A Web Based Intelligent Tutoring System
This paper describes an Intelligent Tutoring System that provides adaptable facilities to students over the World Wide Web. The system is able to adapt to a large corpus of students, in terms of allowing commonly used paths to emerge, and adapts to individual students by employing a novel student model.
The lack of intelligent tutoring systems outside of academic research has largely been attributed to the fact that they are domain specific. Whilst very powerful for the tutoring of a specific subject, the inability of a knowledge-based approach to artificial intelligence to generalise that has rendered it less useful for generic systems. Neural networks, or connectionist models, are the antithesis of knowledge-based approaches in that they are extremely adept at generalising which gives them the ability to work with very noisy data.
The research project described in the paper employs both knowledge-based representations and neural networks to model students using non-domain specific parameters, such as browse strategies and ability to answer questions. The domain is structured in a hypermedia network using semantic linking that enables the system to automatically produce and weight new links. The weighting system is tailored according to a student 's requirements and the student 's ability level and is continuously updated.
This novel paraigm is of great potential in a tele-education environment, since the system s generic and is therefore useful to a multitude of authors/domains and the system is able t adapt to a large number of students, such as may be found on the World Wide Web.
Keywords: Hypermedia, neural networks, domain independence, browsing strategy, student modelling
1 Faculty of Information and Engineering Systems, Leeds Metropolitan University, Beckett Park, Headingley, LS6 3QS, Tel 0113 832600, Fax 0113 833182, email d.mullier@lmu.ac.uk INTRODUCTION
Hypermedia systems when used for learning generally offer no constraint on the user. Indeed
The lack of intelligent tutoring systems outside of academic research has largely been attributed to the fact that they are domain specific. Whilst very powerful for the tutoring of a specific subject, the inability of a knowledge-based approach to artificial intelligence to generalise that has rendered it less useful for generic systems. Neural networks, or connectionist models, are the antithesis of knowledge-based approaches in that they are extremely adept at generalising which gives them the ability to work with very noisy data.
The research project described in the paper employs both knowledge-based representations and neural networks to model students using non-domain specific parameters, such as browse strategies and ability to answer questions. The domain is structured in a hypermedia network using semantic linking that enables the system to automatically produce and weight new links. The weighting system is tailored according to a student 's requirements and the student 's ability level and is continuously updated.
This novel paraigm is of great potential in a tele-education environment, since the system s generic and is therefore useful to a multitude of authors/domains and the system is able t adapt to a large number of students, such as may be found on the World Wide Web.
Keywords: Hypermedia, neural networks, domain independence, browsing strategy, student modelling
1 Faculty of Information and Engineering Systems, Leeds Metropolitan University, Beckett Park, Headingley, LS6 3QS, Tel 0113 832600, Fax 0113 833182, email d.mullier@lmu.ac.uk INTRODUCTION
Hypermedia systems when used for learning generally offer no constraint on the user. Indeed
Links: are offered to the student in ordered groups, for example a group of links representing the local semantic structure and a group of links representing the weighted, automatically generated links. The lists of links may be formatted by a Java script and presented on a World Wide Web page. Selection of a link results in the server presenting the relevant information or graphic on the web page. The system is then able to record the links that each student visits and is able to slightly modify the link weight, so as to make the selection of the link more likely for the next student. In this fashion useful paths tend to emerge. The presentation of the links is therefore controlled by the server, upon which the student model resides. It is possible for the student model to store unique information about each student by providing a free registration and log in service. The utilisation of the World Wide Web is therefore useful for the research project in terms of it providing the requisite number of students to evaluate the intelligent facilities. It is also a paramount concern of the project that the system is itself useable over the Internet, since this imbues the system with the greatest potential as a mass educational aid.