© Springer-Verlag Berlin Heidelberg 2008 An E-Learning System Engineering Ontology Model on the Semantic Web for Integration and Communication WenAn Tan, FuJun Yang, Anqiong Tang, Suxi
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The founding process of the optimal group includes the following key steps:
1 According to grouping standard , the algorithm generates a matrix that consists
of the characteristics that need to be similar in the grouping standards and are from
the learner's characteristic model The system assigns all learners into the request K group using Fuzzy C Mean (FCM) clustering algorithm;
2 Pick out a learner from each group as representative who should be kept in the group and others should be deleted from group In our system, the representative may
be the arbitrary member in the group
3 Pick out a learner from learners who have not been assigned into any group, then find the group that the selected learner should be assigned to, using the data calcula-tion and comparison Finally assign the learner to the group that has been found Data calculation includes:
1) We calculate the group average distance d base on these characteristics which
needs to be similar
2) We calculate the group average varianceσbase on these characteristics that need to be complementary
3) For each group, calculate d-σ value
4) Finds out the group whose d-σ value is smallest among existing groups It is
the group that the learner should be assigned to
4 If all learners have been assigned in a special group, then grouping is over, else return to 2
In our system, we have adopted the ISODATA （iterative self-organization data
analysis techniques algorithm）clustering algorithm Its advantage is that the algo-rithm is clear and definite, clustering effectiveness is pretty well However, because each iteration needs to calculate the clustering centre again, the amount of calcula-tions is tremendous
7 Conclusion
The WBPCLS, into which “the intelligence course recommendation”, “the optimal group formation” and “the optimal collaborative partner discovery” have been im-ported, support not only collaborative learning, but also personal learning It is able to change learner's passive collaborative style into active one It will overcome the defi-ciency and shortcoming of current learning systems in the organization environment and will attract more learner's participation and improve the learning effectiveness and efficiency
References
1 Kim, W.: Directions for Web-Based Learning In: Liu, W., Li, Q., Lau, R (eds.) ICWL
2006 LNCS, vol 4181, pp 1–9 Springer, Heidelberg (2006)
2 Jianhua, Z., Kedong, L., Akahori, K.: Modeling and System Design for Web-Based Col-laborative Learning In: Proceedings of 2nd international conference on information, pp 89–
96 (2001)
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3 Liang, G., Weining, K., Junzhou, L.: Courseware Recommendation in E-Learning System In: Liu, W., Li, Q., Lau, R (eds.) ICWL 2006 LNCS, vol 4181, pp 10–24 Springer, Hei-delberg (2006)
4 Ying, L., Fuzong, L., Xue, W.: Using Agents in Web-Based Constructivist Collaborative Learning System Tsinghua Science and Technology 9(2), 189–196 (2004)
5 Serce, F.C., Yildirim, S.: A Web-Based Synchronous Collaborative Review Tool: A Case Study of an On-line Graduate Course Educational Technology & Society, vol 9 (2), pp 166–177 (2006)
6 Chang, C.-K., Chen, G.-D., Li, L.-Y.: Constructing a community of practice to improve coursework activity Computers & Education (accepted) (August 4, 2006) http://dx doi.org/10.1016/j.compedu.2006.05.003 (SSCI)
Trang 3F Li et al (Eds.): ICWL 2008, LNCS 5145, pp 446 – 456, 2008
© Springer-Verlag Berlin Heidelberg 2008
An E-Learning System Engineering Ontology Model on the Semantic Web for Integration and Communication
WenAn Tan, FuJun Yang, Anqiong Tang, Suxian Lin, and Xue Zhang
Software Engineering Institute Zhejiang Normal University
Jinhua, Zhejiang, P.R China jk76@zjnu.cn, yangfujun011@163.com, jk80@zjnu.cn,
{linsuxian,blacktulip119}@126.com
Abstract This paper investigates ontology-based approaches for representing
information semantics and in E-learning system A general E-learning system engineering (ESE) knowledge representation scheme, called an ESE ontology model, to facilitate communication and information exchange in heterogeneous E-learning systems The proposed approach focuses on how to support the inte-gration of heterogeneous E-learning systems, and how to complete information autonomy allowing the individual learners to keep their own information mod-els rather than requiring them all to adopt standardized terminology Mean-while, a communication model Based on SOAP and ontology, is designed for heterogeneous information systems interoperable communications A prototype
interface has been developed to validate the communication model
Keywords: Ontology, E-learning system integration, Information island,
Sys-tem Communication
1 Introduction
Since the world has entered the information era, the E-learning system integration has been the hot spots in education technology research, computer science and education, e-education technology, and other cross-cutting research field The flexible integra-tion of the E-learning system is a new research point on the educaintegra-tion technology file, which should improve the sharing of learning resource
