With the copious amounts of data in higher education, it can be difficult to know exactly where to start in order to make data-backed decisions.
Ultimately, your existing data paired with the right data analytics platform is all you need to kick off data-centric strategies. Below are seven ways colleges and universities can use their data sets to make improvements that optimize resources and benefit students and faculty.
- Measure course success rates
Course completion and success rates are proof of whether or not students are doing well, so this is data that shouldn’t be overlooked.
By analyzing these rates, it’s possible to identify patterns that can tell you which courses have the best and worst completion rates. The successful courses can tell you how to improve the ones that seem to be struggling. For instance, if completion rates are low for all classes that start before 8 a.m., you may want to look at more successful time periods throughout the day.
This can help you better allocate a department’s budget. Since you’ll have data-backed proof that students are struggling to get through certain courses, you can re-evaluate the program schedule and make program or class adjustments where necessary.
State laws require institutions to report on these rates on an annual basis. Institutions can go a step further by promoting high success rates in marketing and recruitment materials as a way to prove value. With endless options available to anyone who wants an education, proving that your school can prepare students for success is a definite way to gain leverage.
- Identify certain students who may need more support
There’s no such thing as a typical student anymore. Some are full-time and live on campus while others are part-time with full-time jobs. Some students prefer s courses while others like in-person lectures, and nearly everyone is trying to balance school work with their personal lives.
Since every student has a different lifestyle and different needs from their school, Disproportionate Impact reports are the best way to see if and where there are success gaps in your student body. The data in these reports enables institutions to compare outcomes between certain cohorts and measure success rates compared to the entire student population. Cohorts that are commonly assessed include:
- Various ethnicities
- Gender
- Veteran statuses
- First-year students
Here’s an example: If only 65% of first-year commuter students pass their courses, you can compare those who were struggling to those in this cohort who succeeded, as well as to the entire student body. You might find that commuting at certain times makes it difficult for students to get to class on time. From there, you can determine whether moving around schedules or offering more online courses could help improve success rates.
- Keep track of target enrollment numbers
Since a college or university’s success is based on the enrollment rates for every department, program and course, data is used to create a narrative that clearly defines year-over-year enrollment numbers.
If your data tells you that enrollments in kinesiology courses have been significantly declining over the past four semesters, you can identify trends and try making changes to your programs. Maybe the kinesiology program can be combined with another similar program. This also works for certain cohorts. If the declining enrollments are primarily within the female cohort, you can dig a little deeper to explore why.
Your marketing efforts are another area that can be analyzed by enrollment data. If you targeted specific areas during recruitment season, you can measure enrollments by zip code to see if your campaigns were worth the effort.
- Increase retention rates
With so many educational options, understanding students’ motivation and any external factors that could possibly affect their educational success is really the least that institutions can do.
As we’ve mentioned, the types of students working toward a degree represent a diverse crowd. From high school graduates to retired adults, there are external facts that can affect whether or not they continue through your degree program or drop out.
Using data related to dropout rates and times during the year when students stop enrolling in courses, you can filter down by age, demographics and location to figure out why students are leaving.
Here’s an example: If a high number of junior-year nursing students are dropping out after taking the same course, you’ve found the common denominator as to why retention rates are declining. From there, you can assess the times, location and difficulty of the course to see if it needs to be re-evaluated.
If you’re seeing students who are also working full-time dropping out due to an inability to balance their school and work schedules, you could consider offering weekend classes, accelerated degree programs or more online options.
- Build a fact sheet for prospective students
Fact sheets are public institutional documents that show breakdowns of information like student success, graduation, enrollments and retention rates. A lot of schools display their fact sheets on their website, include them in recruitment efforts and share them with prospective students.
When your rates are looking good, fact sheets can be an effective recruitment tool. There’s nothing more attractive to a potential student than cold hard facts that prove the school they’re considering produces successful, career-ready professionals. Graduation rates are especially important since it proves that students stick with your school for the long haul.
Many institutions also keep track of what their students do after graduation, which can be another attractive line item. If 95% of your social worker graduates are hired within six months of graduating, you absolutely need to share this with prospects!
Here are more data-supported facts that students may like to see in your fact sheet:
- Student-to-faculty ratio
- Male-to-female ratio
- Average amount of financial aid students receive
- Percentage of students who work while attending school
- Assess productivity
Productivity reports are crucial since many states use this information as a way to determine how much financing a school can receive.
A prime indicator of productivity is the number of students in every course. With your data, you can see which sections and classes are underfilled, full or overfilled, and then you can adjust scheduling as necessary. Maybe ENG 101 consistently has a wait list or ART 202 is routinely under booked. Guided by your data, reassess program structures to determine where you can better serve your students, increase productivity levels and make course and budget adjustments where necessary.
- Optimize your resources
Half-empty classrooms are a waste of resources, from faculty and student time to electricity and heating. But looking at your section fill rate data is a great way to optimize your resources like electricity, heating, cooling and instructor time.
Compare enrollment data by section and face-to-face, hybrid and online methods to see which are the most successful. If ENG 101 face-to-face lectures are on a decline, you can potentially save resources by migrating certain sections into online formats. Using data in this way addresses one 2020 higher ed prediction that
With campus data, administrators can also strategize a plan for more efficient building use for courses that remain on campus. One option may be to schedule section meeting times in the same buildings to avoid having to light and heat an entire building just for one class.
If you’re just starting with a data analytics platform, don’t let all of the different options for analyzing overwhelm you. Select one area to focus on, like improving course success rates, and narrow your focus. From there, you can venture out to other data sets.
Author Bio:
Eric Spear is the Founder and President of Precision Campus, a higher education data analytics software program designed exclusively for higher education. Eric has more than 20 years of data warehouse development experience, including his work as a senior developer for the University of Maryland, performing all related duties including database management, user requirements, gathering, coding, training, and data administration.
