290 likes | 313 Views
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
E N D
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 • Institutional Practices and Public Policies
What if Education Data was Personal and Mobile? http://www.youtube.com/watch?NR=1&v=8O1i0InZ8bM&feature=endscreen
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
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? • Cost • Quality • Knowing the customer • Value Co-Creation
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 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 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 People Technology Processes Student Resources Finances Preparation Self-Awareness Informed
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)
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 • 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.
THANK YOU! QUESTIONS?? DISCUSSION