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

E-learning is a form of Technology SupportedEducation where the medium of instruction is throughDigital Technologies, particularly Computer Technology.An instance is the use of search engines like Google andYahoo, which aid Collaborative Learning. However, thewidespread provision of distributed, semi-structuredinformation resources such as the Web has obviouslybrought a lot of benefits; but it also has a number ofdifficulties. These difficulties include people gettingoverwhelmed by the sheer amount of information available,making it hard for them to filter out the junk andirrelevancies and focus on what is important, and also toactively search for the right information. Also, people easilyget bored or confused while browsing the Web because ofthe hypertext nature of the web, while making it easy to linkrelated documents together, it can also be disorienting. Toalleviate these problems, the Web Information Food ChainModel was introduced. How effective has this been with thedynamic nature of computing technologies? Pervasivecomputing devices enable people to gain immediate accessto information and services anywhere, anytime, withouthaving to carry around heavy and impractical computingdevices. Thus, the bulky PCs become less attractive andbeing slowly eroded with the development of a newgeneration of smart devices like wireless PDAs, smartphones, etc. These embedded devices are characterized bybeing unobtrusively embedded; completely connected;intuitively intelligent; effortlessly portable and mobile; andconstantly on and available. This paper presents the use ofembedded systems and Intelligent Agent-Based WebInformation Food Chain Model in Multi-Agent Informationand Retrieval Framework (IIFCEMAF), to realizing fullpotentials of the internet, for users’ improved system ofcollaborative e-learning in education

Amalthaea--information filtering and discovery using a multiagent evolving system

Thesis (M.S.)--Massachusetts Institute of Technology, Program in Media Arts & Sciences, 1997.Includes bibliographical references (p. 73-76).Alexandros G. Moukas.M.S

Personality representation: predicting behaviour for personalised learning support

The need for personalised support systems comes from the growing number of students that are being supported within institutions with shrinking resources. Over the last decade the use of computers and the Internet within education has become more predominant. This opens up a range of possibilities in regard to spreading that resource further and more effectively. Previous attempts to create automated systems such as intelligent tutoring systems and learning companions have been criticised for being pedagogically ineffective and relying on large knowledge sources which restrict their domain of application. More recent work on adaptive hypermedia has resolved some of these issues but has been criticised for the lack of support scope, focusing on learning paths and alternative content presentation. The student model used within these systems is also of limited scope and often based on learning history or learning styles.This research examines the potential of using a personality theory as the basis for a personalisation mechanism within an educational support system. The automated support system is designed to utilise a personality based profile to predict student behaviour. This prediction is then used to select the most appropriate feedback from a selection of reflective hints for students performing lab based programming activities. The rationale for the use of personality is simply that this is the concept psychologists use for identifying individual differences and similarities which are expressed in everyday behaviour. Therefore the research has investigated how these characteristics can be modelled in order to provide a fundamental understanding of the student user and thus be able to provide tailored support. As personality is used to describe individuals across many situations and behaviours, the use of such at the core of a personalisation mechanism may overcome the issues of scope experienced by previous methods.This research poses the following question: can a representation of personality be used to predict behaviour within a software system, in such a way, as to be able to personalise support?Putting forward the central claim that it is feasible to capture and represent personality within a software system for the purpose of personalising services.The research uses a mixed methods approach including a number and combination of quantitative and qualitative methods for both investigation and determining the feasibility of this approach.The main contribution of the thesis has been the development of a set of profiling models from psychological theories, which account for both individual differences and group similarities, as a means of personalising services. These are then applied to the development of a prototype system which utilises a personality based profile. The evidence from the evaluation of the developed prototype system has demonstrated an ability to predict student behaviour with limited success and personalise support.The limitations of the evaluation study and implementation difficulties suggest that the approach taken in this research is not feasible. Further research and exploration is required –particularly in the application to a subject area outside that of programming

Intelligent Agents and Their Potential for Future Design and Synthesis Environment

