Analyzing and Predicting Students Flow Visualization - NS, Hima Bindu; R, Swathi; K, Sreedivya (International Journal of Computer Sciences and Engineering, 2019)
In this work, I have a tendency to gift information science system to model and visualize student flow patterns supported electronic student data of a university. The datasets utilized by eCamp were antecedently disconnected and solely maintained and accessed in a much siloed manner by freelance field offices. At a campus-level, our models and image show however students create selections among many potential majors, as students step by step progress towards their sophomore, junior, and senior year. At a department-level, the scholar flow patterns unconcealed by eCamp show however every course plays a special role inside a syllabus. ECamp more dives all the way down to the roughness of the precise categories offered in every semester. At that level, eCamp shows however students navigate from one set of categories in one semester to a different set in a very enchant semester. I’d wish to build a deeper set of analytics mistreatment a lot of discourse info with further information sources like pedagogue info of every category, student help info, and student admission info. Previously, comprehensive info regarding student progression patterns in the slightest degree of those levels was merely unavailable. to it finish, we have a tendency to additionally demonstrate however insights into such student flow patterns will support analytical tasks involving student outcomes, student retention, and syllabus style.