[IEEE 2011 IEEE 8th International Conference on e-Business Engineering (ICEBE) - Beijing, China (2011.10.19-2011.10.21)] 2011 IEEE 8th International Conference on e-Business Engineering - A Collaborative Learning System Based on Cloud and E-commerce
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A Collaborative Learning System Based on Cloud and E-commerce
Jian Liao School of Online and Continuing Education
Southwest University Chong Qing, China
Minhong Wang Faculty of Education
The University of Hong Kong Hong Kong, China email@example.com
AbstractThe number of learners using e-learning has been explosively increasing in the past decade by virtue of easy access to preferable educational resources at Internet. On the other hand, the number of teachers in schools or universities is growing slowly. As a result, instructional problems have emerged due to lack of sufficient support to learners in their e-learning process. Collaborative learning is suggested as a solution to this problem. However, current collaborative learning has focused on teamwork or group discussion without sufficient support to each individual. This paper presents a new model for collaborative e-learning called Collaborative Cloud, in which knowledge modelling and market economic mechanism are utilized to optimize the collaborative use of e-learning resources including teachers, students, and artifacts in collaboration. To implement the approach, cloud computing and electronic commerce are applied to connect learners and coordinate the resources in e-learning in a more effective way.
Keywords-collaboartive learning; cloud computing; grid
I. BACKGROUND With the increase of on-line learners, the star-shaped
topological structure in traditional learning or e-learning, i.e., one or few teacher is in the centre and all students are connected to the teacher, as is shown in first picture of figure 1, results in the tremendous contradiction. For example, the number of distance education students in China has risen from 500727 to 3558950 since 2003. However, the number of teachers still maintains unchanged approximately. Some common courses like advanced mathematics even contains thousands of students but just one teacher. Students almost have no chance to communicate with teacher.
Figure 1. Topological structure of different learning forms
One form of collaboration is learning in team, which specific tasks are given to a team and will be completed by its members collaboratively or co-operatively . The structure of this learning form in topology becomes
hierarchy, in which the teacher is on the top to assign the task for the team, the team leaders are in the middle to manage the team and other students are at the bottom, as is shown in second picture of figure 1. The shortage of this form is that finitude of team size and the number of members has limited a wider range of interaction among students.
Another form of collaborative learning is discussing in an online learning community by text, audio, video or other internet-supported synchronously or asynchronously  which the teacher and students connect freely, as is shown in the third picture of figure 1. Although it permits making collaboration in a broader scope, the participation and contribution of members are out of balance. Some members participate in interaction actively. By contrast, some of them barely communicate with others, even isolated.
In a word, online learners in current mass scale cannot collaborate effectively and efficiently in current learning forms. It needs a new collaborative form of learning according to newest learning theories and technologies.
II. RELATED THEORIES AND TECHNOLOGIES
A. Related Learning Theoretical Trends Recently, connectivism is beginning to get more attention
in the area of learning science. Different from traditional learning theories, connectivism proposes that learning not only takes place in the process of personal interaction with others, but also occurred in the connections among learners. In other words, the relations in a group is same important as the outcome of learning.
Moreover, Web 2.0 also advocates the idea that all members in group share and create the knowledge together . Refer to the idea of Deconstruction in Post-modernism , the old order in the relations among the learners in a group, such as class, grade, or school, should be broken up, and more reasonable order should be rebuilt according to personal demands and the degree of mastering knowledge. Not only the teacher but also learners who master certain knowledge or capability can tutor other learners in this knowledge unit.
In fact, the research of PALS (Peer Assisted Learning Support)  also shows learners can tutor learners themselves. In the case study of PALS, some students in a higher grade are organized to tutor the lower grade students and the results show they improve their learning performance significantly.
2011 Eighth IEEE International Conference on e-Business Engineering
978-0-7695-4518-9/11 $26.00 2011 IEEEDOI 10.1109/ICEBE.2011.14
To sum up, it will get to be important tendency of collaborative learning that exploring how to optimize the relations among the learners to make maximum performance based on their knowledge distribution and degree of mastering in a mass collaborative group.
B. Cloud Technology By using the cloud technology, users can get different
services based on their demands and pay it in real-time according to the quantity and quality of service, just like consuming the electric power or water for life. These services come from the background of the cloud system, which is constructed by a large number of virtual resources. As for the narrow definition of cloud, the virtual resources just consist of IT infrastructures, and the services are merely related to IT, software or Internet. However, in the general definition of cloud, the resources include people who possess certain professional knowledge and can provide tutorial services for other people .
C. Electronic commerce Electronic commerce consists of buying and selling of
products or services over electronic systems like the Internet. A large percentage of electronic commerce is conducted entirely electronically for virtual items such as access to premium content on a website. The sale and purchase transaction can be completed electronically and interactively in real-time. Electronic commerce can provide a mechanism of payment between buyer and seller with genuine or virtual concurrency .
III. PROPOSED SOLUTION OF COLLABORATIVECLOUD
A. Abbreviations and Acronyms According to the analysis of current learning forms and
related theories, new collaborative learning solution should include four aspects as follow.
1) Learners can not only acquire support from teachers but also from other learners who have mastered the related knowledge or skills.
2) The collaborative group allows mass users who come from anyplace to join in at any time. There is little influence for learners if some of them quit from the group.
3) The whole group is a mass complicated system of knowledge delivery and construction. The building of collaborative connection is flexible. It should not be built based on the traditional organization such as team, class, grade or school but on knowledge status of each member. Learners even do not take care of whom they collaborate with but what they can get from others.
4) It needs a mechanism to stimulate participation of members and balance the contribution of every member. The effort and performance of collaboration also be recorded and scaled in detail. On the one hand, learners request what they need from group with least costs. On the other hand, they provide what they can provide to obtain most benefits.
