Abstract
Visual Analysis of Contact Patterns in School Environments
Highlights
Several researchers have been focusing in recent years on data modeling involving data sets that represent any kind of interaction among elements
We analyzed the interactions among students/students and students/teachers, as well as the associated metadata. None of these networks provide metadata about individual or group performances on tests and exams, we show that the analysis of both network structure and interaction dynamics allows the identification of meaningful patterns that can be used to support and optimize the teacher’s decision making, especially those related to strategic group formation and student performance analysis
This paper aims to use visual analysis techniques to study interaction evolution involving students/students and students/teachers and analyze how this information can affect decision making about teaching strategies, especially those related to strategic group formation, and school management
Summary
Several researchers have been focusing in recent years on data modeling involving data sets that represent any kind of interaction among elements. May represent a “black-box” to the user, impairing pattern comprehension Another approach involves Information Visualisation, whose strategies help in data analysis by providing interactive and graphical computational tools, including the user in the entire process of exploration and validation (Ware, 2012). The visual analysis of temporal networks may be useful to facilitate the full understanding of how the interactions involving students and teachers occur over time, as well as to allow the identification of patterns that influence the learning process. We present case studies involving two real-world education networks that represent a primary and a high school Both networks were analyzed using well established temporal network visualisation strategies.
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