OFMTutor: An operator function model intelligent tutoring system

The design, implementation, and evaluation of an Operator Function Model intelligent tutoring system (OFMTutor) is presented. OFMTutor is intended to provide intelligent tutoring in the context of complex dynamic systems for which an operator function model (OFM) can be constructed. The human operator's role in such complex, dynamic, and highly automated systems is that of a supervisory controller whose primary responsibilities are routine monitoring and fine-tuning of system parameters and occasional compensation for system abnormalities. The automated systems must support the human operator. One potentially useful form of support is the use of intelligent tutoring systems to teach the operator about the system and how to function within that system. Previous research on intelligent tutoring systems (ITS) is considered. The proposed design for OFMTutor is presented, and an experimental evaluation is described

The effect of multiple knowledge sources on learning and teaching

Current paradigms for machine-based learning and teaching tend to perform their task in isolation from a rich context of existing knowledge. In contrast, the research project presented here takes the view that bringing multiple sources of knowledge to bear is of central importance to learning in complex domains. As a consequence teaching must both take advantage of and beware of interactions between new and existing knowledge. The central process which connects learning to its context is reasoning by analogy, a primary concern of this research. In teaching, the connection is provided by the explicit use of a learning model to reason about the choice of teaching actions. In this learning paradigm, new concepts are incrementally refined and integrated into a body of expertise, rather than being evaluated against a static notion of correctness. The domain chosen for this experimentation is that of learning to solve "algebra story problems." A model of acquiring problem solving skills in this domain is described, including: representational structures for background knowledge, a problem solving architecture, learning mechanisms, and the role of analogies in applying existing problem solving abilities to novel problems. Examples of learning are given for representative instances of algebra story problems. After relating our views to the psychological literature, we outline the design of a teaching system. Finally, we insist on the interdependence of learning and teaching and on the synergistic effects of conducting both research efforts in parallel

An intelligent simulation training system

The Department of Industrial Engineering at the University of Central Florida, Embry-Riddle Aeronautical University and General Electric (SCSD) have been funded by the State of Florida to build an Intelligent Simulation Training System. The objective was and is to make the system generic except for the domain expertise. Researchers accomplished this objective in their prototype. The system is modularized and therefore it is easy to make any corrections, expansions or adaptations. The funding by the state of Florida has exceeded $3 million over the past three years and through the 1990 fiscal year. UCF has expended in excess of 15 work years on the project. The project effort has been broken into three major tasks. General Electric provides the simulation. Embry-Riddle Aeronautical University provides the domain expertise. The University of Central Florida has constructed the generic part of the system which is comprised of several modules that perform the tutoring, evaluation, communication, status, etc. The generic parts of the Intelligent Simulation Training Systems (ISTS) are described

Man-machine interface analysis of the flight design system

The objective of the current effort was to perform a broad analysis of the human factors issues involved in the design of the Flight Design System (FDS). The analysis was intended to include characteristics of the system itself, such as: (1) basic structure and functional capabilities of FDS; (2) user backgrounds, capabilities, and possible modes of use; (3) FDS interactive dialogue, problem solving aids; (4) system data management capabilities; and to include, as well, such system related matters as: (1) flight design team structure; (2) roles of technicians; (3) user training; and (4) methods of evaluating system performance. Wherever possible, specific recommendations are made. In other cases, the issues which seem most important are identified. In some cases, additional analyses or experiments which might provide resolution are suggested

Knowledge Based Systems: A Critical Survey of Major Concepts, Issues, and Techniques

This Working Paper Series entry presents a detailed survey of knowledge based systems. After being in a relatively dormant state for many years, only recently is Artificial Intelligence (AI) - that branch of computer science that attempts to have machines emulate intelligent behavior - accomplishing practical results. Most of these results can be attributed to the design and use of Knowledge-Based Systems, KBSs (or ecpert systems) - problem solving computer programs that can reach a level of performance comparable to that of a human expert in some specialized problem domain. These systems can act as a consultant for various requirements like medical diagnosis, military threat analysis, project risk assessment, etc. These systems possess knowledge to enable them to make intelligent desisions. They are, however, not meant to replace the human specialists in any particular domain. A critical survey of recent work in interactive KBSs is reported. A case study (MYCIN) of a KBS, a list of existing KBSs, and an introduction to the Japanese Fifth Generation Computer Project are provided as appendices. Finally, an extensive set of KBS-related references is provided at the end of the report

