Teaching Clustering Algorithms With EduClust: Experience Report and Future Directions

Johannes Fuchs; Petra Isenberg; Anastasia Bezerianos; Matthias Miller; Daniel A Keim; Beatriz Sousa Santos; Ginger Alford

doi:10.1109/MCG.2020.2970560

Teaching Clustering Algorithms With EduClust: Experience Report and Future Directions

IEEE Comput Graph Appl. 2020 Mar-Apr;40(2):98-102. doi: 10.1109/MCG.2020.2970560.

Authors

Johannes Fuchs, Petra Isenberg, Anastasia Bezerianos, Matthias Miller, Daniel A Keim, Beatriz Sousa Santos, Ginger Alford

PMID: 32149615
DOI: 10.1109/MCG.2020.2970560

Abstract

We share our experiences teaching university students about clustering algorithms using EduClust, an online visualization we developed. EduClust supports professors in preparing teaching material and students in visually and interactively exploring cluster steps and the effects of changing clustering parameters. We used EduClust for two years in our computer science lectures on clustering algorithms and share our experience integrating the online application in a data science curriculum. We also point to opportunities for future development.