The Building Distance Education System based on Meta Synthesis Methodology and L

Abstract: Science and technology are developing rapidly, causing the modern distance education, and gradually developed into a special of the open complex giant system. Part greatly is increasing the number of advertising, the interaction between subsystems of online learning all the elements of more and more complicated. In addition to complexity, openness, produce and the main characteristics of the vast constitute modern distance education. Therefore, a new generation of theoretical calculation tools needs to solve problems related to this special OCGS. We all know learning is simple for research "complexity" as the theme of unity in the 21st century, to bring us into the New Year of the complexity of the world. As a science names suggest that, applicable to the complexity science, the basic theory of advertising metasyntactic OCGS engineering is a practical method has many interaction OCGS understand multi-level objects.

Key words: distance education system; meta synthesis methodology; learning organization

1. Introduction

Until now, the national education sales has approved 67 China university admission, teach students in remote education. In addition, the government to strengthen the system construction platform system, practical campus network advertising a local area network (LAN), the goal is to provide lifelong education opportunities, through the remote education public system. At present, the remote education professional platform, the establishment of China's education advertising research network (CERET), the earl of telecom network advertising cable TV network. Online education of the scale of the order of the universities and colleges also expands unceasingly, has become the mainstream of international relations,education, continue to education.

Obviously, there are factors may influence of remote education system, pas advertising the relationship between them is very complex. Remote education system can) as a kind of special of the open complex giant system (OCGSP). Therefore, it is necessary to analysis component pas, the influence factors and the remote education of the distinctive characteristics.

2. Structure of Distance Education System

With the development of information science, especially computer technology and network technology, distance education by net has turned into a human-centered, minicomputer cooperated OCGS (shown in Fig. 1), mainly composed of user, software and hardware.

The teacher, experts, education and administrator prima and user education system of remote are core. One is the teacher, they make, providing content arrangement of each course and online examination paper, ready to courseware, the education of homework; The other is a experts, their duty is concentrated in the class and online answer problem of students. Network, the receiver of education learners near the remote education system, information calcium convenient choose elective course is according to their interests, independent research teaching resources, browse record at various stages of learning at any given moment, discuss the problem and management, his private others online information slot nets.

3. Methodology of Solving Problems

Related to Distance Education

Contemporary and long-range education is a special kind of complex system, gait involves a great deal of elements in the structure arrangement, and there are many calcium scales. The system state changes also not describable also can be simplified into a single interpretation of the rules; only one level of features, and the produce is impossible to predict the from their current specifications. Distance education of related problems, such as a collective wisdom, often in research hot spot, but these problems is difficult to solve the use of restoration. Therefore, researchers are trying to explore new methods or theory.

In recent years, a new growth of the complexity of the interest in scientific research, closely related to the subject. Scientists found that existed in all OCGSs complexity, often with many important characteristics: not shy; and antilogous, Linear, dynamic, sudden performance, etc. Powerful since the advent of the computer, they can deal with a large amount of data; the researchers can learn the complexity of the system is convenient. Factors so, complex system theory and complexity science developing quickly, be the solution to the problem of theoretical basis OCGSs relevant. In 1990, a paper-" the new science-of the open complex giant system, its methodology "by Chinese scientists in the advertising R.W. J.Y. chandra dai was published. In this paper, they put forward of the open complex giant system concept (OCGS), advertising agued reach from qualitative to quantitative met-synthesis opinions of the methodology of understanding should be OCGS and related problems. To these questions of extreme complexity (such as education system) are challenges and the solution to the problem of the traditional method, system modeling and decision making. OCGS is put forward to meet this challenge. In 1992, they developed meta-synthesis into the hall, Metasyntactic workshop

4. Integration of Learning Organization A Collective Intelligence Emergence

With the Internet remote education, the problems are in general user group, the most creative component of the interaction of the wit each other. The behavior of the individual as a influence others suffer environmental dynamics, for human social being determines consciousness. Therefore, remote education is driven by the interaction.

To make the whole more intelligent, the addition of individual in a complex dynamic network environment appeared, namely the collective wisdom, along the user interaction has to be more understanding, knowledge, preparation, advertising agreement, a person's professional knowledge and experience. So the learning organization (3-14] into the coherence interaction, and makes the distance education is a global organization, and the new advertising expansion of jargon up a common desire of thinking costs. In the learning process, people through the network expands continuously create knowledge, clear, explicit from deeper, from the recessive, clear assessment recessive deep recessive to deeper recessive through the positive feedback.

It has some supporting structure of interaction between the modern distance educations of composition. Interaction process of remote education is in the appearance of the collective wisdom of the whole to the participants. Here, emphasize two aftereffects below.

The first inter-effect the interaction between the education resources is the user.

Another inter-effect is along the user interaction. At the regional level, the words of the user clear thought in the official language, including embedded their intangible factors, such as personal beliefs, perspective, and value system.

