The description section of the Case study article provides a good initial outline of how to plan your analysis using MIDFIELD student records. Under each heading, we’ll pose some prompts to help you assemble the resources you’ll need.
Data.
- What programs are to be included?
- Do you know their CIP codes?
- If you don’t plan to use the
cipdataset in midfieldr, do you have another source available? Do you know how it is structured? - Are you planning to use the MIDFIELD research database? Have you requested access from ASEE?
- If not, do you have an alternative set of student-level data? To use midfieldr, your data must be modeled on the MIDFIELD database.
Metric. Program stickiness: the ratio \small (S) of the number of graduates of a program \small (N_\textrm{grad}) to the number ever enrolled in the program \small (N_\textrm{ever}), including part-time students, migrators, transfers, and students admitted in any term (Ohland et al. 2012).
\small S = \frac{\small N_\textrm{grad}}{\small N_\textrm{ever}} = \frac{\small\mathrm{number\ of\ graduates\ of\ a\ program}}{\small\mathrm{number\ ever\ enrolled\ in\ the\ program}}
Programs. Civil, Electrical, Industrial/Systems, and Mechanical Engineering.
Records. Exclude records later than a student’s first degree term; filter for data sufficiency and degree seeking; no exclusions due to part-time status, transfer status, admission term, or starting program.
Population. The set of unique IDs from the above records.
Blocs. Students ever enrolled in the programs and timely graduates of the programs are required by the metric.
Groupings. We select program, race/ethnicity, and sex for grouping and summarizing.
Outcome. To calculate the metric, we construct a data frame with columns for each grouping variable (program, race/ethnicity, and sex) and the counts by group \small N_\textrm{grad} and \small N_\textrm{ever}.
Dissemination. Exclude groupings too small to preserve anonymity. Edit column names to suit the audience. Condition/transform data as needed for tables or charts.