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This project tackles a real-world example of a classroom with college students to discover what factors affect a student’s outcome in the class as well as investigate when and why a student who started well in the semester may end poorly later on. First, this project performs a statistical analysis to ensure that the total score of a student is truly based on the factors given in the dataset instead of due to random chance. Next, factors that are the most significant in affecting the outcome of scores in zyBook assignments are discovered. Thirdly, visualization of how students perform over time is displayed for the student body as a whole and students who started well at the beginning of the semester but trailed off towards the end. Lastly, the project also gives insight into the failure metrics for good starter students who unfortunately did not perform as well later in the course.
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.
Chandler Unified School District (CUSD), a large school system in Arizona that serves 45,000 students from preschool through high school, has been unable to escape similar structural and frictional inequities within its schools. One instance of a racially charged student performance at Santan Middle School motivated CUSD to take a more immediate look at equity in the district. It is during this response that our team of New Venture Group consultants engaged with Matt Strom, Assistant Superintendent of CUSD, in analyzing the important question of “how CUSD can take steps towards closing equity gaps within the district?”
CUSD defines an equity gap as any difference in student opportunity, achievement, discipline, attendance, etc. contributable to a student’s ethnicity, gender, or socioeconomic status. Currently, certain student populations in CUSD perform vastly different academically and receive different opportunities within schools, but as was our problem statement, CUSD is aiming to reduce (and eventually close) these gaps.
Our team approached this problem in three phases: (1) diagnosis, (2) solution creation, and (3) prevention. In phase one, we created a dashboard to help principals easily and visually identify gaps by toggling parameters on the dashboard. Phase two focused on the generation of recommendations for closing gaps. To achieve this goal, a knowledge of successful gap-closing strategies will be paired with the dashboard. In our final phase, the team of consultants created a principal scorecard to ensure equity remains a priority for principals.
Visualizations can be an incredibly powerful tool for communicating data. Data visualizations can summarize large data sets into one view, allow for easy comparisons between variables, and show trends or relationships in data that cannot be seen by looking at the raw data. Empirical information and by extension data visualizations are often seen as objective and honest. Unfortunately, data visualizations are susceptible to errors that may make them misleading. When visualizations are made for public audiences that do not have the statistical training or subject matter expertise to identify misleading or misrepresented data, these errors can have very negative effects. There is a good deal of research on how best to create guidelines for creating or systems for evaluating data visualizations. Many of the existing guidelines have contradicting approaches to designing visuals or they stress that best practices depend on the context. The goal of this work is to define the guidelines for making visualizations in the context of a public audience and show how context-specific guidelines can be used to effectively evaluate and critique visualizations. The guidelines created here are a starting point to show that there is a need for best practices that are specific to public media. Data visualization for the public lies at the intersection of statistics, graphic design, journalism, cognitive science, and rhetoric. Because of this, future conversations to create guidelines should include representatives of all these fields.