Get an overview of the enrollment dashboard and understand student cohorts.

This is the introduction and basic functionality tutorial for the National Student Clearinghouse’s Postsecondary Data Partnership Enrollment dashboard. ​

The Enrollment dashboard reports the 12-month enrollment counts and key characteristics for first-time and transfer-in students enrolling in your institution by cohort year. You can use this dashboard to understand institutional context like student characteristics, levels of academic preparation, and access.​

Student cohorts are made up of students who enrolled in college for the first time and students who have recently transferred into your institution in a given year. One of the unique characteristics of the PDP is that all new students are counted, regardless of whether their first term is in the fall, spring, or summer. In fact, you can filter by cohort and cohort term to see the differences between student characteristics starting in different terms. ​

Why is it important to understand students who enrolled in college for the first time across different cohorts? From an enrollment perspective, it is important to understand how your new student population is changing, particularly if you are targeting growth in specific subpopulations.   ​

If you’re involved in implementing support programs, then it’s necessary to understand the population you are serving and how those populations are changing over time. Are there large populations of first-generation students? Students of color? Transfer-in students? Are there smaller populations of credential-seeking students or students enrolling in the summer term?    ​

In addition, it’s important for you to understand access and equity gaps among first-year students. Which students enter college not prepared for college-level math and/or English courses? Or what is the distribution of students by GPA?​

Now, let’s explore the Enrollment dashboard.​

But before we continue, please remember that the results and trends shown in this tutorial can not be applied to your institution. This data is only for demonstration purposes only.  Please review your institution’s data before drawing conclusions.​

This is the Home Page for the Postsecondary Data Partnership dashboards. Clicking the Enrollment icon takes us to the dashboard. Let’s explore the dashboard navigation. ​

At the top are the dashboard’s global filters, which affect both charts on the dashboard. These include metrics like Enrollment Type, Gender, and First-Generation. Applying one or more filters allows us to focus on a specific student population, like first-generation male students who transferred into our institution. ​

Below the global filters is our first reporting section, which gives us the total cohort represented, the number of first-time students, and the number of new transfer-in students for a specific cohort. The dashboard defaults to the most recent cohort, which is the 2018-19 cohort. In that academic year, the institution enrolled 16,083 students. ​

If we apply a filter, like Gender = Female, we see that these numbers change. 

Now, let’s explore the two charts. On the left is a bar chart that gives us the total first-year enrollment by cohort. The data is disaggregated by first-time students, who are represented by a light blue bar, and transfer-in students, who are represented by a dark blue bar. The overall height of each bar represents the total number of first-year students enrolled at the institution in that academic year.​ ​

The chart on the right is a line chart that reports the total number of students enrolled in the cohort by academic year. Notice that, within this chart, we find dimensions. Applying a dimension only affects this chart; it does not affect the stacked bar chart on the left.​ ​

Now, let’s add a filter. Remember that filters affect both charts, while dimensions only affect the chart on the right. I’m curious how many first-year students attend the institution full-time. To find that, click the “Attendance” global filter, deselect “All”, select “Full-time”, and click “Apply”.​

After applying that filter, we see that the number of students showing in our cohort total enrollment went from 16,083 to 7,706, our first-time student enrollment dropped from 11,364 down to 6,076 students, and our new transfer-in enrollment dropped from 4,719 to 1,630 students.  ​

In addition, our bar chart changed to match those enrollment numbers. And, if we hover over the 2018-19 data point on the line chart, we see a total enrollment of 7,706 students.

Now, let’s change Attendance back to include part-time students. Click “Attendance”, click “All”, and click “Apply”. Notice that our first-year population is back to 16,083 since we removed the filter.​

Next, let’s add the “Attendance” dimension to our line chart to see what effect it has. Click “Select Dimension” and select “Attendance”.  ​ ​

We have a line for each of the three attendance categories: Full-time, Part-time, and Unknown. But also notice that the enrollments listed above and in the bar chart on the left are unchanged.  In this case, we are not filtering the underlying data. The only thing we did was ask the line chart to disaggregate by the Attendance variable so that we can compare the enrollment of students who started college as full-time students to students who started college as part-time students. Those categorized as “unknown” were not given an attendance type by our PDP administrator.​

Hovering over the 2018-19 data point, we see that 47.9% of our student population started college as full-time students, 39.2% started college as part-time students, and 12.9% have an unknown status.​

In summary, we explored the definitions, dimensions, filters, and basic functionality of the Enrollment dashboard.​

This dashboard provides important information to better understand the characteristics of students who first enrolled and identify gaps in access and equity.​