfer for non-science and technology educated farmers effectively.