Title: Descriptive Analysis of Grade Outcomes Report Team Name: The Null Wranglers Team Authors :
Final project repo for INFO 523 - Fall 2023. Repo Organization
The following are the folders involved in the Project repository.
data/ - Used for storing any necessary data files for the project, such as input files.
images/ - Used for storing image files used in the project.
extra/ - Used to brainstorm our analysis which won't impact our project workflow.
freeze/ - This folder is used to store the generated files during the build process. These files represent the frozen state of the website at a specific point in time.
github/ - Folder for storing github templates and workflow.
.git - hidden directory at the root of the repository that contains the internal data structure and configuration files
about.qmd - contains information about Project title and team members.
presentation.qmd - contains the presentation for final project
proposal.qmd - contains the proposal for the final project
index.qmd - Contains the abstract for the project.
Time_Series_Analaysis.qmd - Contains the Time series analysis for the project
EDA_Grade_Outcomes.qmd - Contains the Exploratory Data Analysis code chunks and plots
Decision_Tree.qmd - Contains Decision Tree Analysis execution
Regression.qmd - Contains regression analysis and regularization using lasso and ridge models
There is a lack of understanding of how higher education has been impacted by the Corona virus global pandemic. This study aims to explore grade outcomes for students at a level one research institution before, during, and after this public health emergency. An exploratory data analysis will examine and compare grade values outcomes by college, department, and division level. Anomaly detection indicated that the College of Social and Behavioral Sciences observed the greatest number of high DEW percentage courses. A time series analysis indicated that the lowest DEW percentages were observed during the first semester of the pandemic followed by the highest levels of DEW percentage courses in the next semester. A decision tree analysis found that fully online courses are a key factor in determining whether a course will be above average for the DEW percent. A regression analysis found a correlation between the DEW percent and fully online classes as well as classes offered in the second half session of a semester. An accurate predictive model was unable to be constructed during the course of this study. However, future research that extends the time frame of the data and includes more fine-grained data could yield further insights regarding relationships between grade value outcomes and course attributes.
Derived from the original data viz course by Mine Çetinkaya-Rundel @ Duke University