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ESSENTIAL DATA FOR ADMISSIONS ADVISERS August 2012 Reuben Ternes, OIRA

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Essential Data for Admissions Advisers. August 2012 Reuben Ternes , OIRA. Overview. Presentation in 6 Parts Introduction to OIRA Part I: FTIAC Growth Part II: Recruitment Data Part III: The Importance of Transfer Students Part IV: Comparing OU to National Data - PowerPoint PPT Presentation

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Page 1: Essential Data for Admissions Advisers

ESSENTIAL DATA FOR ADMISSIONS

ADVISERS

August 2012Reuben Ternes, OIRA

Page 2: Essential Data for Admissions Advisers

Presentation in 6 PartsIntroduction to OIRAPart I: FTIAC Growth

Part II: Recruitment DataPart III: The Importance of Transfer Students

Part IV: Comparing OU to National DataPart V: Academic Success Indicators

OVERVIEW

Page 3: Essential Data for Admissions Advisers

• Tracks and projects enrollment• Reports to federal agencies (IPEDS)• Official record keeper for large amounts of university data• Analyzes policy decisions• (i.e. Is it a good policy to encourage students to take 16

credits their first semester, regardless of their ACT score? What will happen to our retention rates if we change our admission requirements?)

• Reports graduation rates, retention rates, etc.• Gathers and reports on various student surveys.• …and much much more…

WHAT DOES OIRA DO?

Page 4: Essential Data for Admissions Advisers

www.oakland.edu/OIRALots of potentially useful info on the website:

• New student profiles• Enrollment data, current and historical

• Ad hoc reports• Retention and Graduation Rate Data

• NSSE Data• Assessment data and links

• PowerPoint Presentations (including this one)

OIRA WEBSITE

Page 5: Essential Data for Admissions Advisers

Part I

FTIAC GROWTH

Page 6: Essential Data for Admissions Advisers

1998

1999

2000

2001

2002

2003

2004

2005

2006

2007

2008

2009

2010

2011

2012

0

500

1000

1500

2000

2500

3000

1530

1813188819051868

210120532213228723402350

2466231123612430

FTIACs

HISTORICAL FTIACS NUMBERS 1998 - 2012

?

Page 7: Essential Data for Admissions Advisers

CHALLENGES TO FTIAC GROWTH

2006

2008

2010

2012

2014

2016

2018

2020

1500

1700

1900

2100

2300

2500

2700

Projected New Undergraduate (FTIACs) by Year

Goal Pace (25,000 by 2020)Current OIRA Projections

We are here.

Page 8: Essential Data for Admissions Advisers

There are two major obstacles responsible for the gap between the 2020 goal and the steady state projections

1). High School Demographics

2). Current Market Share

UNDERSTANDING THE PROJECTIONS

Page 9: Essential Data for Admissions Advisers

20092010201120122013201420152016201720182019202020210

20000

40000

60000

80000

100000

120000

140000

NCES Projections of Michigan High School Graduates

Page 10: Essential Data for Admissions Advisers

• NCES has revised their projection downward from last year’s projection.

• (This means they expect even fewer students to graduate from MI high schools in the next few years)

NCES NOTES

Page 11: Essential Data for Admissions Advisers

County of Origin % of 2011 FTIAC Cohort

Oakland 42.5%

Macomb 30.4%

Wayne 10.4%

Genesee 2.9%

Lapeer 2.1%

St. Clair 2.0%

Every Where Else 9.7%

2011 OU-FTIACS BY COUNTY

Page 12: Essential Data for Admissions Advisers

MARKET SHARE, 2011 VS. 2006

Market Share of FTIACsCounty 2011 2006

Oakland 15.5% 15.4%

Macomb 23.5% 25.1%

Wayne 4.0% 3.7%

Page 13: Essential Data for Admissions Advisers

Bad News for FTIAC Enrollment• High school graduates are down• We will need to do more with less

• Over 80% of our FTIACs come from only 3 counties• Our market share in other counties is low and/or non-existent.

The Good News for FTIAC Enrollment• The decline in projected high school students is slightly less severe in Oakland and Macomb counties (at least for the next few

years).• These are the counties where we have the highest market share.

