Adaptive Learning Systems in the World Wide Web

Abstract

With the steadily growing demand for further education, the World Wide Web is becoming a more and more popular vehicle for delivering on-line learning courses. A challenging research goal is the development of advanced Web-based learning applications that can offer some amount of interactivity and adaptivity in order to support learners who their start learning with different background knowledge and skills. In existing on-line learning systems, some types of adaptivity and adaptability require different types of user models. This paper briefly introduces ELM-ART, an example of a substantial adaptive learning system on the WWW. It uses several adaptive techniques and offers some degree of adaptability. The adaptive techniques are based on two different types of user models: a multi-layered overlay model that allows for sophisticated link annotation and individual curriculum sequencing; and an episodic learner model that enables the system to analyze and diagnose problem solutions and to offer individualized examples to programming problems. The last section gives an overview of empirical results with adaptive learning systems and discusses the problems concerned with the evaluation of complex learning systems in real-world learning situations.