Matching Items (2)
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Description
Visualizations are an integral component for communicating and evaluating modern networks. As data becomes more complex, info-graphics require a balance between visual noise and effective storytelling that is often restricted by layouts unsuitable for scalability. The challenge then rests upon researchers to effectively structure their information in a way that

Visualizations are an integral component for communicating and evaluating modern networks. As data becomes more complex, info-graphics require a balance between visual noise and effective storytelling that is often restricted by layouts unsuitable for scalability. The challenge then rests upon researchers to effectively structure their information in a way that allows for flexible, transparent illustration. We propose network graphing as an operative alternative for demonstrating community behavior over traditional charts which are unable to look past numeric data. In this paper, we explore methods for manipulating, processing, cleaning, and aggregating data in Python; a programming language tailored for handling structured data, which can then be formatted for analysis and modeling of social network tendencies in Gephi. We implement this data by applying an algorithm known as the Fruchterman-Reingold force-directed layout to datasets of Arizona State University’s research and collaboration network. The result is a visualization that analyzes the university’s infrastructure by providing insight about community behaviors between colleges. Furthermore, we highlight how the flexibility of this visualization provides a foundation for specific use cases by demonstrating centrality measures to find important liaisons that connect distant communities.
ContributorsMcMichael, Jacob Andrew (Author) / LiKamWa, Robert (Thesis director) / Anderson, Derrick (Committee member) / Goshert, Maxwell (Committee member) / Arts, Media and Engineering Sch T (Contributor) / Barrett, The Honors College (Contributor)
Created2020-05
Description
The Tutoring Center Management System is a web-based application for ASU’s University Academic Success Programs (UASP) department, particularly the Math Tutoring Center. It is aimed at providing a user-friendly interface to track queue requests from students visiting the tutoring centers and convert that information into actionable data with the potential

The Tutoring Center Management System is a web-based application for ASU’s University Academic Success Programs (UASP) department, particularly the Math Tutoring Center. It is aimed at providing a user-friendly interface to track queue requests from students visiting the tutoring centers and convert that information into actionable data with the potential to live-track and assess the performance of each tutoring center and each tutor. Numerous UASP processes are streamlined to create an efficient and integrated workflow, such as tutor scheduling, tutor search, shift coverage requests, and analytics. The intended users of the application feature ASU students and the UASP staff, including tutors and supervisors.
ContributorsJain, Prakshal (Co-author) / Gulati, Sachit (Co-author) / Nakamura, Mutsumi (Thesis director) / Selgrad, Justin (Committee member) / Department of Information Systems (Contributor) / Computer Science and Engineering Program (Contributor, Contributor) / Barrett, The Honors College (Contributor)
Created2019-12