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.