Work

Dynamic Course Generation

Year: 2015

Type: article

Abstract: This paper presents an approach and architecture for Dynamic Course Generation, based on applying AI planning techniques to a structured representation of the domain knowledge and allowing explicit representation of teaching expertise. An individual course is generated automatically for a given teaching goal and is dynamically adapted at run-time to a student's individual progress and preferences according to the teaching expertise. The separate representation of the teaching materials from the domain structure allows an easier updating and re-use of ready CAL materials. In this way our approach provides an alternative to traditional CALauthoring. An implementation in a simple engineering domain is described . An evaluation of the benefits of this approach in terms of cost-effectiveness for authoring is shown.

Source: Journal of Computing and Information Technology

Author: Julita Vassileva

Institution: Universität der Bundeswehr München

Language: English

Topic: Intelligent Tutoring Systems and Adaptive Learning

Subfield: Artificial Intelligence

Field: Computer Science

Domain: Physical Sciences

SDG: Quality education

Open Access status: gold

Estimated APC paid: $485

OpenAlex ID: W2481590669

FWCI: 0.885

Cites: 21

Cited by: 27

Related to: 10