Data analytics is revolutionizing education, and the numbers don’t lie. According to recent research, the global big data analytics market in education was valued at an impressive $18.02 billion in 2022 (Global Big Data Analytics in Education Market Report 2022-2027). Looking into the future, the valuation is projected to experience a substantial growth rate, reaching a staggering $36.12 billion by 2027, with a CAGR of 14.92%.
This rapid growth is a testament to the immense potential that data analytics can offer to educational outcomes. If you want to jump on the trend, this article is for you. We’ll explore some of the ways that educational institutions can harness the power of data analytics for their students and faculty.
Big data refers to the vast amounts of information generated every day in our digital world. In the context of education, big data encompasses a range of student and institutional information, including:
- Student data: demographics like age, ethnicity, and gender; full-time or part-time status; online, on-campus, or mixed-mode class attendance.
- Course data: enrollment headcounts; grades and completion rates by program or section.
- Instructor data: demographics like age, ethnicity, and gender; salary information; productivity levels.
- Facility data: classroom utilization and resource allocation; hours per week each room is being used.
However, organizations need to take additional measures (aside from just collecting it) to derive insights and value from this wealth of data. Without a robust data analytics program, this information remains untapped and useless.
The traditional one-size-fits-all approach to education is on its way out. Now, thanks to analyzing data in education, organizations are changing the way they approach teaching and learning. This is achieved through:
- Improved decision-making. Data analytics is empowering educators to make more evidence-based decisions. From teaching strategies to student support, there are insights into every aspect of education.
- Targeted interventions. Organizations can identify areas where students or faculty may be struggling and develop targeted interventions to address those issues. For example, many students are consistently failing a particular subject, or staff members aren’t taking any professional development opportunities.
- Improved student outcomes. By leveraging insights, educators can help struggling students catch up, and high-performing students can excel even further.
- Higher efficiency. With data analytics, everything is centralized in a single, easily accessible location. As a result, it streamlines administrative tasks, be it managing student enrollment, attendance, or financial records.
- Better communication. Instead of working in silos, educators, administrators, and other staff members can share data and be collaborative. This approach also breaks down barriers between educators and students (and their parents).
- Resource optimization. Data analytics can solve the challenge of optimizing resources and managing costs while delivering high-quality education. Striking such a balance doesn’t come easy otherwise.
Education isn’t immune to the demands of the business landscape. To stay afloat and remain relevant, organizations need to be agile and innovative, constantly seeking new ways to operate. One way to do this is by using data analysis.
Think of data analysis in education as a map that guides organizations on a journey to success. Through the collection and analysis of data on performance, attendance, and other key metrics, they gain a clearer picture of how students and workers are doing. Of course, what they do after also matters.
Data may reveal that a large number of students are not attending classes regularly. In that case, you can look into implementing new policies or incentives to encourage attendance. Maybe there are logistical challenges in getting to school. Whatever the reason turns out to be, the issues might not have been identified in the first place.
Similarly, data analysis can point out to faculty members where they may need to adjust their teaching methods or course materials to better support student learning. And they can track their own effectiveness as teachers.
If you’re eager to make the most out of your institution’s data, there are many exciting ways to leverage the power of data analytics.
With the right tools for data analytics for schools, institutions can track student progress in real time. This can be incredibly beneficial for both teachers and students. Teachers can promptly detect and address the needs of struggling students through targeted support, while students can set goals for improvement.
At the University of New England, the implementation of the Automated Wellness Engine has changed the policy for student support. The AWE utilizes a combination of data from various university systems (including the online student portal) to identify high-risk students. Faculty members have reports with detailed reasons for withdrawals and wellness-happiness ratings. As a result, they can identify who’s struggling or may be dropping out and provide timely support. During the testing period, the dropout rate went down from 18% to 12%.
Resource allocation is a critical area that data can optimize. This involves analyzing financial, human, and physical resources so that institutions can decide how to allocate resources most effectively.
For example, data analytics can detect where an institution is overspending or underspending. This will allow them to adjust their expenditures for maximum impact and possibly invest more resources for better revenue.
Similarly, data tools can be used for staffing levels. If that’s your goal, you’ll need to analyze employee productivity and workload and find out where employees may be overworked or underutilized.