Freeform User Interfaces for Graphical Computing

報告番号: 甲15222 ; 学位授与年月日: 2000-03-29 ; 学位の種別: 課程博士 ; 学位の種類: 博士(工学) ; 学位記番号: 博工第4717号 ; 研究科・専攻: 工学系研究科情報工学専

EXPERT ASSESSMENT MODULE (EAM) FOR INTELLIGENT TUTORING SYSTEM (ITS)

This paper, entitled Expert Assessment Module (EAM) for Intelligence Tutoring System (ITS), looks into theway of implementing Artificial Intelligence (AI) components into an online learning system that could help tertiary students to master the subject of Structure Programming in C. The main objective ofthis project isto develop aprototype of EAM that is capable of assessing, diagnosing and categorizing students into three main level of expertise based ontheir performance, so that learning experience can be much more effective. Currently, most of the existing online learning systems are only capable to cater one-way-communication direction in which the lecturer of a particular subject will upload all the relevant study materials at one end and students will download and learn them firom the other end. Unfortunately, slow learners might find difficulty to understand complicated topics without any explanation or guidance from the lecturers. Nevertheless, the lecturer has less or no supervision of his students' performances and perhaps the tests conducted tend to be set according to the lecturer's own standard. Therefore, the scope of study for this project will covers the understanding ofcurrent online learning system and the field of Artificial Intelligence, the best pedagogical approach to design the course contents for learning modules based on the student's performance, prototype development of EAM and integration of the system as a whole. The EAM is expected to solve this problem by assessing the student's capability, providing guidance and tips, grading students, and deterrnining the best ways of presenting the lecture materials according to the student's level of expertise. The Waterfall Model is used to assist and monitor all activities through out the project's lifetime. The methodology consists of five phases including the requirement definition phase, system and software design phase, development and unit testing phase, implementation and system testing phase and project closing and submission phase. This project is seen to be capable of improving the capability of current online learning system andthe output obtained is expected to assist both students and lecturers in learning and teaching the subject ofCPrograrnming more conveniently and effectively.

Negotiated Tutoring: An Approach to Interaction in Intelligent Tutoring Systems

This thesis describes a general approach to tutorial interaction in Intelligent Tutoring Systems, called "Negotiated Tutoring". Some aspects of the approach have been implemented as a computer program in the 'KANT' (Kritical Argument Negotiated Tutoring) system. Negotiated Tutoring synthesises some recent trends in Intelligent Tutoring Systems research, including interaction symmetry, use of explicit negotiation in dialogue, multiple interaction styles, and an emphasis on cognitive and metacognitive skill acquisition in domains characterised by justified belief. This combination of features has not been previously incorporated into models for intelligent tutoring dialogues. Our approach depends on modelling the high-level decision-making processes and memory representations used by a participant in dialogue. Dialogue generation is controlled by reasoning mechanisms which operate on a 'dialogue state', consisting of conversants' beliefs, a set of possible dialogue moves, and a restricted representation of the recent utterances generated by both conversants. The representation for conversants' beliefs is based on Anderson's (1983) model for semantic memory, and includes a model for dialogue focus based on spreading activation. Decisions in dialogue are based on preconditions with respect to the dialogue state, higher level educational preferences which choose between relevant alternative dialogue moves, and negotiation mechanisms designed to ensure cooperativity. The domain model for KANT was based on a cognitive model for perception of musical structures in tonal melodies, which extends the theory of Lerdahl and Jackendoff (1983). Our model ('GRAF' - GRouping Analysis with Frames) addresses a number of problems with Lerdahl and Jackendoff's theory, notably in describing how a number of unconscious processes in music cognition interact, including elements of top-down and bottom-up processing. GRAF includes a parser for musical chord functions, a mechanism for performing musical reductions, low-level feature detectors and a frame-system (Minsky 1977) for musical phrase structures