...
The model for providing ongoing enrollment analytics data/insights should be:
flexible
robust
comprehensive
inclusive
Needs to accommodate all kinds of schools and programs, most especially “non-traditional cycle” graduate programs
multiple annual entry terms
spring or summer start dates
alternate application stages like interviewing/traffic rules
small application populations
Needs to accommodate variety of dataset sizes; not all programs will have statistically significant numbers or numbers that make sense
Points of ambiguity:
What counts as a “cycle”?
Application changes within cycle (MPH change concentration or start term from spring to fall)
Clearly define when admissions stops being the “system of record” (i.e., dropping during add/drop, etc.)
SIS quick admit
SIS history of admit decline? Program Action codes?
What counts as a complete application?
Deferrals
Withdrawals
Deny vs. Do Not Interview
our policies vs. external reporting organization requirements/policies (i.e., what APTA considers complete vs. what we consider complete.
Race/Ethnicity – different prompts in different systems, how do classify consistently (East Asian vs. West Asian, Hispanic Spanish, etc.)
...