3R’s: Research, Retention and Repayment
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Transcript of 3R’s: Research, Retention and Repayment
3R’s: Research, Retention and Repayment
Predicting the Future by Understanding Current and Past Students
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Ted LannanDirector of Market Research
Ted began his career as a teacher and counselor working with an Upward Bound program. His primary focus was on college placement and career planning for the students.
Then, Ted transitioned into market research where he then spent the span of his career.
Now with Inceptia, he applies business analytics to higher education.
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Importance of data analysis on YOUR campus
and how it links to
greater retention,
improved graduation rates and
enhanced repayment.
Objective
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WHAT IS ANALYTICS?
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“Analytics is the use of data, statistical analysis, and explanatory predictive models to gain insights and to act on complex issues.”
Analytics in Higher Education: Benefits, Barriers, Progress and Recommendations, August 2012EDUCAUSE Center for Applied Research
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CURRENT ENVIRONMENT
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1 in every 4 students leaves college
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½ of freshmen
drop out
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$13.3 Million Lost to Attrition
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$6.2 billion in state appropriated funds
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State allocations changing -- supporting graduation
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WASFAA Region2009 - 3 Year Cohort Default Rates
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Private Schools
Public Schools
Proprietary Schools
5.7%
10.1%
23.0%
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WASFAA Region Proprietary Schools - 2009 3 Year CDRs
FOR PROFIT 2YR FOR PROFIT 4YR
30%28%
18%
23%
19%21%
23%25%
11%
3%
< 10% 10% TO 14% 15% TO 20% 21% TO 29% 30% +
Avg for sector = 20.6% Avg for sector = 24.0%
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WASFAA Region Public Schools - 2009 3 Year CDRs
PUBLIC 2YR PUBLIC 4YR
11%
80%
14%11%
41%
8%
28%
1%0.06
0
< 10% 10% TO 14% 15% TO 20% 21% TO 29% 30% +
Avg for sector = 22.2%
Avg for sector = 5.8%
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WASFAA Region Private Schools - 2009 3 Year CDRs
PRIVATE 2YR PRIVATE 4YR
44%
84%
17%
8%6% 6%11%
2%
22%
1%
< 10% 10% TO 14% 15% TO 20% 21% TO 29% 30% +
Avg for sector = 22.5% Avg for sector = 5.1%
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Sound business principles emphasize higher education institutions much
focus on retaining students to generate an acceptable rate of return
to maintain financial viability.
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THE STARTING POINT …
ANALYTICS
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Introducing…
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Tom And, Molly
Group 1 Group 2 Group 3 Group 4
43%
18%
27%32%
% Graduates
What does the data say?
Group1 = Above Average ACT / Above Average GPA
Group 2 = Below Average ACT / Below Average GPA
Group 3 = Above Average ACT / Below Average GPA
Group 4 = Below Average ACT / Above Average GPA
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Analytics:• Evaluates data to determine patterns• Helps mine and connect vast amounts of
information• Are being used a schools nation-wide• Offer a predictive view of upcoming challenges• Make available a means to target available
resources
What you should know about analytics
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Importance of data analysis on YOUR campus
and how it links to
greater retention,
improved graduation rates and
enhanced repayment.
Objective
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DATA IS USED TO IDENTIFY TRENDS TO IMPROVE STUDENT SUCCESS
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Four Step Process
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Step 1Build Data Warehouse
Step 2Define
Research Questions
Step 3Modeling
& Reports
Step 4Tracking
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The process starts with organizing your student data
STEP 1: Building a Data Warehouse of Student Information
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Turn raw data into meaningful information
STEP 2: Define Your Research Project and Analyze Data
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• What has been the impact of various recruiting strategies and/or policies on bringing students to campus?
• What are the best high schools, counties and states to target for producing graduates? What characteristics make up our recruiting efficiency profile?
• Where did students go who were admitted but did not matriculate?• Which strategies have produced the most enrollees and graduates?
What has happened to the "Trustee Admits"? • How much does your institution spend in institutional aid to produce a
successful graduate? How much is wasted on dropouts?• What are the characteristics of successful graduates versus dropouts?• What high school GPA and ACT levels does it really take to be
successful at your institution? Which is more important?• Which majors produce the most graduates?
Your school’s data can help you answer important questions
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• Who are the populations that you serve and how big are they?
• What does it mean to be successful with each population?
• What learn of “academic preparation” is really needed for each of your programs of study?
• Does remediation work? Are their better ways to promote academic success?
• Where do your students go after they leave your school?
Questions for Community Colleges
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Custom reports that provide detail and analytics to make strategic decisions
STEP 3: Benchmark Reports and Predictive Modeling
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Reporting Data
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Inceptia examples:
• Financial Aid Statistical Reports
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Reporting Data
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Inceptia examples:
• Enrollment Management Reports
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• Predictive modeling uses past information to help predict the future• Rank students by degree
of risk and identify risk factors for each student – early intervention is key
• Effectively use your resources to ensure the greatest results with students
Predictive Modeling
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Predictive Modeling
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Inceptia examples:
• Student Success Profile
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Effective research and analytics is not “one and done”
STEP 4: Ongoing Analysis to Measure Success
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• Data • Data quality, data ownership, data access
and data standardization
• Affordability• Expenses of staff, training and tools• Demand on IR and IT resources
• Accountability requirements mean IR is focused on reporting
Roadblocks
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• Map out strategy and planning• Find an advocate among senior
administration• Look for an early win• Invest in people over tools• Don’t wait for perfection• Partnerships and communication
are key• Plan for an infrastructure that
supports analytics• Benchmark to provide context
Creating Success
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THANK YOU!