utMetrics provides the official metrics of Utah Tech University. These metrics can be used in both internal and external presentations regarding Utah Tech University. If you need metrics that need to come from or match USHE or IPEDS, please reach out to the Insitutional Effecitiveness office (datablaze@utahtech.edu) to receive those metrics.
Metric Names
Metric names are designed to give a clear understanding of the metric.
Metric names are derived from the components of the Metric.
- Season (if applicable)
- Computation
- by
- Partition(s)
- :: Segment(s) (if applicable)
To see more information about metric names, see Naming Metrics Vignette
Season and Year (Term)
Metrics are calculated by season (Fall, Spring, Summer) and Year. Season and Year together is referred to as Term. The term code (202440) is the term Fall 2024. Season may also be tied to the computation. Sometimes the season, is integrated into the computation name (i.e. Fall to Fall Comeback Rate), which will also have a season of Fall. To see more information about year, see Computations - utMetrics Vignette
| Term | Season | Year |
|---|---|---|
| Fall 2023 | Fall | 2023 |
| Spring 2022 | Spring | 2022 |
| Summer 2021 | Summer | 2021 |
Computation
Metrics are organized by computations. The Computation is the way the metric is computed or calculated.
There are several computations in the utMetrics package:
- Headcount
- Census Headcount
- End of Term Headcount
- Cohort Retention
- Fall to Fall Cohort Retention
- Returned 3rd Fall Cohort Retention
- Returned 4th Fall Cohort Retention
- Term to Term Retention
- Fall to Spring Comeback Rate
- Fall to Fall Comeback Rate
- Fall to Spring Return Rate
- Fall to Fall Return Rate
- Graduation Rate
- 150% Graduation Rate
- Full-Time Equivalent (FTE)
- Census FTE
- End of Term FTE
To see more information about computations, see Computations Vignette
Partition
Each metric can be displayed by partitions and segments. Partitions are a way to parse or break down a metric. In the literature, this is often referred to as disaggregating data. More than one partition can be used in a metric.
There are more than 30 partitions. Here are some common examples:
- All Students
- All Degree Seeking Students
- Gender
- College
- Department
- Cohort
- Race Ethnicity
- Minority
- Student Type
- Course Load
- Course Level
Partitions can also be combined. All the metrics displayed below have more than one partition, this allows the metric to be displayed by more than one category.
Here are some examples:
- Student Type, Course Load
- College, Gender
- Cohort, Entering College
- Online Program, College
When a metric has more than one partition, they are displayed in the naming with a hyphen.
Here are examples using the examples above:
- Student Type-Course Load
- College-Gender
- Cohort-Entering College
- Online Program-College
Segments
Each partition creates segments. Segments are the values that each partition produces. The values are typically unique to the partition. For example, the partition of Gender would create the segments of Male and Female.
If partitions are combined as described above, then segments will also be combined. When more than one segment is present, the data is separated by a hyphen (i.e. Gender and College partitions produce segments that look like this: Male-CHASS).