Improving Collaborative Learning Using Pervasive Embedded System-Based Multi- Agent Information and Retrieval Framework In Educational Systems

Abstract

E-learning is a form of Technology Supported Education where the medium of instruction is through Digital Technologies, particularly Computer Technology. An instance is the use of search engines like Google and Yahoo, which aid Collaborative Learning. However, the widespread provision of distributed, semi-structured information resources such as the Web has obviously brought a lot of benefits; but it also has a number of difficulties. These difficulties include people getting overwhelmed by the sheer amount of information available, making it hard for them to filter out the junk and irrelevancies and focus on what is important, and also to actively search for the right information. Also, people easily get bored or confused while browsing the Web because of the hypertext nature of the web, while making it easy to link related documents together, it can also be disorienting. To alleviate these problems, the Web Information Food Chain Model was introduced. How effective has this been with the dynamic nature of computing technologies? Pervasive computing devices enable people to gain immediate access to information and services anywhere, anytime, without having to carry around heavy and impractical computing devices. Thus, the bulky PCs become less attractive and being slowly eroded with the development of a new generation of smart devices like wireless PDAs, smart phones, etc. These embedded devices are characterized by being unobtrusively embedded; completely connected; intuitively intelligent; effortlessly portable and mobile; and constantly on and available. This paper presents the use of embedded systems and Intelligent Agent-Based Web Information Food Chain Model in Multi-Agent Information and Retrieval Framework (IIFCEMAF), to realizing full potentials of the internet, for users' improved system of collaborative e-learning in education.