Learn how to use the Postsecondary Data Partnership Credit Accumulation Rate dashboard to identify the relationship between GPA and credit accumulation rate.
Transcript
In this tutorial, we demonstrate how to use the PDP Credit Accumulation Rate dashboard to identify the relationship between GPA and credit accumulation rate.
As a quick reminder, the Credit Accumulation Rate Institution-Level dashboard reports the number of students who have successfully completed enough credits for satisfactory academic progress. It also helps clarify which students are (or are not) gaining academic momentum in their college career. Understanding which students are lagging in momentum will help determine which students need additional support.
Let’s use this dashboard to answer this research question: Is there an achievement gap in the credit accumulation rate by academic performance?
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.
On the Home Page for the Postsecondary Data Partnership dashboards, one of the early momentum metrics is the Credit Accumulation Rate Institution-Level dashboard. Clicking this icon takes us to the dashboard.
For now, let’s leave the credit threshold set at 15 credits for part-time students and 30 credits for full-time students.
Our research question asks if there is an achievement gap in the credit accumulation rate by academic performance. Because we want to find an achievement gap, we need to apply a dimension, which will disaggregate our data. Click “Select Dimension” and select “GPA Range”.
We notice that our line chart now has nine lines and our bar chart in the lower left quadrant has nine sections – one for each of the GPA range categories.
The horizontal bar chart in the lower right quadrant is not affected by adding a dimension since it shows overall data.
Because there are nine categories in the GPA metric, it makes it challenging to read these charts. Let’s filter out the mid-range GPAs and keep the higher and lower GPAs. Click the GPA Range global filter, deselect “All” and select “2.0 to 2.5” and “3.5 to 4.0,”then click “Apply”.
Now that our line chart now shows just two lines, and our bar chart shows two sections.
Hovering over the 2018-19 data points, we find that 40.3% of students with a GPA between 3.5 and 4.0 met the credit threshold, while only 14.2% of students with a GPA between 2.0 and 2.5 met the threshold. That is a very large achievement gap.
How does that achievement gap change for part-time students? To focus on a specific student population, we need to apply a filter. Click the “Attendance” global filter, deselect “All”, select “Part-time”, and click “Apply”.
Now, the credit accumulation rate for our high-performing part-time students is 61.8%, while the rate for our lower-performing part-time students is 30.3%. Our achievement gap widened from 26 percentage points to over 30 percentage points.
Now, let’s explore if this achievement gap continues for our part-time students’ second academic year. To change academic years, click the Academic Year filter and select “2”. Now, the students in this dashboard are higher and lower-performing part-time students. The credit accumulation rate now represents the percentage of part-students who completed 24 credits after their second academic year.
Looking at the line chart, we see that the achievement gap has narrowed considerably. However, over the 2018-19 data point, we find that 7.7% of our high-performing part-time students and 2.1% of our lower-performing part-time students achieved that credit threshold.
And, while the credit accumulation rate remained steady for several cohorts of part-time students in their second academic year, the rate declined during the 2018-19 academic year.
How can this information be used? If you know the characteristics of lower-performing students who are less likely to meet credit thresholds, you can share that information with units like academic advising and tutoring services so they can better support this population of students.
As you explore your institution’s PDP dashboards, think about how the data can best be used to support your students. Thank you for joining us.