Multiple Agent Roles in an Adaptive Virtual Classroom Environment

Proceedings BotShow, 2001

2002

Artificial Intelligence is an important area in the field of Computing applied to Education in terms of technological implementation. This paper describes IVTE, Intelligent Virtual Teaching Environment, implemented by Multi-Agents technology including pedagogical features, represented by Guilly. Guilly is a Animated Pedagogical Agent that acts based on a student model and teaching strategies. Keyword: Computer Science, Education, Learning Environment, Cognition, Games.

Digital Education …, 2010

This paper presents the evolution description and relevance of IVTE-Intelligent Virtual Teaching Environment project in terms of Artificial Intelligence and Artificial Intelligence in Education field. Furthermore, it describes the importance of Multi-agents modeling used in the IVTE software and also gives emphasis in the Cognitive Agent Model represented by an Animated Pedagogical Agent. The purpose of IVTE software is to educate children to preserve the environment. The IVTE software is implemented with Multi-agent (MAS) and Intelligent Tutoring Systems (ITS) technology, which gives more adaptable information to the teaching process. The adaptable information is promoted by Tutor of ITS or, in other words, by Animated Pedagogical Agent. The Animated Pedagogical Agent monitors, guides and individualizes the learning process using student model and teaching strategies.

Effective collaboration does not occur spontaneously. Students participating in collaborative learning environments need to learn about how to collaborate. This can be done by coaching students on which roles they should adopt in a collaborative activity. By giving advice on tasks and behaviours, students become able to adhere to specific roles and learn to collaborate effectively. This paper identifies the importance of roles in collaborative learning environments. It proposes "Acting Coach" agents as companions/advisors to support learners in adopting suitable roles. It describes a framework where students and "Acting Coach" agents can interact in a collaborative setting. Finally, it shows some of the results of a preliminary study about students and roles.

1997

Virtual reality can broaden the types of interaction between students and computer tutors. As in conventional simulation-based training, the computer can watch students practice tasks, responding to questions and offering advice. However, immersive virtual environments also allow the computer tutor to physically inhabit the virtual world with the student. Such a "pedagogical agent" can physically collaborate with the student on tasks and employ the sorts of nonverbal communication used by human tutors. This paper describes Steve, a pedagogical agent for virtual environments that helps students learn procedural tasks. Steve inhabits the virtual world with students, and he collaborates with them on tasks by gracefully shifting between demonstrating the task and providing assistance while the student performs the task. The paper also describes the subtle ways in which such a pedagogical agent can interact with students through nonverbal communication to achieve more human-like collaboration.

2005

This paper describes the design and empirical validation of three distinct pedagogical agent roles (Expert, Motivator, and Mentor) for college students within the MIMIC (Multiple Intelligent Mentors Instructing Collaboratively) agent-based research environment. The pedagogical agent roles were operationalized by image, animation, affect, voice, and dialogue and were developed in Poser 4 and implemented via Microsoft Agent. Two controlled experiments validated the instantiation of the three roles according to learner perception (N=78) and actual impact on motivation and learning (N=71). The results confirmed that the agent roles were not only perceived by the students to reflect their intended purposes but also led to significant changes in learning and motivation, as designed.

International Conference on Information Integration and Web-based Applications & Services (IIWAS), 2004

The paper presents an agent driven virtual educational environment - Platform Independent Agent- based Virtual Educational Environment (PIAVEE). The motivations and design objectives of PIAVEE, its conceptual architecture and the current implementation are presented.

2007

Personalization in virtual learning environments is the system ability to provide individualization and a set of personalized services such as personalized content management, learner model, or adaptive instant interaction. The intelligent agent technology has potential regarding the creation of such personalized, adaptive and interactive elearning applications. However, most of the available solutions have so far focused on porting existing courses with traditional teaching methods onto the virtual environments, making them available in an attractive animated interface without any fine-tuning and adaptation to the learner needs. This paper proposes a novel market-inspired collaboration model where the agents are self-interested autonomic elements collaborate to achieve a comprehensive learner model. Mentor agent makes decisions on top of a Dempster-Shafer belief accumulation to help student whenever she believes student has lost the clues and needs help. Proposed architecture is validated by applying on a sample agent augmented virtual environment designed to engage and motivate students at the lower secondary level in Singapore. Extensive experiments illustrate the effectiveness of the proposed interaction model where students have found the mentor agent as believable as a virtual teacher.

The 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.

Seventh IEEE International Conference on Advanced Learning Technologies (ICALT 2007), 2007

In this paper it is described the extension of the classical ITS structure proposed in the MAEVIF model to build reusable and adaptable VR based ITSs.