EduClust -A Visualization Application for Teaching Clustering Algorithms

Johannes Fuchs (1) , Petra Isenberg (2) , Anastasia Bezerianos (3, 4, 5) , Matthias Miller (1) , Daniel Keim (1)

1 University of Konstanz
2 AVIZ - Analysis and Visualization
3 ILDA - Interacting with Large Data
4 LRI - Laboratoire de Recherche en Informatique
5 UP11 UFR Sciences - Université Paris-Sud - Paris 11 - Faculté des Sciences

We present EduClust, a visualization application for teaching clustering algorithms. EduClust is an online application that combines visualizations, interactions, and animations to facilitate the understanding and teaching of clustering steps, parameters, and procedures. Traditional classroom settings aim for cognitive processes like remembering and understanding. We designed EduClust for expanded educational objectives like applying and evaluating. Educators can use the tool in class to show the effect of different clustering parameters on various datasets while animating through each algorithm's steps, but also use the tool to prepare traditional teaching material quickly by exporting animations and images. Students, on the other hand, benefit from the ability to compare and contrast the influence of clustering parameters on different datasets, while seeing technical details such as pseudocode and step-by-step explanations.

Keywords: Interactive learning environments; Unsupervised learning and clustering; Information Visualization

Domains: Human-Computer Interaction [cs.HC]

Johannes Fuchs, Petra Isenberg, Anastasia Bezerianos, Matthias Miller, Daniel Keim. EduClust -A Visualization Application for Teaching Clustering Algorithms. Eurographics 2019 - 40th Annual Conference of the European Association for Computer Graphics, May 2019, Genova, Italy. pp.1-8. ⟨hal-02103293⟩