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

Challenges to Institutions

The Players

Number of students who tookan online course in 2011

The investment in onlineeducation in 2012

6.7 MILL ION $91 BILL ION

Technological innovations are transforming both what happens in the college classroom, as well as how students are supported in the admissions process and enrollment. At scale, higher education’s migration to online will rede�ne 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.

2012

62.4%

2002

34.5%

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

48.4%

2002

22.1%

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

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

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

Historically slow to change

Innovation is nearly always incremental

Success in education is difficultto measure

Education has historicallybeen very labor-intensive

Need for broadband Internetaccess may leave out unconnected households

Inadequate technology infrastruc-ture may slow institutional adoption

MOOCs – For Pro�t

Coursera

MOOC2Degree

Udacity

iTunesU

MOOCs – University –Backed

edX

The Open University

Saylor Foundation

OpenupEd

Enablers

2U

Blackboard

Deltak

Embanet

Everspring

Non-Traditional

AltiusEd

American Honors College

Minerva

For – Pro�tsTraditional

Capella

University of Phoenix

London School ofBusiness and Finance

University of Atlanta

Walden

California SouthernUniversity

Devry

1 http://sloanconsortium.org/publications/survey/changing_course_20122 http://www.inc.com/best-industries-2013/april-joyner/online-education-and-training.html3 Global Agenda Council on Education and Skills, "Education and Skills 2.0: New Targets and Innovative Approaches," 2014.4 http://www.babson.edu/Academics/faculty/provost/Pages/babson-survey-research-group.aspx5 http://www.insidepolitics.org/brookingsreports/education%20big%20data.pdf

created by: oBizMedia

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:

IDENTITY

TRADITIONAL DATA NEW DATA

INFERRED CONTENT

Do different segments of a class perform differently on an assessment?

Do tailored questions and question types improve learning outcomes for different groups?

Does the question actually assesswhat it is supposed to?

Name

Administrative rights

School district or university

Permissions

Demographic information

SYSTEM-WIDE

Rosters

Grades

Disciplinary records

Attendance information

USER INTERACTION

Engagement metrics

Time on page

Bounce rates

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

students 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 ONLINEEDUCATION CAN:

Improve graduation rates and student retention

Determine what a learner does and doesnot know

Monitor a student’s behavior and level of engagement

Notify a professor when learner is getting offtrack, bored, or frustrated

Increase engagement via game mechanics

RESEARCHERS WITH THISDATA CAN IDENTIFY ANDANALYZE PATTERNS TO:

Help predict student success

Reduce classroom administrative work

Help faculty refine content to keep relevant

Facilitate both global and local communitydevelopment

Measure student performance beyond test scores

Personalize the learning process