The Center for Inclusive Computing (CIC) is a groundbreaking initiative that aims to increase the number of women graduating with undergraduate computing degrees.
The CIC collaborates with colleges and universities through grant making, technical advising, and data collection and analysis (the Data Program). To date, the CIC is working with 57 partner schools, representing ~ 25% of computing graduates nationally.
As part of the data program, schools submit historic and current enrollment, persistence, retention, and graduation data. These data are then used to help diagnose where in the curriculum schools are losing students and to shed light on the efficacy of implemented interventions.
To evaluate the impact of their interventions, the CIC requires the ability to locate the specific areas within their partner schools curriculums where students are being lost. While currently utilizing manually entered information, the CIC has determined that this process is far to time consuming and prone to error.
To allow the CIC to continue with their important work, we were challenged with creating a dynamic data collection tool that allows partner schools to quickly and seamlessly upload their enrollment, retention, and graduation data - and which allows the CIC team to effectively analyze that data with a compatible data visualization tool.
We built a robust system that allows CIC’s partner schools to quickly and accurately submit enrollment, retention, and graduation data through a dynamic interface. To allow for seamless data analysis we additionally integrated this new interface with the CIC’s existing data visualization platform, Tableau.
To begin the data collection process, users tasked with submitting data are provided with a secure system login and once logged in are presented with a user dashboard. This dashboard clearly displays each semester requiring data, along with the semesters “status” - ie. whether or not the task has been completed. To ensure users are clearly able to determine exactly what data needs to be uploaded we utilized clear design cues, including a color coded legend.
To reduce the amount of time and potential for errors associated with the manual entry of data, we built in the ability for users to quickly upload cfv files. Once uploaded, files are run through a data validation tool that determines whether there are any errors present in the file. If an error is detected, the user is informed via an error message, allowing them to correct any issues present.
Additionally, for users at the CIC we created an admin portal that allows them to manage their partner schools and their users, enabling administrators to add or remove schools from the system and efficiently handle user accounts.
To enable efficient analysis and visualization for users at the CIC, we designed a data model that facilitates seamless integration between the data collected from partner schools and the teams existing visual analytics platform, Tableau. To ensure compatibility with Tableau for historical analysis, we additionally developed a script that imports previously saved data into the new system
To ensure that the CIC's data collection tool is easily recognizable as a product of Northeastern University, we incorporated the university's style guide. By adhering to the guidelines outlined in the style guide, we ensured that the designs of the tool accurately reflected and maintained the university's distinctive brand identity.