20,486 research outputs found

    Designing intelligent computer‐based simulations: A pragmatic approach

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    This paper examines the design of intelligent multimedia simulations. A case study is presented which uses an approach based in part on intelligent tutoring system design to integrate formative assessment into the learning of clinical decision‐making skills for nursing students. The approach advocated uses a modular design with an integrated intelligent agent within a multimedia simulation. The application was created using an object‐orientated programming language for the multimedia interface (Delphi) and a logic‐based interpreted language (Prolog) to create an expert assessment system. Domain knowledge is also encoded in a Windows help file reducing some of the complexity of the expert system. This approach offers a method for simplifying the production of an intelligent simulation system. The problems developing intelligent tutoring systems are examined and an argument is made for a practical approach to developing intelligent multimedia simulation systems

    Issues in designing learning by teaching systems

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    Abstract: Learning by teaching systems are a relatively recent approach to designing Intelligent Learning Environments that place learners in the role of tutors. These systems are based on the practice of peer tutoring where students take on defined roles of tutor and tutee. An architecture for learning by teaching systems is described that does not require the domain model of an Intelligent Tutoring System. However a mutual communication language is needed and is defined by a conceptual syntax that delimits the domain content of the dialogue. An example learning by teaching system is described for the domain of qualitative economics. The construction and testing of this system inform a discussion of the major design issues involved: the nature of the learnt model, the form of the conceptual syntax, the control of the interaction and the possible introduction of domain knowledge. 1

    Problem-Solving Knowledge Mining from Users’\ud Actions in an Intelligent Tutoring System

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    In an intelligent tutoring system (ITS), the domain expert should provide\ud relevant domain knowledge to the tutor so that it will be able to guide the\ud learner during problem solving. However, in several domains, this knowledge is\ud not predetermined and should be captured or learned from expert users as well as\ud intermediate and novice users. Our hypothesis is that, knowledge discovery (KD)\ud techniques can help to build this domain intelligence in ITS. This paper proposes\ud a framework to capture problem-solving knowledge using a promising approach\ud of data and knowledge discovery based on a combination of sequential pattern\ud mining and association rules discovery techniques. The framework has been implemented\ud and is used to discover new meta knowledge and rules in a given domain\ud which then extend domain knowledge and serve as problem space allowing\ud the intelligent tutoring system to guide learners in problem-solving situations.\ud Preliminary experiments have been conducted using the framework as an alternative\ud to a path-planning problem solver in CanadarmTutor

    Design considerations of an intelligent tutoring system for programming languages

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    The overall goal of the thesis is to attempt to highlight the major topics which must be considered in the design of any Intelligent Tutoring System and to illustrate their application within the particular domain of LISP programming. There are two major sections to the thesis. The first considers the background to the educational application of computers. It examines possible roles for the computer, explores the relationship between education theory and computer-based teaching, and identifies some important links among existing Tutoring Systems. The section concludes with a summary of the design goals which an Intelligent Tutoring System should attempt to fulfill. The second section applies the design goals to the production of an Intelligent Tutoring System for programming languages. It devises a formal semantic description for programming languages and illustrates its application to tutoring. A method for modelling the learning process is introduced. Some techniques for maintaining a structured tutoring interaction are described. The work is set within the methodology of Artificial Intelligence research. Although a fully implemented tutoring system is not described, all features discussed are implemented as short programs intended to demonstrate the feasibility of the approach taken

    Towards an Intelligent Knowledge Based Tutoring System for Foreign Language Learning

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    Intelligent Tutoring Systems have found a wide range of potential applications across a multitude of disciplines and subject areas. The Intelligent Spaniard is an Intelligent Knowledge Based Tutoring System designed to assist intermediate level students with their learning of Spanish grammar, by testing their knowledge of regular and irregular verbs. This paper describes the system\u27s architecture which takes the form of three rule-based expert systems working in synergy with each other. The Intelligent Spaniard has been developed as a domain-independent generic tutoring system, hence, its knowledge bases can be replaced with knowledge bases containing the vocabulary and grammar of other foreign languages

