Advanced Training System
for Emergency Management


The main objective of the A-TEAM project is to improve advanced technical training with a new approach using an integration of artificial intelligence (AI) technologies and dynamic simulation modeling to create fully interactive multi-media content within a real-time knowledge-based system framework for the domain of emergency management applications. The underlying client-server architecture supports easy access in Intranet/Internet distributed systems so that the approach can be used in support of more traditional supervised classroom teaching, structured distance learning, and learning-on-demand.

The basic approach is to extend an operational emergency management system, major components of which have been developed in an ESPRIT HPCN project under framework 4 (HITERM 22723), into a training system by including didactic components into the same basic logical framework of the interactive decision support tool. The main innovative features of the proposed approach to advanced technical training include:

  • A realistic and immersive real-world experience provides a more effective learning environment: through the use of a simulation based real-time emergency management decision support system as the training framework: the system is the lecture, test, and tutor at the same time.

  • Learning-by-doing under machine supervision: an embedded didactic model with immediate feedback, error correction, and replay and post-mortem analysis capabilities combined with classical explanatory material and background information with multiple-choice tests.

  • Real-time monitoring of learner performance: any individual response can be used to modify the presentation of content, add explanatory and in-depth material, start test sequences whenever appropriate, and in general design and configure a training environment that includes many of the essential features of an intelligent tutor in a student-tutor dialogue.

  • The integration of Artificial Intelligence methodology (knowledge based systems, expert system, case-based reasoning, intelligent agents) and interactive simulation modeling with specific didactic material. The use of AI components supports advanced navigational features but also student monitoring and immediate feedback that go far beyond the classical sequence of lecture units and subsequent tests.

  • Complex navigation: the linkage of problem representation and description at various levels of aggregation and explanatory power, enabling the student to navigate from simple empirical black-box components for fast and efficient situation control to fully analytical step-by-step explanatory features with additional hyperlinked background material;

  • Real-time multimedia: the integration of classical computer based distance-learning approaches (multimedia presentations with embedded tests) into a real-time management scenario that requires decisions under stress in an action oriented real- time virtual reality-training scenario.

The approach proposed for A-TEAM adds a new dimension of artificial intelligence to computer based training systems. This moves the technology from a simple computer implementation of textbooks and video taped lectures to a completely new level of interaction, dynamic response, continuous evaluation, and a highly adaptive course delivery. Building an intelligent tutor into the system that follows every step of the training process promises a new efficiency in the delivery of technical training in complex domains.

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