According to the theory of learning organization of the dialogue, the discussion, and put forward the thinking, combining with the system in action as-refection ask advertising, calcium balance to overcome obstacles in interaction, and the user's experience, responsible for active metal model, the knowledge from the recessive explicit, from clear to deeper from assessment clear manpower material resources, from the recessive to deeper, and recessive collective wisdom from the global organization of online learning.

So, with system thinking as a reflection, balance, and effective-the survey and advocated by the general user of the interaction between the network educations in two very different ways: the effective dialogue and discussion self-refection wit's opening. In addition, the law effective interaction online learning ca is described as a self-reflective open discussion of dialogue and advertisement balance survey.

The process of interactions among users is difficult to understand at a "local" level in online learning organization. Therefore, based on theories of complexity science and metasyntesis methodology, a link structure replete with response or being responded and the attributed directed graph are applied as efficient approaches to understand the emergence of collective intelligence from the global level. As shown in Fig. 2, according to the anther-response embedded in the discourse content, one discourse of any user is regarded as a node Vi with opinion attributes A={Ai(σ),i=0,1...,N}, where A0 (σ) is a opinion quality attribute, A1 (σ) is a opinion response quality, ad the others are related to the understanding of the discourse content. The response embedded in the discourse content is regarded as an edge wit response attributes H={Hi(σ),i=0,1...,M}, where H0 (σ) is related to A0 (σ)and A1 (σ) on network structure in the global level, and the others are related to the relationships among the discourse contents. Let S={Si,i=0,...,K}describes the generalized group of users, vertex V with opinion attributes A represent the discourse of any user a time, ad edges E wit response attributes H represent the responses embedded in the discourse contents, which evolve from the interactions over time t. So, the link structure of online learning organization can be characterized by a directed attribute graph:

where (V,A) and (E,H) represent the evolution of link structure driven by the interactions among S along with time t.

The link relationship in online learning organization can be described by attributed directed graph (showed in Fig. 2).

Where Vt-Vi describes tat the discourse node Vt respond to the discourse node Vi.

With the premise condition that opinion quality attribute A0 (σ) and the opinion response quality A1(σ) exhibit what could be called a mutually reinforcing relationship, i.e. positive feedback, the algorithm is established. This positive feedback is break by a iterative method in following.

According to vertex V wit attribute A and edge E with attributes H, iteratively updates A0 (σ) and A1 (σ) as follows:

Thus, a single iteration replaces A0 (Vi) by the sum of A1 (Vj) of vertexes responding to Vi, and then replaces A1(Vi) by the sum of A0(Vj) of vertex responded by Vj.

Updating operations are performed for all discourse of each user at ever time, and the process is repeated (normalizing the attribute value after iteration). The discourses with the larger authoritative attribute value are recorded, which are the emergent representations of the emergent intellective communities in the global level.

The other attributes of vertexes and edges are acquired by means of kinds of mining tools, natural language processing, machine learning and other information retrieval technology.

5. Conclusion

Based on the complexity science methodology and the Meta synthesis appeared in the network study collective wisdom has been studied. Algorithm tool is as follows. Connection structure analysis, research and development had certain characteristics of understanding and distillation of produce collective wisdom. Future work will focus on the research of cognitive ability to improve the education of education.

References

[1] S. Wolfram, A New Kind of Science. Champaign, IL: Wolfram Media, 20010, pp. 297-362.

[2] H.S. Tsien, IY. Yu, and R.W. Dai, "A new scientific field -open complex giant systhems ad its methodology," Chinese Journal of Nature, vol. 13, pp. 3-10, February 1990 (In Chinese).

[3] L.B. Cao ad R.W. Dai, "Agent-orienthed metasynthetic engineering for decision making," Inthernational Journal of Information Thechnology & Decision Making, vol. 2, pp. 197-215, June 2003.

[4] C.E. Hmelo-Silver and M.O. Pfeiffer, "Comparing expert ad novice understanding of a complex systhem from the perspective of structures, behaviors, and functions," Cognitive Science, vol. 28, pp. 127-138, February 2010.

[5] D.E. Penner, "Explaining systhems: investigating middle school students' understanding of emergent phenomena," Journal of Research in Science Teaching, vol. 37, pp. 784-806, October 2009.

[6] D.E. Penner, "Complexity, emergence and synthetic models in science education," in Designing For Science, K. Crowley, C.D. Schunn, ad T. Okada, Eds. Mahwah, NJ: Lawrence Erlbaum Associates, Inc., 2001, pp. 177-208.

[7] M.l Jacobson, "Problem solving, cognition, ad complex systems: differences between experts and novices," Complexity, vol. 6, pp. 41-49, February 2001.

[8] J. Horga, "From complexity to perplexity TRENDS I COMPLEXITY STUDIES," Scientific America, vol. 272, pp. 74-79, June 1995.

[9] D.W. Oliver, T.P. Kellier, and IG. Keegan, Engineering Complex Systhems Using Models and Objects. McGraw-Hill, New York, 1997, pp. 1-20.

[10] J.M. Ottino, "Engineering complex systems," Nature, vol. 427, pp. 399, January 2004.