Published on 2013/07/09

Understanding Analytics in Higher Education

—Co-written with Mike Moore | Senior Account Manager, Analytics, Desire2Learn—

Understanding Analytics in Higher Education
Analytics can be extremely useful for an institution to understand and adapt to the changing needs and demands of students. However, the first step involves understanding how to collect and analyze the breadth of data available.

Institutions collect data every day. What is this data used for? Is the right data being collected? Is this data accurate? Is the data consistently measured? Can reliable decisions be made based on the data? There are many aspects of institutional effectiveness that rely on the analysis of good data. Is there one person or a team of people responsible for collecting and analyzing the data an institution is using in order to impact change within the institution?

These questions will help lay the ground work for institution leaders to understand how to collect and analyze good data so they can improve the functioning of a school by addressing five areas of concern.

What is Analytics?

Accreditation, student retention, student success and institutional improvement; these are many of the areas where analytics can be beneficial. So, what is analytics? Analytics is all of the information gathered about a particular person or situation and the ability to see patterns within that information.  These patterns can help describe, predict and improve performance. Most analytics programs use recorded information from verifiable sources and apply that data to create visualizations and reports to help explain what is being recorded. The first area of concern is determining which individuals will be responsible for collecting the data.

Where is the Data?

For higher education institutions, the aforementioned data can be found in recruitment databases, student information systems, learning management systems and on publisher content sites and individual computers. If the data resides outside of your campus, what is your access to that data? One issue institutions have is the ability to aggregate all of the data into one warehouse. The second area of concern is to develop a plan to provide structure to an analytics data warehouse and determine how the data will be imported.

What Does the Data Look Like?

When developing the data warehouse, you have to make sure the data is accurate. Accuracy starts with putting a responsible person or team in place to understand where all of the data lives. Providing context around this will ensure the data being used is pure, with minimal errors.  Accuracy also encompasses consistency in terms of measurement and collection. The third area of concern is to empower the person or team to develop the protocols to ensure good data is being recorded.

What are the Outcomes?

One point of data collection begins at the course level and progresses through the programs and then to the institution. These are often called student learning outcomes. It is how an institution knows if the students it is graduating have the competencies and knowledge they set out to learn. Each program should develop a curriculum map to determine if the curriculum is aligned to the learning outcomes and to the assessments that will provide evidence of achievement. Each instructor should then use these outcomes to design courses. These assessments can be objective based, project based and/or portfolio based, to name a few. As students work their way through the program, there should be an understanding about whether each student is achieving the learning outcomes that have been put in place. The fourth area of concern is to determine how student achievement aligns to the curriculum of the program.

What are Co-Curricular Outcomes?

What happens once a student leaves the classroom? Is learning being done outside of the program curriculum? As students join campus organizations and participate in other activities, they are adding a wealth of knowledge to the academic curriculum. The fifth area of concern is to determine how to record what a student does outside of the classroom to show institutional competencies.

As the Journey Begins

To use analytics to improve, predict and describe, an institution needs to take a look at its policies and practices by addressing the above concerns. As a team is held responsible for developing the protocols to collect accurate data and the institution comes together to produce good information, there is a path to student success.

Rhonda Blackburn will be discussing data analytics in more detail this September at the annual NUTN Network conference in Albuquerque. To learn more about the NUTN Network conference, please click here

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Readers Comments

Quincy Adams 2013/07/09 at 9:36 am

I think it makes a huge amount of sense to start basing institutional decisions on analytics rather than “gut-feel” and tradition.

The more I consider this analytics question, the more it seems like the movie Moneyball, where the scouts at the beginning of the movie all sat around discussing how a player looked and how he might appear on a baseball card rather than breaking down his statistics and how he would fit into the team.

Analytics are a critical piece of the puzzle as institutions start adapting to their marketplace and operate more like businesses.

Natalie MIller 2013/07/09 at 12:32 pm

This is a very good introduction into the world of data analytics. On the issue of where to store data, perhaps this is where institutions can partner with private companies that specialize in developing data repositories. There are some pretty user-friendly systems being offered on the market that would allow the institution to focus on data interpretation while the private provider would take care of the “back end.”

Ryan Loche 2013/07/09 at 11:58 pm

Data analytics are incredibly important for higher education administrators. They give an indication of how students are faring and whether learning outcomes are being met, and the findings may be used for long-term strategic planning. However, many administrators are still at the point where they don’t know how to collect or interpret this “big data.” They would do well to invest in a team of experts, as Blackburn says, to perform this important function.

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