Institutions are now more equipped to create courses that better align with student needs and interests. For example, Austin Peay University has created a nifty tool called Degree Compass that helps students select the best modules to study. By analyzing a student’s academic history and interests, Degree Compass recommends modules that are most likely to be a good fit. One of the most helpful aspects is the ability to identify patterns that may not be immediately apparent to human advisors.
According to students themselves, this new approach leads to greater success and satisfaction in their academic pursuits.
Curriculum insights can inform the development of new classes. By analyzing data, you can identify gaps in existing course offerings and start developing new courses that fill those gaps.
Using data on student performance, interests, and learning styles, you can tailor learning experiences as needed. Compare students who are gifted in a particular subject or those who have unique learning needs. In the first case, you’d want to challenge them with advanced materials, while in the latter, you’d want to provide additional support for cognitive, behavioral, or emotional differences.
Another possible application is for people with different learning styles. Some students may learn better through visual aids, while others may prefer a more hands-on approach. So, for the first group, instructors can incorporate more images, videos, and infographics into their teaching materials. For the second group, there will be more practical exercises and real-life examples.
A university could analyze its past successful admissions. The findings may reveal that students with a certain GPA range and extracurricular activities are most likely to enroll and succeed. The organization could then focus its recruitment efforts on attracting more students with those specific characteristics.
Another reason to leverage data is to address roadblocks that cause prospective students to abandon their applications. For example, if many applicants are dropping out during a certain stage of the application process, this stage needs optimizing and simplifying. If sorted out, the results may be a higher enrollment rate and a more diverse student body.
You can even predict enrollment numbers for future semesters with reasonable accuracy. This will help you plan for the resources you’ll need. This includes faculty, classrooms, and other facilities, as well as resources for marketing and recruitment strategies.
Institutions can leverage data analytics to gain insights into how students are interacting with course materials. And if done in real time, educators can make necessary adjustments to course materials, pacing, or teaching methods.
Open University Australia has developed a software tool called Personalised Adaptive Study Success. PASS works with various types of data—individual characteristics, social web, curriculum, and physical data—to see who’s experiencing disengagement. The tool also recommends relevant content and activities that engage students back in their educational journey.
Colleges and universities are always looking for vital partners who can help promote the institution and its programs, provide networking opportunities for current students, and contribute to fundraising efforts. And yes, data analytics in higher education helps with that, too.
For example, institutions can track alumni giving patterns and determine which groups are most likely to donate. They can uncover specific appeals that resonate most with their alumni. It can be scholarship opportunities, research initiatives, campus improvements, or some other cause. Additional insight into the most effective methods of reaching donors—email marketing, social media, and direct mail—will also help.
With the rapid growth of data in academia, analytics is becoming essential to making sense of the vast amounts of data that researchers are generating. At Walden University, they’ve found a way to make tracking scholarly activity much easier and more engaging than just keeping a spreadsheet. They’re using a data analytics tool called Faculty Insight to aggregate and match data on individual faculty members’ scholarly activities.
Faculty Insight examines publications, citations, research grants, and professional honors. Together, it provides a comprehensive view of the member’s output. The tool is available to academic leaders and faculty members alike, so both have insights into possible funding sources, award opportunities, and research collaborators.
These eight ways to leverage data analytics demonstrate the vast potential of this technology for educational institutions. However, to truly succeed in leveraging data analytics, organizations need to make a conscious effort. And more importantly, they need to turn to collaboration.
By working with technology vendors, data analysts, and other stakeholders, educational institutions can tap into the tools and expertise needed for the implementation. It’s like building a dream team, where everyone brings unique skills and perspectives to the table to make the most out of data.
Educational organizations, particularly management, must also be flexible and open-minded to embrace new ideas and approaches. As the field of data analytics continues to evolve, it’s crucial to stay up-to-date with the latest trends and best practices in the industry. This means being willing to invest in the necessary technology and resources. Only then can organizations position themselves for success in the digital age.
Reach out today to leverage data analytics in education! For 28+ years, the Intetics team has been at the forefront of talent and people innovation, helping our clients in 17+ industries stay ahead of the curve.