rise of big data in higher education n.
Skip this Video
Loading SlideShow in 5 Seconds..
Rise of Big Data in Higher Education PowerPoint Presentation
Download Presentation
Rise of Big Data in Higher Education

Loading in 2 Seconds...

play fullscreen
1 / 29

Rise of Big Data in Higher Education - PowerPoint PPT Presentation

  • Uploaded on

Rise of Big Data in Higher Education. EDUCAUSE Webinar March 22, 2012 By: 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

I am the owner, or an agent authorized to act on behalf of the owner, of the copyrighted work described.
Download Presentation

PowerPoint Slideshow about 'Rise of Big Data in Higher Education' - fadey

An Image/Link below is provided (as is) to download presentation

Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author.While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server.

- - - - - - - - - - - - - - - - - - - - - - - - - - E N D - - - - - - - - - - - - - - - - - - - - - - - - - -
Presentation Transcript
rise of big data in higher education

Rise of Big Data in Higher Education



March 22, 2012

By: Louis Soares

Center For American Progress

  • 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
What if Education Data was Personal and Mobile?


what is big data
What is Big Data?
  • Fine-grain Information
    • Customer Experiences
    • Organizational Processes
    • Emergent Trends
  • Generated By Doing Business
students 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
technology enabled learning
Technology-Enabled Learning

Each of these interactions is an opportunity to gather Big Data

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

why big data matters
Why Big Data Matters?
  • Cost
  • Quality
  • Knowing the customer
  • Value Co-Creation
quality is in question
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

Additional 16M degrees needed

to be the most educated by 2020

Source: National Center for Higher Education Management Systems, 2009

know your customer
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
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
College As A Service

A. University

B. Student

Service Relationship

A & B create value together

Responsibility Relationship

B on C

Responsibility Relationship

A on C

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.

University Resources




Student Resources





student learning
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
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


course success
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
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
five practices of high performing institutions
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)
it infrastructure for big data
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
Public Policies for Big Data
  • 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.
  • 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.
  • 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.