3R’s: Research, Retention and Repayment Predicting the Future by Understanding Current and Past...

3R’s: Research, Retention and Repayment

Predicting the Future by Understanding Current and Past Students

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.

Importance of data analysis on YOUR campus

and how it links to

greater retention,

improved graduation rates and

enhanced repayment.

Objective

WHAT IS ANALYTICS?

“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

CURRENT ENVIRONMENT

1 in every 4 students leaves college

½ of freshmen

drop out

$13.3 Million Lost to Attrition

$6.2 billion in state appropriated funds

State allocations changing -- supporting graduation

WASFAA Region2009 - 3 Year Cohort Default Rates

Private Schools

Public Schools

Proprietary Schools

WASFAA Region Proprietary Schools - 2009 3 Year CDRs

FOR PROFIT 2YR FOR PROFIT 4YR

30%28%

19%21%

23%25%

< 10% 10% TO 14% 15% TO 20% 21% TO 29% 30% +

Avg for sector = 20.6% Avg for sector = 24.0%

WASFAA Region Public Schools - 2009 3 Year CDRs

PUBLIC 2YR PUBLIC 4YR

14%11%

1%0.06

< 10% 10% TO 14% 15% TO 20% 21% TO 29% 30% +

Avg for sector = 22.2%

Avg for sector = 5.8%

WASFAA Region Private Schools - 2009 3 Year CDRs

PRIVATE 2YR PRIVATE 4YR

8%6% 6%11%

< 10% 10% TO 14% 15% TO 20% 21% TO 29% 30% +

Avg for sector = 22.5% Avg for sector = 5.1%

Sound business principles emphasize higher education institutions much

focus on retaining students to generate an acceptable rate of return

to maintain financial viability.

THE STARTING POINT …

ANALYTICS

Introducing…

Tom And, Molly

Group 1 Group 2 Group 3 Group 4

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

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

Importance of data analysis on YOUR campus

and how it links to

greater retention,

improved graduation rates and

enhanced repayment.

Objective

DATA IS USED TO IDENTIFY TRENDS TO IMPROVE STUDENT SUCCESS

Four Step Process

Step 1Build Data Warehouse

Step 2Define

Research Questions

Step 3Modeling

& Reports

Step 4Tracking

The process starts with organizing your student data

STEP 1: Building a Data Warehouse of Student Information

Turn raw data into meaningful information

STEP 2: Define Your Research Project and Analyze Data

• 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

• 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

Custom reports that provide detail and analytics to make strategic decisions

STEP 3: Benchmark Reports and Predictive Modeling

Reporting Data

Inceptia examples:

• Financial Aid Statistical Reports

Reporting Data

Inceptia examples:

• Enrollment Management Reports

• 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

Inceptia examples:

• Student Success Profile

Effective research and analytics is not “one and done”

STEP 4: Ongoing Analysis to Measure Success

• 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

• 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

THANK YOU!

3R’s: Research, Retention and Repayment Predicting the Future by Understanding Current and Past...

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