Crowdsourcing mode-based learning activity flow approach to promote subject ontology generation and evolution in learning

Abstract

ABSTRACTSubject ontology can help implement the structured organization of knowledge for online learners and thus plays an important role in the learning process. However, building ontologies by experts is time-consuming, and the adaptation of such ontologies to different contexts might be a problem. Crowdsourcing, which allows users to build and refine ontologies during their learning process, has exhibited potential for solving this problem. In this study, a crowdsourcing mode-based learning activity flow approach is proposed to guide the learning of online learners while promoting the generation and evolution of subject ontologies using the learners’ contributions to the learning content. This flow makes full use of the learners’ wisdom during the learning process to promote self-regulated learning as well as the generation and evolution of the ontology. Based on the proposed approach, a learning support system was developed and an experiment conducted involving a Chinese lesson on “The Liangzhou Poem”. In the experiment, student participants built 722 triples, of which 584 evolved as formal items in the subject ontology. Moreover, all learners were able to construct a well-organized knowledge graph. Students in both high- and low-scoring groups contributed valuably to the knowledge generation and evolution of the subject ontology. Furthermore, while the widths of the knowledge constructed by students in high- and low-scoring groups were similar, their depths were substantially different. During this process, the crowdsourcing-based activity flow system achieved satisfactory technique acceptance, which means that the proposed approach and system are useful for the effective generation of subject ontologies while helping learners acquire knowledge.