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Knowledge is a cornerstone of intelligent tutoring systems, and an ontology provides the foundation for organizing and understanding complex knowledge structures. However, previous studies have focused on constructing ontologies based solely on the principles of objectivity and clarity while overlooking the subjective and situational nature of humanistic knowledge. Ontologies constructed on the principles of “clarity and objectivity” tend to be stable and objective but fail to capture the ambiguity and uncertainty inherent in humanistic knowledge. Learners' understanding of knowledge and its relationships are closely tied to the expression of that knowledge and influenced by the environment or context. For example, in response to the question “What becomes of snow when it melts?” some students may answer “spring,” which shows the diversity of humanistic knowledge. Thus, the situated, subjective, and generative features of knowledge should be considered when constructing ontologies.
This paper presents a method using collective intelligence to address the subjectivity and situational nature of humanistic knowledge in ontology construction. By leveraging the visualization capabilities of knowledge graphs and the support provided by the Learning Cell platform, a collective knowledge graph activity was designed to promote the construction and evolution of Chinese subject matter ontology through the participation of learners. One approach to addressing this issue is to analyze and investigate the process of learners' participation in learning activities using collective intelligence. Collective intelligence arises from communication, collaboration, competition, brainstorming, and similar activities and can be more powerful and wise than the sum of individual contributions. Scholars have recognized the value of collective intelligence in many fields, such as public decision-making, voting activities, social networking, and crowdsourcing (Yu et al., 2018). By incorporating collective intelligence into the ontology construction process, we can better capture the richness and complexity of humanistic knowledge. By embracing the subjectivity, generativity, and situatedness of knowledge, we can create more effective and relevant ontologies that are applicable to a wider range of contexts.
The essay is structured as follows:
- 1.
A systematic literature review was conducted on “ontology and knowledge graph,” “ontology construction and evolution,” and “ontology construction and evolution ideas” based on collective intelligence.
- 2.
An ontology evolution activity based on a collective knowledge graph was proposed. Following this proposal, an experiment was conducted to verify the findings, demonstrating how collective intelligence can improve the ambiguity and uncertainty present in knowledge.
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Finally, the contributions, limitations, and future research directions of this paper are discussed.
In summary, the study demonstrates the potential of collective intelligence in ontology construction and evolution. The incorporation of learners' knowledge, experiences, and perspectives can enrich the ontologies produced, resulting in a more complete and accurate representation of knowledge. Future research could explore additional methods to enhance and refine the proposed collective knowledge graph activity for ontology construction.