CHRYSAOR: an Agent-Based Intelligent Tutoring System in Virtual Environment

11 pagesInternational audienceThe various existing Intelligent Tutoring Systems (ITS) models do not capitalize on all the possibilities permitted by the use of virtual reality. In this paper, we first establish the important characteristics of ITS (genericity, modularity, individualization, scenario edition, adaptativity). Subsequently we present our studies using an agent metamodel (Behave) based on an environment metamodel (Veha), in order to make a generic ITS. We focus on describing our agent model and its knowledge of the pedagogical situation and incorporate a pedagogical scenario model in our ITS. The use of this ITS is illustrated by an application of a virtual biomedical analyzer which enables to learn the technical procedures of the device

Systematic Review of Intelligent Tutoring Systems for Hard Skills Training in Virtual Reality Environments

Advances in immersive virtual reality (I-VR) technology have allowed for the development of I-VR learning environments (I-VRLEs) with increasing fidelity. When coupled with a sufficiently advanced computer tutor agent, such environments can facilitate asynchronous and self-regulated approaches to learning procedural skills in industrial settings. In this study, we performed a systematic review of published solutions involving the use of an intelligent tutoring system (ITS) to support hard skills training in an I-VRLE. For the seven solutions that qualified for the final analysis, we identified the learning context, the implemented system, as well as the perceptual, cognitive, and guidance features of the utilized tutoring agent. Generally, the I-VRLEs emulated realistic work environments or equipment. The solutions featured either embodied or embedded tutor agents. The agents’ perception was primarily based on either learner actions or learner progress. The agents’ guidance actions varied among the solutions, ranging from simple procedural hints to event interjections. Several agents were capable of answering certain specific questions. The cognition of the majority of agents represented variations on branched programming. A central limitation of all the solutions was that none of the reports detailed empirical studies conducted to compare the effectiveness of the developed training and tutoring solutions.Peer reviewe

A generic architecture for interactive intelligent tutoring systems

This thesis was submitted for the degree of Doctor of Philosophy and awarded by Brunel University, 07/06/2001.This research is focused on developing a generic intelligent architecture for an interactive tutoring system. A review of the literature in the areas of instructional theories, cognitive and social views of learning, intelligent tutoring systems development methodologies, and knowledge representation methods was conducted. As a result, a generic ITS development architecture (GeNisa) has been proposed, which combines the features of knowledge base systems (KBS) with object-oriented methodology. The GeNisa architecture consists of the following components: a tutorial events communication module, which encapsulates the interactive processes and other independent computations between different components; a software design toolkit; and an autonomous knowledge acquisition from a probabilistic knowledge base. A graphical application development environment includes tools to support application development, and learning environments and which use a case scenario as a basis for instruction. The generic architecture is designed to support client-side execution in a Web browser environment, and further testing will show that it can disseminate applications over the World Wide Web. Such an architecture can be adapted to different teaching styles and domains, and reusing instructional materials automatically can reduce the effort of the courseware developer (hence cost and time) in authoring new materials. GeNisa was implemented using Java scripts, and subsequently evaluated at various commercial and academic organisations. Parameters chosen for the evaluation include quality of courseware, relevancy of case scenarios, portability to other platforms, ease of use, content, user-friendliness, screen display, clarity, topic interest, and overall satisfaction with GeNisa. In general, the evaluation focused on the novel characteristics and performances of the GeNisa architecture in comparison with other ITS and the results obtained are discussed and analysed. On the basis of the experience gained during the literature research and GeNisa development and evaluation. a generic methodology for ITS development is proposed as well as the requirements for the further development of ITS tools. Finally, conclusions are drawn and areas for further research are identified

Proceedings of the 1993 Conference on Intelligent Computer-Aided Training and Virtual Environment Technology, Volume 1

These proceedings are organized in the same manner as the conference's contributed sessions, with the papers grouped by topic area. These areas are as follows: VE (virtual environment) training for Space Flight, Virtual Environment Hardware, Knowledge Aquisition for ICAT (Intelligent Computer-Aided Training) & VE, Multimedia in ICAT Systems, VE in Training & Education (1 & 2), Virtual Environment Software (1 & 2), Models in ICAT systems, ICAT Commercial Applications, ICAT Architectures & Authoring Systems, ICAT Education & Medical Applications, Assessing VE for Training, VE & Human Systems (1 & 2), ICAT Theory & Natural Language, ICAT Applications in the Military, VE Applications in Engineering, Knowledge Acquisition for ICAT, and ICAT Applications in Aerospace

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

Exploring Emerging Technologies for Requirements Elicitation Interview Training: Empirical Assessment of Robotic and Virtual Tutors

Requirements elicitation interviews are a widely adopted technique, where the interview success heavily depends on the interviewer's preparedness and communication skills. Students can enhance these skills through practice interviews. However, organizing practice interviews for many students presents scalability challenges, given the time and effort required to involve stakeholders in each session. To address this, we propose REIT, an extensible architecture for Requirements Elicitation Interview Training system based on emerging educational technologies. REIT has components to support both the interview phase, wherein students act as interviewers while the system assumes the role of an interviewee, and the feedback phase, during which the system assesses students' performance and offers contextual and behavioral feedback to enhance their interviewing skills. We demonstrate the applicability of REIT through two implementations: RoREIT with a physical robotic agent and VoREIT with a virtual voice-only agent. We empirically evaluated both instances with a group of graduate students. The participants appreciated both systems. They demonstrated higher learning gain when trained with RoREIT, but they found VoREIT more engaging and easier to use. These findings indicate that each system has distinct benefits and drawbacks, suggesting that REIT can be realized for various educational settings based on preferences and available resources.Comment: Author submitted manuscrip

