Suitability Analysis of Graph Visualization Algorithms for Personalized Study Planning

2016 20th International Conference on System Theory, Control and Computing (ICSTCC 2016): Proceedings 2016
Raita Rollande, Jānis Grundspeņķis, Antons Mislēvičs

In previous papers the present authors have covered personalized study planning framework, and also have implemented study planning system (SPS) prototype, which allows to create a personalized study program, and then to plan the course learning, setting the courses in the required sequence, and make structure analysis thus detecting the most significant nodes in the graph structure. In this paper authors describe the application of eight common graph visualization algorithms - Tree, Circular, EfficientSugiyama Fruchterman-Reingold - FR, BoundedFR, ISOM, Kamada - Kawai - KK; LinLog - for representing study plans and course structures in the personalized study planning system.

Keywords
LinLog, personalized education, graphs, graph visualizing algorithms, Tree, Circular, EfficientSugiyama Fruchterman-Reingold — FR, BoundedFR, ISOM, Kamada — Kawai — KK
DOI
10.1109/ICSTCC.2016.7790705
Hyperlink
http://ieeexplore.ieee.org/document/7790705/

Rollande, R., Grundspeņķis, J., Mislēvičs, A. Suitability Analysis of Graph Visualization Algorithms for Personalized Study Planning. In: 2016 20th International Conference on System Theory, Control and Computing (ICSTCC 2016): Proceedings, Romania, Sinaia, 13-15 October, 2016. Piscataway: IEEE, 2016, pp.441-448. ISBN 978-1-5090-2721-7. e-ISBN 978-1-5090-2720-0. Available from: doi:10.1109/ICSTCC.2016.7790705

Publication language
English (en)