- To improve course outcomes. Institutions can analyze assessment data to determine whether there are areas of the curriculum that students don’t understand. If so, the institution can revisit and revise those courses, thereby improving outcomes.
- To predict student outcomes. Institutions can gather and analyze data about students’ grades, course schedules, graduation rates, and more to identify patterns that could predict whether particular students or groups of students will graduate on time. Georgia State University, which is highlighted in this NPR story, is a good example of a university that is using predictive analytics to improve graduation rates.
- Accreditation. Institutional effectiveness is the number-one standard that institutions are found to be out of compliance with. With the right tools, you can extract useful data (enrollment, program effectiveness, etc.) to support accreditation.
Do you have the right technology?
Having the right technology is a key to making big data work. In a 2016 article on EDUCAUSE Review, authors Chris Dede and Andrew Ho note, “The grand challenge in data-intensive research and analysis in higher education is to find the means to extract knowledge from the extremely rich data sets being generated today and to distill this into usable information for students, instructors, and the public.”
That is still true. Luckily, tools are advancing.
I work at a company that develops assessment solutions and see firsthand the impact that data—and good data analysis—can have for higher ed. I also see the immense need that still exists.
I’ll speak specifically to assessment data, which is what I am most familiar with. It’s important to select an assessment solution that helps an institution gather data to measure program success and student outcomes. Formative and summative assessments should be tied to specific outcomes and your data solution should be able to measure the success at the program, course, and student levels.
Here are some tips to consider when selecting technology to manage and analyze assessment data.
- Select data tools that provide administrators, professors, and students with analytics so that customized teaching and learning techniques can be identified, and all levels of an institution can transparently work together to meet academic goals and objectives.
- Select a solution that offers a cloud-based platform. Cloud applications integrate more easily with programs like a learning management system to make a more user-friendly experience. Keeping data in the cloud makes it instantly accessible to those who need it and meets FERPA compliance better than e-mailing reports.
- Select a solution that can be used regardless of whether your assessments are paper-based, online, or a mix. Many institutions still use pencil-and-paper testing sheets and scanners. If your institution is trending toward online assessments, make sure the data analytics tool is flexible enough to support a convenient transition at a pace that is beneficial to everyone.
Big data doesn’t have to be intimidating. Higher education institutions just have to be smart about how they approach it. With the right tools, colleges and universities can harness the power of big data to improve student learning and to meet the requirements of accreditation agencies.
Brian Apperson is vice president of higher education at Apperson, an industry leader in educational testing technology. The company has been improving education for more than 20 years with its scanners, forms, and analysis software. Its newest cloud-based product, DataLink Ascend, is an assessment-management solution that supports both paper and online testing combined with detailed reporting on assessments and learning outcomes.
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