Knowledge Representation Framework For A Web-based Intelligent Tutoring System For Engineering Courses

Tutoring is one of the most effective instruction methods. Computer as an Intelligent Tutor is an area of research since many decades. Technology advancement in Information and Communication Technology (ICT) can be used in developing Web – based Intelligent Tutoring System (WITS), which provides ind...

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Bibliographic Details
Main Author: Bhaskerray, Bhatt Chetan
Other Authors: Umanand, L
Language:en_US
Published: 2010
Subjects:
Online Access:http://hdl.handle.net/2005/901
Description
Summary:Tutoring is one of the most effective instruction methods. Computer as an Intelligent Tutor is an area of research since many decades. Technology advancement in Information and Communication Technology (ICT) can be used in developing Web – based Intelligent Tutoring System (WITS), which provides individualized tutoring at the same time to large number of students geographically distributed. Intelligent Tutoring System requires knowledge representation of expert, student and instructional strategy. While web technology promises many attractive features to build web based ITS, it would still be a challenge to represent knowledge objects that are scalable, reusable and platform independent. It is required to derive generalized knowledge representation framework which can be used in developing WITS for many courses. This research work proposes an instruction System Design (ISD) model based framework in development of WITS for Control Systems. ADDIE model is selected in development of WITS. Front end analysis is conducted to identify the learning goals of a course. Proposed research work presents a Bloom - Vincenti framework for preparing learning objectives for engineering courses. Problem Based Learning (PBL) is selected as instruction strategy. Then it presents an ontology based knowledge representation framework for expert module, tutoring module, and student module. Ontology for expert module is proposed on the course structure, instruction system, instruction material ontology, and Bloom – Vincenti Taxonomy. Ontology for student module is also proposed on course structure and Bloom – Vincenti Taxonomy. Tutoring module consists of ontology about the facts of the instruction material and rule base based on the categories of engineering knowledge (Vincenti) and cognitive skill (Bloom’s Taxonomy). Proposed way of knowledge representation supports scalability, and reusability. Prototype Web – based Intelligent Tutoring System for first level course on Control Systems is developed. JAVA technology used in development of Web – based Intelligent Tutoring System (WITS), makes WITS platform independent. Web – based Intelligent Tutoring System for Control Systems is deployed at laboratory level and its efficacy is tested for first two modules of a course.