Big Data & Higher Education

“Today, digital innovation is driving unprecedented change across the education sector. In doing so, it has the potential to both improve student learning outcomes and expand access to high-quality education opportunities in ways that would have been unimaginable even a decade ago…” – From Education and Skills 2.0: New Targets and Innovative Approaches

The Higher Education Online Landscape

Number of students who took an online course in 2011: 6.7 Million

The investment in online education in 2012: 91 Billion

Technological innovations are transforming both what happens in the college classroom, as well as how students are supported in the admission process and enrollment. At scale, higher education’s migration to online will redefine what it means to provide a great education to students.

86.5% : According to Babson Survey Research Group, as of 2012, all but 13.5 % of institutions had some online offerings.

Universities offering online degree programs nearly doubled from 2002 to 2012.

2002: 34.5%

2012: 62.4%

Nonprofit institutions with online degree programs more than doubled from 2002 to 2012.

2002: 22.1%

2012: 48.4%

How Education Benefits From More Data

While these investments create new competition in the market, a focus on the market overlooks the potential educational value generated from these investments. Online education is producing vast amounts of data on student learning outcomes, data of the sort that was previously unavailable to student and educators. It will allow academic institutions to better deliver and market their degrees to the right type of students. And it will let students personalize their educational experience to best suit their needs, increasing the chance they graduate and succeed after.

Data From Online Education Can:

Help predict student success

Improve graduation rates and student retention

Determine what a learner does and does not know

Monitor a student’s behavior and level of engagement

Notify a professor when learner is getting off track, bored, or frustrated

Increase engagement via game mechanics

Researchers With This Data Can Identify And Analyze Patterns To:

Personalize the learning process

Reduce classroom administrative work

Help faculty refine content to keep relevant

Facilitate both global and local community development

Measure student performance beyond test scores

The Four Categories of Educational Data

Online education generates a wide variety of data, which universities can use to improve the student learning experience. These data include:

Traditional Data



Administrative rights

School district or university


Demographic information




Disciplinary records

Attendance information

New Data

User Interaction

Engagement metrics

Time on page

Bounce rates

Inferred Content

Do different segments of class perform differently on an assessment?

Do tailored questions improve learning outcomes for different groups?

Does the question actually assess what it is supposed to?

Challenges to Institutions

Universities and colleges must overcome the following challenges to take advantage of data that online education offers.

Historically slow to change

Innovation is nearly always incremental

Success in education is difficult to measure

Education has historically been very labor-intensive

Need for broadband Internet access may leave out unconnected households

Inadequate technology infrastructure may slow institutional adoption

The Players

Outside vendors, both for profit and nonprofit, are moving into higher educational space, a space that was historically left to colleges and universities.

MOOCs- For Profit





MOOCs – University – Backed


The Open University

Saylor Foundation








For – Profits



University of Phoenix

London School of Business and Finance

University of Atlanta


California Southern University




American Honors College




3 Global Agenda Council on Education and Skills, “Education and Skills 2.0: New Targets and Innovative Approaches, 2014



Berkeley School of information