During the process of the development of learning informationization, there are many application systems that have been developed by many education sectors Many of those systems are based on the development of functional modules, but also based on the model of development organizations With the changing needs of learning and the continuous expansion of functions, those application systems can not effectively quick adjustments for the change Meanwhile, the differences of the system architectures and the system resources semantic description of E-learning systems are difficult to achieve the sharing resources and systems integration The different information systems can be integrated by E-learning Application Integra-tion (EAI) Initially, educaIntegra-tion sectors focused their concern on the connecIntegra-tion of the internal systems of the application, and the integration of their own subsystems But now, more of the agencies would like to achieve the integration of Learner to
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Teacher to connect learning processes Of course, the realization of the latter is very difficult and complicated The core problem is difficult to achieve the communica-tion mechanism particularly between heterogeneous systems
Department of education issued the standards of E-learning management tion [1] is to address the problem developed, and its essence is to classify the informa-tion of China's E-learning into various types, and establish an informainforma-tion model by the approach data dictionary, in order to achieve the certainty and consistency of the semantic of the exchanged information Compared with this, a number of specific technical solutions are proposed by some foreign agencies in the same case for the interoperability issues of E-learning information systems, such as the E-learning wide interoperability framework (EIF, E-learning Interoperability Framework) imple-mented by the United States software and information industry associations in North America [2] For addressing the issues the ISO launched ISOTC184 as the interna-tional standard of industrial automation systems and integration areas Meanwhile, many technology vendors (such as Ariba, I2, Microsoft), some Technology Associa-tions (such as UDDI, QAGI), and several individual industries (such as RosettaNet from the electronical industry, BoleroNet from the financial services industry, and WISe of the insurance industry) have implemented various (not compatible) stan-dards To sum up, the existing solutions have mainly the following two aspect defi-ciencies: Existing interoperability frameworks depend on special systems too much to suit heterogeneous and complex systems Traditional methodology need to compile code for each application to achieve interoperability, based on their databases The methodology settles existing E-learning MIS system interoperability issues, which may be an effective solution However, development of the E-learning management information system needs realize an independent solution model to drive the commu-nication of the complex systems Because of the tightly required by coupling semantic
of information and communication data, so traditional communication models will not accommodate the changing of a information which should directly rise a large-scale modification of the communication model
In such circumstances, we established a heterogeneous information systems interop-erable communications model following the model of the E-learning information man-agement standards.[1] The model was implemented based on Web services technology
to achieve the seamless exchange of information among autonomous management in-formation system, E-learning management inin-formation resources databases, various units, and departments
The rest of this paper is organized as follows Section 2 designs the Analysis of the E-learning Integrated System; Section 3 discusses the relation of Ontology and E-learning system; Section 4, we provide the communications model of the system; Section 5 describes the methodology of data exchange; Section 5 presents a case study; Section 6 concludes the paper with perspectives
2 Integrated E-Learning System Analysis
E-learning system architecture is shown in Figure 1 The Web layer of the E-learning platform provides a Web interface and a range of services for users The E-learning platform is the application service layer of the topology which includes the integration
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of supply chain services of agent system-level unified data format and security au-thentication Agent layer is composed of the different companies which are scattered
in the supply chain, which have different advantaged education After the integrating and reengineering learning portfolio, these originally loose heterogeneous E-learning systems show integrity to learner Meanwhile, the integrated process is trans-parent to the user
2.1 Web Layer
Web layer is composed of the Web servers distributed around and browsers of the terminal-users The layer is the interface between the system and terminal-users The requests of the terminal-users are sent to the browsers of Web server in the form of RDF files to the information database of logistics The users receive inquiries in RDF file form from the Web server by RDF Parser Those RDF files are parsed with refer-ring to RDF Schema that is used to define parsers, and shown on the Internet
Agent 4
Agent 3
Agent 1
User 2
User 1
User n
Agent System Layer Web Services Layer
Agent 2
Application Services Layer
Ontology Database
E-learning Resource
Fig 1 Network topology for E-learning system
2.2 Application Services Layer
Application services layer receives Web service requests from Web services layer, and transmits services to the Agent system layer Application services layer is com-posed of the following three parts:
1) Analysis Module: The module is responsible to receive service requests from the Web services, and searches the service Registration Information database to find the agent system which provides the service Then the module transmits the service re-quests to the database server