Based on these requirements, a new collaborative learning solution called collaborative cloud (CL) based on cloud computing and electronic commerce can be represented in figure 2. In this form, a learner can access the cloud management system in which other learners and teachers are connected to provide support upon requested.
Figure 2. Topological structure of collaborative cloud
B. Definition of Related Conception in Collaborative Cloud To describe the definition of collaborative cloud, it is
necessary to define the key elements in cloud as follows: Collaborators: All users in the cloud including
learners and teachers. They are treated as advance collaborators who master more knowledge to a greater extent.
Artifacts: Learning resources produced in the process of collaboration or provided by collaborators.
Resource: All what collaborators can obtain from the cloud, including collaborators and artifacts.
Collaborative Connection: A kind of relationship among collaborators. It is built among two or more collaborators when they prepare to interact with each other.
Collaborative Service: Collaboration among collaborators can be regarded as a collaboration service from one collaborator to another. As a kind of service, it can be recorded or assessed, and it costs some virtual concurrency.
Service Requestor & Service Provider: Each collaborator has two roles in the cloud. When he (or she) asks for help or wants to collaborate with others , the collaborator plays the role of service requestor. On the contrary, when he (or she) provides service to others, the collaborator is service provider.
Virtual Account: It is a virtual concurrency deposited for checking, savings, or brokerage use by collaborators. It also records the balance and the history of saving or payment.
Collaborative Cloud: It is the further application of the idea of cloud in collaborative learning. The foreground of collaborative cloud provides learning support services through the internet and the users pay for the services according to their quantity and quality. The background of the collaborative cloud is constructed by a large number of organized collaborators. And they form a virtual resource pool with redundancy and high availability.
IV. THE FRAMEWORK OF COLLABORATIVECLOUD
According to the definition of collaborative cloud and its key elements above, the framework of collaborative cloud is shown in figure 3:
Figure 3. Framework of collaborative cloud
In this picture, there are four sub systems in cloud which are resource pool, connection router, interaction platform and service transaction. In these sub systems, resource pool contains mass collaborator agents which represent collaborators behaviors. Connection router will establish collaborative connections based on service requestors demands. Interaction platform includes all kind of synchronous or asynchronous instructional services such as video conference, electronic whiteboard, remote assistance and so on. The sub system of Service transaction mainly deals with related transactions in each collaboration.
There is a typical flow in the cloud. First of all, collaborator needs to register their basic information and the degree of mastering knowledge or skill roughly. After this, the collaborator can request collaborative service. The cloud will understand the demands of service requestors and dispatch it to related collaborator agents. By contrast, the service provider will receive the request and acknowledge it if it is suitable. After that, the requestor will select a service provider according to the knowledge status, service quality and service price. Thus, the connection between or among the collaborators will be built and the tutorial or other learning support service will take place by the interaction platform. When the service finishes, requestor will pay for
the service and assess this service. Then, the knowledge status of both service requestor and provider will be updated in detail. If there are any issues or contradictions during the collaborative process, they can ask for managers of the cloud of which are also played the role by certain collaborators to arbitrate.
V. KNOWLEDGE MODEL IN COLLABORATIVECLOUD
A. Knowledge Structure How to model knowledge or skill is crucial for collaborative cloud. Ontology should be established in the cloud. Based on this, learning objective and knowledge status of collaborators can be described formally. The artifact also can be related to proper knowledge units. As a result, the collaborative connection can built more reasonably according to this. An example of knowledge structure is shown in figure 4. Each node is a knowledge unit. There are some relations among the knowledge unit such as part-of , sequence, sub and so on. Highlight sub diagram is the objective which the collaborator needs to master.
Figure 4. An example of knowledge structure in collaborative cloud
Table 1 lists basic relationships between two concepts in the constructed ontology, used in the prototype of the proposed collaborative cloud model.
TABLE I. THE BASIC RELATIONS AMONG KNOWLEDGE
Name Present Description
PartOf Par(A,B) Knowledge unitUnit A is a part of Knowledge Unit B
Sequential Seq(A,B) Knowledge Unit B is the prerequisite of Knowledge Unit A
Relevant Rel(A,B) Knowledge Unit A and Knowledge Unit B are co-relevant.
In fact, more types of relations of knowledge units can be listed and described in an ontology. In the ontology conceptualizing the learning environment, knowledge structure is decomposed into sub-concepts that are called knowledge units and their relationships. The prototype of the proposed model is constructed using the context of an e-learning course in software testing . Software testing is an important and mandatory part of software development. It is essential for evaluating the quality of software products by identifying defects and problems. Figure 4 also depicts the ontology which conceptualizes the knowledge structure in a software-testing course. It is constructed based on IEEE standards for software testing.
B. Knowledge Status Based on the knowledge structure ontology, the e-
learning prototype identifies a set of Knowledge units that relate to learning objective, and then generate a customized objective test to exam the learners knowledge roughly.
Another way to obtain initial knowledge status is self-assessment. Users can evaluate the degree of all or the top level of knowledge unit.
A users initial knowledge status over a certain knowledge unit is calculated using equation 1. The equation defines the knowledge status of the jth knowledge unit of the ith collaborator. Nj is the number of questions in the test relevant to knowledge unit j. Tijk is the score of the kth question of the ith collaborator on knowledge unit j. Sij is the score of self-assessment of user i on knowledge unit j., are the weight of test and self-assessment.
After this, the knowledge status of users can be updated dynamically during the process of using collaborative cloud. Service provider will receive the assessment result Khijfrom service requestor in the hth collaboration, as is shown in equation 2.
C. Knowledge Reasoning Table 2 lists two hidden relations. More comprehensive...