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- All Subjects: Data Analysis
- Creators: Chen, Yinong
- Creators: Mejía, Mauricio
For our thesis, we analyzed a set of data from the on-going longitudinal study, “Aging In the Time of COVID-19” (Guest et al., ongoing) from the Center for Innovation in Healthy and Resilient Aging at Arizona State University. This study researched how COVID-19 and the resulting physical/social distancing impacted aging individuals' health, wellbeing, and quality-of-life. The survey collected data regarding over 1400 participants’ social connections, health, and experiences during COVID-19. This study gathered information about participants’ comorbid conditions, age, sex, location, etc. We presented this work in the form of a website including the traditional elements of an Honors Thesis as well as a visual essay with the data analysis portion coded with the JavaScript library D3 and a list of resources for our target audience, older adults who are experiencing social isolation and/or loneliness.
The process of learning a new skill can be time consuming and difficult for both the teacher and the student, especially when it comes to computer modeling. With so many terms and functionalities to familiarize oneself with, this task can be overwhelming to even the most knowledgeable student. The purpose of this paper is to describe the methodology used in the creation of a new set of curricula for those attempting to learn how to use the Dynamic Traffic Simulation Package with Multi-Resolution Modeling. The current DLSim curriculum currently relates information via high-concept terms and complicated graphics. The information in this paper aims to provide a streamlined set of curricula for new users of DLSim, including lesson plans and improved infographics.