Genisa: A web-based interactive learning environment for teaching simulation modelling

Intelligent Tutoring Systems (ITS) provide students with adaptive instruction and can facilitate the acquisition of problem solving skills in an interactive environment. This paper discusses the role of pedagogical strategies that have been implemented to facilitate the development of simulation modelling knowledge. The learning environment integrates case-based reasoning with interactive tools to guide tutorial remediation. The evaluation of the system shows that the model for pedagogical activities is a useful method for providing efficient simulation modelling instruction

Designing and Implementing Embodied Agents: Learning from Experience

In this paper, we provide an overview of part of our experience in designing and implementing some of the embodied agents and talking faces that we have used for our research into human computer interaction. We focus on the techniques that were used and evaluate this with respect to the purpose that the agents and faces were to serve and the costs involved in producing and maintaining the software. We discuss the function of this research and development in relation to the educational programme of our graduate students

Supporting Constructive Learning with a Feedback Planner

A promising approach to constructing more effective computer tutors is implementing tutorial strategies that extend over multiple turns. This means that computer tutors must deal with (1) failure, (2) interruptions, (3) the need to revise their tactics, and (4) basic dialogue phenomena such as acknowledgment. To deal with these issues, we need to combine ITS technology with advances from robotics and computational linguistics. We can use reactive planning techniques from robotics to allow us to modify tutorial plans, adapting them to student input. Computational linguistics will give us guidance in handling communication management as well as building a reusable architecture for tutorial dialogue systems. A modular and reusable architecture is critical given the difficulty in constructing tutorial dialogue systems and the many domains to which we would like to apply them. In this paper, we propose such an architecture and discuss how a reactive planner in the context of this architecture can implement multi-turn tutorial strategies

Learning process: Multi-Agent Tutoring System

A multi-agent architecture has been developed for tutorial assignation scheduling. It has two main types of agents: the students and the teachers. These two are coordinated by an algorithm which assigns the classes in order of arrival. The architecture will provide the necessary tools to the students, so they get the maximum profit from the tutorials. Students and Lecturers can coordinate their tutorial meeting in an efficient way with the help of the multi-agent system

Web-based medical teaching using a multi-agent system

Web-based teaching via Intelligent Tutoring Systems (ITSs) is considered as one of the most successful enterprises in artificial intelligence. Indeed, there is a long list of ITSs that have been tested on humans and have proven to facilitate learning, among which we may find the well-tested and known tutors of algebra, geometry, and computer languages. These ITSs use a variety of computational paradigms, as production systems, Bayesian networks, schema-templates, theorem proving, and explanatory reasoning. The next generation of ITSs are expected to go one step further by adopting not only more intelligent interfaces but will focus on integration. This article will describe some particularities of a tutoring system that we are developing to simulate conversational dialogue in the area of Medicine, that enables the integration of highly heterogeneous sources of information into a coherent knowledge base, either from the tutor’s point of view or the development of the discipline in itself, i.e. the system’s content is created automatically by the physicians as their daily work goes on. This will encourage students to articulate lengthier answers that exhibit deep reasoning, rather than to deliver straight tips of shallow knowledge. The goal is to take advantage of the normal functioning of the health care units to build on the fly a knowledge base of cases and data for teaching and research purposes

Cultivating intelligent tutoring cognizing agents in ill-defined domains using hybrid approaches

Cognizing agents are those systems that can perceive information from the external environment and can adapt to the changing conditions of that environment. Along the adaptation process a cognizing agent perceives information about the environment and generates reactions. An intelligent tutoring cognizing agent should deal not only with the tutoring system’s world but also with the learner-it should infer and predict new information about the learner and tailor the learning process to fit this specific learner. This paper shows how intelligent tutoring cognizing agents can be cultivated in ill-defined domains using hybrid techniques instantiated in the two example agents AEINS-CA and ALES-CA. These agents offer adaptive learning process and personalized feedback aiming to transfer certain cognitive skills, such as problem solving skills to the learners and develop their reasoning in the two ill-defined domains of ethics and argumentation. The paper focuses on the internal structure of each agent and the reasoning methodology, in which, the cognizing agent administration and construction along with the pedagogical scenarios are described

