Automatic generation of learning path for teaching informatics at university

TL;DR

This paper introduces a new algorithm that creates personalized learning paths for university informatics students using concept maps.

Contribution

The LPG algorithm generates customized learning paths by analyzing concept maps, enabling adaptive learning in computer science education.

Findings

The LPG algorithm distinguishes student groups based on performance and generates tailored learning paths.

Topological sorting is used to simplify learning paths for adaptive learning systems.

The approach can be applied across various subject areas beyond computer science.

Abstract

The article discusses the problem concept maps are crucial tools for visualizing informatics knowledge in adaptive learning systems. In computer science education, concept maps are essential for visualizing complex knowledge structures and supporting adaptive learning. This study presents a learning path generation (LPG) algorithm designed to improve personalized learning in computer science. By analyzing students’ concept maps, the LPG algorithm effectively distinguishes between groups of students based on their performance and generates customized learning paths.

The LPG algorithm uses advanced computational methods to analyze concept maps and learning paths. Then, simplified learning paths are generated using a topological sorting algorithm. By using this method in computer science education, the following objectives can be achieved:

Effectively distinguish between groups of students and generate customized learning paths based on their performance.

Knowledge acquisition and increased student engagement.

Learning path generation can be applied to any subject area.

Image, graphical abstract

Figures