Scalable Intelligence for Scheduling Systems

A personalização é um aspeto chave de uma interação homem-computador efetiva. Numa era em que existe uma abundância de informação e tantas pessoas a interagir com ela, de muitas maneiras, a capacidade de se ajustar aos seus utilizadores é crucial para qualquer sistema moderno. A criação de sistemas adaptáveis é um domínio bastante complexo que necessita de métodos muito específicos para ter sucesso. No entanto, nos dias de hoje ainda não existe um modelo ou arquitetura padrão para usar nos sistemas adaptativos modernos. A principal motivação desta tese é a proposta de uma arquitetura para modelação do utilizador que seja capaz de incorporar diferentes módulos necessários para criar um sistema com inteligência escalável com técnicas de modelação. Os módulos cooperam de forma a analisar os utilizadores e caracterizar o seu comportamento, usando essa informação para fornecer uma experiência de sistema customizada que irá aumentar não só a usabilidade do sistema mas também a produtividade e conhecimento do utilizador. A arquitetura proposta é constituída por três componentes: uma unidade de informação do utilizador, uma estrutura matemática capaz de classificar os utilizadores e a técnica a usar quando se adapta o conteúdo. A unidade de informação do utilizador é responsável por conhecer os vários tipos de indivíduos que podem usar o sistema, por capturar cada detalhe de interações relevantes entre si e os seus utilizadores e também contém a base de dados que guarda essa informação. A estrutura matemática é o classificador de utilizadores, e tem como tarefa a sua análise e classificação num de três perfis: iniciado, intermédio ou avançado. Tanto as redes de Bayes como as neuronais são utilizadas, e uma explicação de como as preparar e treinar para lidar com a informação do utilizador é apresentada. Com o perfil do utilizador definido torna-se necessária uma técnica para adaptar o conteúdo do sistema. Nesta proposta, uma abordagem de iniciativa mista é apresentada tendo como base a liberdade de tanto o utilizador como o sistema controlarem a comunicação entre si. A arquitetura proposta foi desenvolvida como parte integrante do projeto ADSyS - um sistema de escalonamento dinâmico - utilizado para resolver problemas de escalonamento sujeitos a eventos dinâmicos. Possui uma complexidade elevada mesmo para utilizadores frequentes, daí a necessidade de adaptar o seu conteúdo de forma a aumentar a sua usabilidade. Com o objetivo de avaliar as contribuições deste trabalho, um estudo computacional acerca do reconhecimento dos utilizadores foi desenvolvido, tendo por base duas sessões de avaliação de usabilidade com grupos de utilizadores distintos. Foi possível concluir acerca dos benefícios na utilização de técnicas de modelação do utilizador com a arquitetura proposta.Personalization is a key aspect of effective Human-Computer Interaction. The ability to adjust itself to its users is crucial to any modern system, in an era where there is so much information and so many people interacting in so many ways. The creation of adaptable systems is a complex domain that requires very specific methods in order to be successful. However, still today there is no standard model or architecture to use on a modern adaptive system. The main motivation of this dissertation is to propose an architecture for user modelling that is able to incorporate separate modules required to create a scalable intelligence system with user modelling techniques. The modules cooperate in order to analyse users and characterize their behaviour, using that information to provide a customized system experience that will increase not only the usability of the system but also the user’s productivity and knowledge. The proposed architecture is composed by three components: a user information unit, a mathematical structure able to classify users and the technique to use when adapting content. The user information unit is responsible for knowing the several types of individuals that can use the system, for capturing every part of relevant interaction between itself and its users and also contains the database which stores that information. The mathematical structure is the user classifier and is in charge of analysing the users and classifying them into one of three roles: beginner, intermediate or expert. Both Bayesian and Artificial Neural Networks are used, and an explanation on how to prepare and train them to deal with user information is provided. With the user role defined, a proper technique to adapt system’s content is required. In this work, a Mixed-Initiative approach is detailed which is based on allowing both the user and the system to gain control in the communication between them. The proposed architecture was developed as part of the ADSyS project. ADSyS is a Dynamic Scheduling system to solve scheduling problems subject to dynamic events. It has a high complexity even for frequent users, hence the need for the adaptation of its content to increase its usability. In order to evaluate the contribution of this work, a computational study of the user recognition was developed, as well as two usability evaluation sessions with distinct users. It was possible to conclude about the benefits of employing user modelling techniques with the proposed architecture

A Multi-Agent Architecture for An Intelligent Web-Based Educational System

An intelligent educational system must constitute an adaptive system built on multi-agent system architecture. The multi-agent architecture component provides self-organization, self-direction, and other control functionalities that are crucially important for an educational system. On the other hand, the adaptiveness of the system is necessary to provide customization, diversification, and interactional functionalities. Therefore, an educational system architecture that integrates multi-agent functionality [50] with adaptiveness can offer the learner the required independent learning experience. An educational system architecture is a complex structure with an intricate hierarchal organization where the functional components of the system undergo sophisticated and unpredictable internal interactions to perform its function. Hence, the system architecture must constitute adaptive and autonomous agents differentiated according to their functions, called multi-agent systems (MASs). The research paper proposes an adaptive hierarchal multi-agent educational system (AHMAES) [51] as an alternative to the traditional education delivery method. The document explains the various architectural characteristics of an adaptive multi-agent educational system and critically analyzes the system’s factors for software quality attributes