Rise of Big Data in Higher Education

EDUCAUSE Webinar

March 22, 2012By: Louis Soares

Center For American Progress

Overview

• Personal Data and Consumer Agency

• Big Data in Higher Education?

• Why Big Data Matters?

• Co-Creating Value with Big Data

• Institutional Practices and Public Policies

What if Education Data was Personal and Mobile?

http://www.youtube.com/watch?NR=1&v=8O1i0InZ8bM&feature=endscreen

The Rise of Consumer Agency

Big Data In Higher Education?

What is Big Data?

• Fine-grain Information– Customer Experiences– Organizational Processes– Emergent Trends

• Generated By Doing Business

Students Doing Business

• Course Selection• Course Registration• Apply for Financial Aid• Class Participation• Study Alone or in groups• Use Online Resources• Purchase/Return Textbook • Work to support education

Black Box EDU

Technology-Enabled Learning

U.S. Department of Education, National Education Technology Strategy, 2010

Each of these interactions is an opportunity to gather Big Data

Questions?

Why Big Data Matters?

• Cost

• Quality

• Knowing the customer

• Value Co-Creation

College Is Expensive

Quality Is In Question

Study of 2,300 undergraduates

– 45 percent “demonstrated no significant gains in critical thinking, analytical reasoning, and written communications during the first two years of college”

– 36 percent show no improvement in four years

# of Credentials Source

1.3 million degrees projected population growth

4.3 million degrees increase high school graduation rates, college-going rates of recent HS graduates, and postsecondary graduation rates

4.2 million degrees half of the 8.4 million adults (25-34) w/ some college complete degree

2.6 million degrees third of the 8.8 million adults (35-44) w/ some college complete degree

3.4 million degrees fifteen percent of the 22.7 million adults (25-44) who have completed high school, but not attended college, complete a degree

Additional 16M degrees needed to be the most educated by 2020

Source: National Center for Higher Education Management Systems, 2009

Know Your Customer

Characteristics on Non-Traditional

• delayed enrollment PSE beyond the first year after HS

• Attend part time

• Are financially independent from their parents

• Work full time

• Have dependents other than a spouse

• Are a single parent

• Have no high school diploma or GED

What Is A Service?An offering in which:

• “deeds, processes, and performances” are provided in “exchange relationships” among organizations and individuals

• Value is co-created by supplier and consumer

• Examples include:– educational services, – health care services, – financial services, – Transportation services,

College As A Service

A. University B. Student

C. College Education

Transforms student knowledge through:

agreements, relationships and other exchanges

among students and university faculty, including

courses offered and taken,tuition paid, and work-study arrangements.

Student Resources

FinancesPreparation

Self-AwarenessInformed

Service Relationship

A & B create value together

Responsibility Relationship

A on C

Responsibility Relationship

B on C

University Resources

People

Technology

Processes

Questions?

Co-Creating Value with Big Data

Student Learning• 425,000 students • Web-based learning environments• Self-directed Learning• Adaptive instructional software• Data Dashboards

– Improve individual performance

– Enhance course redesign

– Predict future performance

Course Enrollment

• 40,000 Students• Course Recommendation Engine

– Service Oriented Higher Education Recommendation Personalization Assistant

• Student Profile– Course preferences– Schedules– Past courses

• Tools– Tutors– Time-management tools– Life-planning resources

SHERPA

Course Success

• Early Warning System • Study patterns and performance• Student/Faculty Dashboard• Profile Development

– Student demographics

– Grade books

– Activity logs from online resources

• Benchmark successful students• Seek Support

Student Lifestyle Management

• Learning Communities• Behavioral Science• Student Profile

– Work/life details– Academics– Preferences

• Nudges to stay on-track– Mobile Platform– Time management– Academic Setbacks– Peer groups

Institutional Practices and

Public Policies

Five Practices of High Performing Institutions

Increase Rate of Degree Completion• Culture of Completion and

Outplacement • Reduce nonproductive credits

Reduce Cost per Student • Redesign instruction delivery• Redesign core support services

– (HR, IT, Finance, student services, academic support services, plant operations)

• Optimize non-core services and other operations– (research, public services, auxiliary

enterprises)

Six Characteristics of Instruction Redesign that

Improve Completion and Reduces Costs

Whole Course Redesign

Target whole course not a single class

Analyze time spent on each activity in course by person

Active Learning Move course from teacher led to active and learner-centered

Note taking replaced by active learning exercises

Computer-based Learning

Web-based tutorials and exercises and

low-stakes quizzes frequent practice and feedback

Mastery Learning

Greater flexibility for when students can engage with a course, not self-paced

Organized by the need to master specific learning objectives, modular

On-Demand Help

Variety of different supports build sense of learning community

Projects replace lectures w/ small group activities (tech supported, staffed assisted)

Alternative Staffing

Apply right level of human intervention to particular problems

Task specific labor: faculty v. GTA, Peer mentors, Course assistant

IT Infrastructure for Big Data

Source: Action Analytics, EDUCAUSE REVIEW,January/February 2008, Authors: Donald Norris, Linda Baer, Joan Leonard, Louis Pugliese, and Paul Lefrere

Public Policies for Big Data

1. Create guidelines for how data generated through these technology tools should be treated in order to promote student privacy while allowing for the data to be shared in a social environment.

2. Review the data it currently collects to find areas where the information might supplement the emerging user-generated data in ways that help students make better choices.

3. Fund the development or spread of emerging “personalization” tools through competitive grants. A special focus could be placed on institutions that serve low-income students and students of color.

THANK YOU!

QUESTIONS??

DISCUSSION