Analyzing applicant and academic records submitted by students applying for an MS in Computer Science/Education. The analysis provides results that highlight which applicants/applicant groups are ready for next academic steps and which require additional documentation.
## Applicant Metrics and Dimensions This analysis uses two primary datasets. The applicant dataset includes applicant ID, citizenship status, program applied, application term, and first-generation status. Tha academic dataset includes applicant ID, institution name, degree status, GPA, GPA scale, credits eanred, graudation year, and GPA eligibility indicators. Applicant ID was used as a unique key to integrate the two datasets.
Equity-Focused
GPA Eligibility by Citizenship Status
Applicant Missing Information and Outreach Needs
Prioritize contacting applicants who are missing key documents to increase completion rates and readiness. Segment emails by missing item type and program for clarity.
Provide additional advising or resources to help first-gen students and answer any quesetions regarding the application process.
Offer webinars or checklist to help with the application process and to increase preparedness. Afterwards, track the effectiveness of emails or outreach interventions by finding the percentage of applicants completing missing items after outreach