User modelling and user adapted interaction in an intelligent tutoring system

Nwana, Hyacinth S.

doi:10.1007/bf00158950

Cited by 28 publications

(10 citation statements)

References 20 publications

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“…The knowledge base consists of two basic parts, namely, the composition of the knowledge system and the teaching material storehouse.. The knowledge system is a collectio n of knowledge points, including the structure and the relationship between knowledge, a knowledge system is a part of subject knowledge is decomposed into a series of knowledge points, and then gives each knowledge point of an attribute, attribute knowled ge includes knowledge point number, importance degree, master degree, prerequisite knowledge requirements the main contents of teaching materials and so on [7,8].…”

Section: Structure Of Intelligent Tutoring Systemmentioning

confidence: 99%

An Intelligent Tutoring System Based on EGL

Yan¹,

Song²

2015

Proceedings of the 2015 International Conference on Management, Education, Information and Control

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Abstract. With the development of Internet technology, intelligent tutoring system is the certain developing trend the human social digitized education. In this paper, aiming at the existing problems of intelligent tutoring system application architecture, in the analysis of the relationship between EGL and Web 2.0 technologies, an application architecture of intelligent tutoring system based on EGL and integrating Web 2.0 technology is proposed. Through the process of design and implementation of an intelligent tutoring system, the key feature of the architecture is demonstrated-developers can focus on the business issues what code handle without caring for software technical details. The architecture is simple, easy to use and across languages, frameworks and runtime platforms. In addition, it can reduce the cost during the development stage of application and effectively improve the real-time requirements and human-computer interaction experience of intelligent tutoring system. A design model for intelligent tutoring system was proposed.

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Section: Structure Of Intelligent Tutoring Systemmentioning

confidence: 99%

An Intelligent Tutoring System Based on EGL

Yan¹,

Song²

2015

Proceedings of the 2015 International Conference on Management, Education, Information and Control

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“…All of the empirical evaluation papers in the ¢rst nine years of UMUAI can be classi¢ed into four broad topic areas: ten papers in adaptive-hypermedia/information-¢ltering (Jennings and Higuchi, 1993;Kaplan et al, 1993;Boyle and Encarnacion, 1994;Vassileva, 1996;Mathe¨and Chen, 1996;Raskutti et al, 1997;Newell, 1997;Hirashima et al, 1997;Alspector et al, 1997;Balabanovic¨, 1998), nine in student modeling (Nwana, 1991;London, 1992;Carbonaro et al, 1995;Corbett and Anderson, 1995;Kashihara et al, 1995;Shute, 1995;Webb and Kuzmycz, 1996;Mitrovic et al, 1996;Milne et al, 1996;Sison et al, 1998), nine in plan recognition/mixed-initiative interaction (Calistri-Yeh, 1991;Albrecht et al, 1998;Gmytrasiewicz et al, 1998;Chiu and Webb, 1998;Chu-Carroll and Brown, 1998;Guinn, 1998;Ishizaki et al, 1999;Green and Carberry, 1999;Virvou and du Bulay, 1999), and three in user interfaces/help systems (Tattersall, 1992;Krause et al, 1993;Debevc et al, 1996).…”

Section: Um Evaluations In the Pastmentioning

confidence: 99%

Untitled

Chin

2001

User Modeling and User-Adapted Interaction

168

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Abstract. Empirical evaluations are needed to determine which users are helped or hindered by user-adapted interaction in user modeling systems. A review of past UMUAI articles reveals insuf¢cient empirical evaluations, but an encouraging upward trend. Rules of thumb for experimental design, useful tests for covariates, and common threats to experimental validity are presented. Reporting standards including effect size and power are proposed.Key words: empirical evaluation, experimental design, covariant variables, e¡ect size, treatment magnitude, power, sensitivity. What Is Empirical Evaluation?Empirical evaluation refers to the appraisal of a theory by observation in experiments. The key to good empirical evaluation is the proper design and execution of the experiments so that the particular factors to be tested can be easily separated from other confounding factors. For example, one may want to test whether a software system with a user model works better than the same system without a user model, test the effect of different levels of user modeling or different user model parameter settings, or test different user interfaces. These factors, which are under the control of the experimenter, are termed independent variables because their values can be varied independently of other variables by the experimenter. Dependent variables are variables whose values depend on the values of other variables. They include response variables or recorded measures such as the frequency/extent of certain behaviours (e.g., system usage), qualities of a behavior in a particular situation, number of errors, error rate, time to complete a task, proportion/quality of tasks achieved, interaction patterns, learning time/rate, and/or subjective evaluations (e.g., user satisfaction). Some dependent variables can only be measured indirectly such as cognitive load measured through blood pressure or pupil dilation.In an ideal experiment, only the independent variables are varied and everything else is ¢xed so that any changes in the dependent variables can be directly attributed to the variations in the independent variables. Unfortunately, such ideal control is

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“…The assumptions that are made with many of these heuristics can be regarded as prerequisites to the felicitous execution of the respective actions. For example, the correct use of an object presumes that the user knows the object; hence he can be assumed to know the object if he uses it correctly [Chin, 1989;Nwana, 1991;Sukaviriya and Foley, 1993]. A request for additional technical details about an object is likely to presume that the user is familiar with this object; hence he can be assumed to know the object if he requests technical details for it [Boyle and Encarnacion, 1994].…”

Section: Inferences Based On the User's Actionsmentioning

confidence: 99%

The user modeling shell system BGP-MS

Kobsa

Pohl

1995

User Model User-Adap Inter

109

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BGP-MS is a user modeling shell system that can assist interactive software systems in adapting to their current users by taking the users' presumed knowledge, beliefs, and goals into account. It offers applications several methods for communicating observations concerning the user to BGP-MS, and for obtaining information on currently held assumptions about the user from BGP-MS. It provides a choice of two integrated formalisms for representing beliefs and goals, and includes several types of inferences for drawing additional assumptions based on an initial interview, observed user actions, and stereotypical knowledge about pre-defined user subgroups.BGP-MS is a customizable software system that is independent from applications, operates concurrently with them, and interacts with them through inter-process communication. For tailoring BGP-MS to a specific application domain, the developer must select those components of BGP-MS that are needed in this domain and fill them with relevant domain-dependent user modeling knowledge. This paper first summarizes the user modeling services that BGP-MS provides to application programs at runtime. It discusses the representational and inferential foundations that determine the scope and the limits of these services, and also gives a detailed example illustrating the interaction between the various system components. It describes interfaces that are available to application developers for tailoring BGP-MS to the specific user modeling needs of their application domains. Finally, it compares the system with all other major user modeling shell systems, and describes a first application that employs BGP-MS for adapting hypertext to users' terminological knowledge.

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User modelling and user adapted interaction in an intelligent tutoring system

Cited by 28 publications

References 20 publications

An Intelligent Tutoring System Based on EGL

An Intelligent Tutoring System Based on EGL

Untitled

The user modeling shell system BGP-MS

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