An intelligent system for teaching and learning algorithms

Abstract

A system for teaching and learning algorithms as a part of an intelligent environment, supports teacher and student activities. The system performs the following learning functions at local level: building the knowledge model of the algorithm, viewing the expert's flow-diagram, printing the flow-diagram, assessing the student's performance, and browsing the local knowledge base of algorithms. The key design problems discussed are knowledge representation, assessment of the student's performance, the system architecture and its interface with the teaching system and the use of the system by both the teacher and the student. The most important characteristics of the intelligent system for teaching and learning algorithms are namely: • • Building a knowledge model of the algorithm of the student's performance by a coefficient of proximity to that of the teacher; • • Objective assessment of the student's performance by a coefficient of proximity to that of the teacher; • • Quick, flexible and free access to every algorithm in the knowledge base by means of explicit hierarchical structures at global level and at local level; • • Teacher's control of the individual learning process, using planning techniques, time parameters and interrupt points; • • Adaptive user interface using options for functions and input/output devices, and the most preferred style for user representation; • • Accumulation of real-time experimental database of the student, subject, teacher and teaching system as a whole.