Semantic Web-based Software Product Line for Building Intelligent Tutoring Systems

Intelligent Tutoring Systems (ITS) have been assumed as an important learning resource to be added as a module in e-learning systems. However, the construction of such systems is still a hard and complex task that involves, for instance, representation and manipulation of different knowledge source. To alleviate these issues, this paper proposes a new approach for building ITS by integrating Software Product Line and Semantic Web technologies focusing on two software engineering aspects: large-scale production and customization for different learners, and how to allow these knowledge to be automatically shared between software and authors in both reuse and knowledge evolution points of view. This paper shows a modeling for the proposed product line, as well as how the Semantic Web technologies was used to achieve the effective shared knowledge

Designing Adaptive Instruction for Teams: a Meta-Analysis

The goal of this research was the development of a practical architecture for the computer-based tutoring of teams. This article examines the relationship of team behaviors as antecedents to successful team performance and learning during adaptive instruction guided by Intelligent Tutoring Systems (ITSs). Adaptive instruction is a training or educational experience tailored by artificially-intelligent, computer-based tutors with the goal of optimizing learner outcomes (e.g., knowledge and skill acquisition, performance, enhanced retention, accelerated learning, or transfer of skills from instructional environments to work environments). The core contribution of this research was the identification of behavioral markers associated with the antecedents of team performance and learning thus enabling the development and refinement of teamwork models in ITS architectures. Teamwork focuses on the coordination, cooperation, and communication among individuals to achieve a shared goal. For ITSs to optimally tailor team instruction, tutors must have key insights about both the team and the learners on that team. To aid the modeling of teams, we examined the literature to evaluate the relationship of teamwork behaviors (e.g., communication, cooperation, coordination, cognition, leadership/coaching, and conflict) with team outcomes (learning, performance, satisfaction, and viability) as part of a large-scale meta-analysis of the ITS, team training, and team performance literature. While ITSs have been used infrequently to instruct teams, the goal of this meta-analysis make team tutoring more ubiquitous by: identifying significant relationships between team behaviors and effective performance and learning outcomes; developing instructional guidelines for team tutoring based on these relationships; and applying these team tutoring guidelines to the Generalized Intelligent Framework for Tutoring (GIFT), an open source architecture for authoring, delivering, managing, and evaluating adaptive instructional tools and methods. In doing this, we have designed a domain-independent framework for the adaptive instruction of teams

Sharing Learners' Behavior to Enhance a Metacognition-oriented Intelligent Tutoring System

International audienceLiterature shows that Intelligent Tutoring Systems (ITS) are growing in acceptance and popularity because they increase performances of students, leverage cognitive development, but also significantly reduce time to acquire knowledge and competencies. Moreover, monitoring metacognitive skills enables learners to assess performance and select appropriate fix-up: individuals unable to ensure self-monitoring cannot detect errors and as a consequence, they process information less efficiently than skilled monitors. Thus, we present an ITS offering the opportunity of evaluating various metacognitive indicators and able to share this information with others learning tools. Our online tutor is based on an existing ITS authoring tool that we extended to support metacognition and share learners’ profiles and activities into a standardized, distributed and open tracking repository. This framework, validated by an experimentation, thus helps to correlate metadata experiences with real performanc

Virtual Cost Engineering Studio (V-CES): a framework for Cost Engineering services

Cost has become a business driver. V-CES is a European Project aiming to develop and deploy a set of services to the Cost Engineering Community: Training, a Cost Engineering Virtual Community, a Cost Estimating Tool, and a Cost Engineering Database. The access to such services will be done via Internet and a Web browser. This implies the possibility for the cost professionals of exercising a just-in time training, estimating and consulting related to their work. The use of these services implies interactions of the kind client-server and peer-to-peer, and their implementation demands the use of different software technologies, being the main ones: Virtual Learning Environment (VLE), database, multi-agent toolkit, and reasoning engine. This paper presents the technological definition of the framework to be used for the over all development and implementation