Information Visualization for Highlighting Conflicts in Educational Timetabling Problems


Scheduling is a very important problem in many organizations, such as hospitals, transportation companies, sports confederations and educational institutions. Obtaining a good schedule results in the maximization of some desired benefit. In particular, in educational institutions (from elementary school to universities) this problem is periodically experienced, either during the preparation of class-teacher or examination timetabling. When a solution proposal is being elaborated (manual, semi-automatic or automatic processes), it is common the occurrence of the phenomenon called conflict, clash or collision. It is characterized by the simultaneous use of a resource (human or material) that can not be shared and, therefore, its occurrence makes that proposal impracticable for adoption. In semi-automatic systems, it is common the identification of such problems and, through user interaction, its resolution. Automatic systems, on the other hand, try to identify/solve conflicts without user intervention. Despite this, conflicts are not easy to resolve. This article proposes the use of information visualization techniques as an approach to highlight the occurrence of conflicts and, using user hints, contribute to its resolution, aiming at obtaining better quality timetables for practical adoption. The proposed visualizations were evaluated in order to determine its expressiveness and effectiveness, considering four aspects: coverage of the research questions, efficiency of the adopted visual mapping, supported level of human interaction and scalability. A conceptual qualitative study showed that the use of these techniques can aim users, mainly non-specialized, to identify conflicts and improve the desired educational timetables.

14th International Symposium on Visual Computing (ISVC 2019)
Fabrizzio Soares
Fabrizzio Soares
Associate Professor and CS Chair

Fabrizzio Soares is a professor of Computer Science, Information Systems and Software Engineering at INF/UFG. His research interests include Computer Vision, Human Computer Interaction, Machine Learning and Programming topics. He is the leader of the Pixellab group, which develops solutions for accesibilty, Precision Agriculture, and Interactive Systems.