    Using Natural Language as Knowledge Representation in an Intelligent Tutoring System

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    Knowledge used in an intelligent tutoring system to teach students is usually acquired from authors who are experts in the domain. A problem is that they cannot directly add and update knowledge if they don’t learn formal language used in the system. Using natural language to represent knowledge can allow authors to update knowledge easily. This thesis presents a new approach to use unconstrained natural language as knowledge representation for a physics tutoring system so that non-programmers can add knowledge without learning a new knowledge representation. This approach allows domain experts to add not only problem statements, but also background knowledge such as commonsense and domain knowledge including principles in natural language. Rather than translating into a formal language, natural language representation is directly used in inference so that domain experts can understand the internal process, detect knowledge bugs, and revise the knowledgebase easily. In authoring task studies with the new system based on this approach, it was shown that the size of added knowledge was small enough for a domain expert to add, and converged to near zero as more problems were added in one mental model test. After entering the no-new-knowledge state in the test, 5 out of 13 problems (38 percent) were automatically solved by the system without adding new knowledge

    Tutorial Dialog in an Equation Solving Intelligent Tutoring System

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    This thesis makes a contribution to Intelligent Tutoring Systems (ITS) architectures. A new intelligent tutoring system is presented for the domain of solving linear equations. This system is novel, because it is the first intelligent equation-solving tutor that combines a cognitive model of the domain with a model of dialog-based tutoring. The tutorial model is novel because it is based on the observation of an experienced human tutor and captures tutorial strategies specific to the domain of equation-solving. In this context, a tutorial dialog is the equivalent of breaking down problems into simpler steps and then asking new questions to the student before proceeding to the next navigational step. The resulting system, named E-tutor, was compared, via a randomized controlled experiment, to an algebra ITS similar to the“Cognitive Tutor by Carnegie Learning, Inc¼. The Cognitive Tutor can provide traditional model-tracing feedback and buggy messages to students, but does not engage students in dialog. Preliminary results using a very small sample size, i.e., teaching equation solving to 15 high school students, showed that E-Tutor with dialog capabilities performed better than E-tutor without dialog. This result showed an effect size of 0.4 standard deviations for overall learning by condition. This set of preliminary results, though not statistically significant, shows promising opportunities to improve learning performance by adding tutorial dialog capabilities to ITSs. However, significant further validation is required, specifically, adding greater numbers and variations of the work to our sample size, before this approach can be deemed successful. The system is available at www.wpi.edu/~leenar/E-tutor

    Intelligent Tutoring in a VR Classroom

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    ITS(Intelligent Tutoring Systems) have played a significant role in today’s smart learning educational technology environment, where students are given feedback instantly at scale. However, the current, more practically inclined approaches de-emphasize the reliance on the problematic student model, i.e. student\u27s motivation, emotional state and interest instead put more effort into the construction of theory-based user interfaces. Although research in ITS has produced many interesting theoretical insights, there are relatively few ITS which are regularly and effectively used. Through research conducted into current practices in ITS, gaps within the system have been noted. Specifically, the paper attempts to propose a solution to improvise an Intelligent Tutoring System called Merits-VR that makes students in the K12 learning domain facilitate deep learning

    An intelligent tutoring system for space shuttle diagnosis

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    An Intelligent Tutoring System (ITS) transcends conventional computer-based instruction. An ITS is capable of monitoring and understanding student performance thereby providing feedback, explanation, and remediation. This is accomplished by including models of the student, the instructor, and the expert technician or operator in the domain of interest. The space shuttle fuel cell is the technical domain for the project described below. One system, Microcomputer Intelligence for Technical Training (MITT), demonstrates that ITS's can be developed and delivered, with a reasonable amount of effort and in a short period of time, on a microcomputer. The MITT system capitalizes on the diagnostic training approach called Framework for Aiding the Understanding of Logical Troubleshooting (FAULT) (Johnson, 1987). The system's embedded procedural expert was developed with NASA's C-Language Integrated Production (CLIP) expert system shell (Cubert, 1987)
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