This document contains the proceedings of the Workshop on Intelligent Agents and Their Potential for Future Design and Synthesis Environment, held at NASA Langley Research Center, Hampton, VA, September 16-17, 1998. The workshop was jointly sponsored by the University of Virginia's Center for Advanced Computational Technology and NASA. Workshop attendees came from NASA, industry and universities. The objectives of the workshop were to assess the status of intelligent agents technology and to identify the potential of software agents for use in future design and synthesis environment. The presentations covered the current status of agent technology and several applications of intelligent software agents. Certain materials and products are identified in this publication in order to specify adequately the materials and products that were investigated in the research effort. In no case does such identification imply recommendation or endorsement of products by NASA, nor does it imply that the materials and products are the only ones or the best ones available for this purpose. In many cases equivalent materials and products are available and would probably produce equivalent results

Agent based personalized information retrieval

Thesis (M. Eng.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 1997.Includes bibliographical references (p. 69-74).by Joshua David Kramer.M.Eng

Modélisation d'un agent de recherche intelligente d'information sur internet

Motivations et le contexte de recherche -- Éléments de la problématique -- Outils et méthodes de recherche d'information -- Moteurs de recherche par index -- Modèle espace vectoriel -- Bibliothèques virtuelles -- Agents et les systèmes multi-agents -- Recherche intelligente d'information -- Modèle conceptuel d'un agent de recherche -- Étude préliminaire du modèle -- Modélisation des besoins fonctionnels de l'agent ARIII -- Choix d'implantation et mise en oeuvre

Knowledge sharing via personalized views on a composite ontology

Thesis (S.M.)--Massachusetts Institute of Technology, School of Architecture and Planning, Program in Media Arts and Sciences, 2000."February 2000."Includes bibliographical references (p. 87-91).Ontologies, or ways of categorizing and describing things, have application to organizing information for human access and allowing software agents to exchange knowledge. The traditional approaches to ontology development involve dedicated effort by a small team of knowledge engineers in a slow and expensive process. We show that a composite ontology of information resources can be constructed from the personal ontologies of individuals in an organization via an ongoing process that combines normal personal organizing activities with low-impedence computer mediation. The MindShare approach is designed to facilitate this process within an organization of people who wish both to organize internal and public information for their personal benefit, and to leverage information previously discovered by others within the organization. MindShare software provides the user with an animated graphical ontology browser for organizing Web documents according to his or her personal ontology, and also for accessing the composite ontology as extensions of the personal ontology with an assisted bimodal browsing interface. The personal ontologies are mapped to the composite ontology by a process that includes MindShare term-based information retrieval methods to suggest existing topics when a user chooses to add a topic, and a variety of user interface affordances that encourage the user to add exposed pieces of the composite ontology to their personal ontology (and later build upon those pieces). We implemented the MindShare software and conducted an initial trial with a small group of users. The MindShare approach behaved as hoped, suggesting that the approach has promise and merits further investigation.by Neil William Van Dyke.S.M

Automatic Image Annotation using Image Clustering in Multi – Agent Society

The rapid growth of the internet provides tremendous resource for information in different domains (text, image, voice, and many others). This growth introduces new challenge to hit an exact match due to huge number of document returned by search engines where millions of items can be returned for certain subject. Images have been important resources for information, and billions of images are searched to fulfill user demands, which face the mentioned challenge. Automatic image annotation is a promising methodology for image retrieval. However most current annotation models are not yet sophisticated enough to produce high quality annotations. This thesis presents online intelligent indexing for image repositories based on their contents, although content based indexing and retrieving systems have been introduced, this thesis is adding an intelligent technique to re-index images upon better understanding for its composed concepts. Collaborative Agent scheme has been developed to promote objects of an image to concepts and re-index it according to domain specifications. Also this thesis presents automatic annotation system based on the interaction between intelligent agents. Agent interaction is synonym to socialization behavior dominating Agent society. The presented system is exploiting knowledge evolution revenue due to the socialization to charge up the annotation process