| As information increases explosively, the diversity and | | | | Fourthly, the user information model and user |
| heterogeneity of knowledge in different domains make | | | | knowledge space model were studied, the user model |
| it difficult to represent and share knowledge. | | | | Ontology was built. The user information sub-Ontology |
| Meanwhile, the adaptive learning pattern is favored by | | | | to describe user's basic information, the user |
| more and more learners, and how to acquire the | | | | preference sub-Ontology to describe user's |
| knowledge in need from complex knowledge bases | | | | preference information, user performance |
| and construct personal knowledge system has | | | | sub-Ontology to describe user's performance |
| recently become a hot spot of research. | | | | information along with the user competency Ontology |
| Semantic learning web, which combines semantic web | | | | to describe user's learning skills were established |
| and web-based education technologies, shed lights on | | | | respectively. The semantic association among user |
| the development of modem education, and provide | | | | model ontology, domain knowledge ontology and |
| learners more efficient and high-quality intelligent | | | | learning resources description Ontology was analyzed. |
| services. This paper, which based on semantic learning | | | | A well-modeled basis was build for the adaptive |
| web, semantically described domain knowledge and | | | | e-learning system. |
| user pattern using Ontology technology, presented the | | | | Finally, the functional modules and system architecture |
| architecture of ontology-based adaptive e-learning | | | | of the ontology-based adaptive e-learning system |
| system (OntoAES) , provided the platform for | | | | (OntoAES) were presented, the correlation and |
| knowledge acquiring and sharing, and also provided | | | | application pattern between various Ontology and |
| learners with effective learning services based on | | | | system modules were studied. The adaptive e-learning |
| personal knowledge spaces and preferences. | | | | steps and process of the OntoAES were discussed. |
| Firstly, various theory models of teaching and learning | | | | Based on analysis of user learning behavior records, |
| processes were studied; the definition and description | | | | the analysis and definition of the potential learning |
| of learning behaviors in those theory models were | | | | resource relation pattern based on users' use of log, |
| analyzed; based on different characteristics of the | | | | the relation model and user preference model were |
| learning behaviors, the features and requirements of | | | | acquired through information extraction and data mining |
| the adaptive e-learning process was studied in order | | | | technologies. Learning path information in Domain |
| to provide the theory architecture and behavior model | | | | knowledge and user preference information could be |
| for the adaptive e-learning system; how to present | | | | refreshed; the model and method this paper presents |
| knowledge space was studied, domain knowledge | | | | were verified. |
| model and user knowledge space model were | | | | The main contributions are as follows: |
| established. | | | | 1) Present the relation model of knowledge space, and |
| Secondly, the features of domain knowledge was | | | | method to build domain knowledge Ontology based on |
| studied; as the complexity and diversity of domain | | | | knowledge engineering; |
| knowledge and the lack of ontology engineering | | | | 2) establish the Ontology of computer science domain |
| technology for domain experts make it difficult to | | | | and user model Ontology, present the architecture of |
| develop domain ontology, the method to establish | | | | the Ontology-based adaptive e-learning system; |
| ontology based on knowledge engineering was | | | | 3) Define the adaptive e-learning rules based on |
| proposed; the method to extract domain knowledge | | | | Ontology, build the matching model between user |
| concepts, define concepts hierarchical structure and | | | | preference ontology and study resource description |
| construct the relationship models were presented. The | | | | ontology, study resource relation model and |
| construction process to build domain ontology was | | | | preference model based on data using. |
| simplified. | | | | This paper provides the basis and guidance for |
| Thirdly, computer science was choose as the | | | | establishing the ontology of the Education Semantic |
| research domain, based on the domain knowledge | | | | Web, and design and building of the adaptive e-learning |
| space model, the knowledge taxonomy architecture | | | | system. The future work includes the perfection of the |
| and concept sets were constructed, and domain | | | | ontology and the function of the adaptive e-learning |
| knowledge ontology was built. On the basis of | | | | system, the study of the matching model in ontology |
| E-learning standards, learning resources description | | | | as well as the rules of adaptive e-learning based on |
| Ontology was established, which provided more | | | | ontology, and to provide learners an intelligent and |
| semantics to learning resources description model and | | | | efficient learning system. |
| more space to be expanded. | | | | |