FTIAC GROWTH: GOOD AND BAD NEWS

Page 14: Essential Data for Admissions Advisers

Part II

RECRUITMENT DATA

Page 15: Essential Data for Admissions Advisers

HIGH SCHOOLS WITH MOST ENROLLED

FTIACS

Top 22 Feeder High Schools for Fall 2011Rank Name Enroll

edRank Name Enroll

ed1 Eisenhower 79 12 Utica 412 Adlai E

Stevenson 75 13 Waterford Mott 39

3 Lake Orion Community 67 14 Rochester Adams 37

4 Romeo 58 15 Warren Mott 335 Stony Creek 57 16 Holly 316 Rochester 55 17 Anchor Bay 287 Athens 54 18 Avondale Senior 27

8 Clarkston Senior 51 19 Brandon 27

9 Troy 50 20 Walled Lake Central 25

10 Henry Ford II 47 21 Paul K Cousino 24

11 Chippewa Valley 41 22 Pontiac 23

Page 16: Essential Data for Admissions Advisers

Yield: the probability that an applicant will enroll.Many variables are correlated with yield

HS GPA

ACT scores

Plus many others.The relationship between HS GPA and yield follows a

non-obvious (and non-linear) pattern.

YIELD BY HS GPA

Page 17: Essential Data for Admissions Advisers

YIELD BY HS GPA FOR FALL 2010

Page 18: Essential Data for Admissions Advisers

• ACT scores follow a similar pattern• Predicting who will attend is not straightforward• Because of this, OIRA used a technique known as Random Forest to predict who might attend and who

might not.• It works a lot like Netflix.

• It does not work like Pandora! (Pandora has a terrible algorithm).

• Takes into account over 50 different variables!• Like Application date, event registration, time between

application and decision, scholarship offers, family income, HS rank and size, ACT scores, etc. etc.

YIELD, CONTINUED

Page 19: Essential Data for Admissions Advisers

• Accuracy = 75%• So, it’s pretty good.

• But it still gets a lot of predictions wrong. It’s not perfect!

• RF is another tool in the toolbox. • It’s useful, but it won’t do our jobs for us.

RANDOM FOREST: WHAT YOU NEED TO KNOW

Page 20: Essential Data for Admissions Advisers

Part IIISWITCHING FOCUS: THE ROLE OF THE TRANSFER

STUDENT

Page 21: Essential Data for Admissions Advisers

New students = FTIACs + New Transfers2361 new FTIACs in 2011

1891 new transfer students in 2011This Year:

FTIACs up 3%

Transfers up 3%

Official count is not until the end of September, so these numbers may fluctuate.

About half of our seniors are transfers.

(Which suggests that about half of our degree recipients are too)

PART III: TRANSFER DATA

Page 22: Essential Data for Admissions Advisers

WHERE DO OUR TRANSFER STUDENTS COME FROM?

Campus Name FA11 New X-fersMacomb Cmty Coll Center

Campus 326OCC – Auburn Hills 193

OCC 123OCC – Highland Lakes 76MCC – South Campus 70

Wayne State University 52OCC – Royal Oak 49

OCC – Orchard Ridge 46Central Michigan University 40Western Michigan University 31

Schoolcraft College 32Michigan State University 31

GVSU 30

Page 23: Essential Data for Admissions Advisers

Approximately 75% come from 2-year colleges while 25% come from 4-year institutions.

Almost 50% were 21 or younger.About 25% are 25 or older.

72% were full-time.70% had a GPA of a 2.5 or higher from their former

institution. Half had a GPA of 2.9 or higher.

NEW TRANSFER STUDENT PROFILE (FALL 2011)

Page 24: Essential Data for Admissions Advisers

Part IV

SIMILARITIES AND DIFFERENCES: COMPARING

OU TO NATIONAL DATA

Page 25: Essential Data for Admissions Advisers

OU has two major student surveys through OIRACIRP (freshmen only)

NSSE (freshmen and seniors)

Results for both are available on: www.oakland.edu/OIRA

These surveys give us information about our student bodyHow many hours they work?

How difficult they find courses to be at OU

How much money their parents make

How often they drink

Why they choose OU

Etc…

Mostly, we find that OU is similar to other institutions. However, there are some differences.

SURVEYS

Page 26: Essential Data for Admissions Advisers

1996

1998

2000

2002

2004

2006

2009

2011

0

10

20

30

40

50

60

70

Good academic rep-utationWanted to live near homeCostOffered financial assistanceGraduates get good jobs

VERY IMPORTANT REASONS TO SELECT

OU

Page 27: Essential Data for Admissions Advisers

1995

1996

1997

1998

1999

2000

2001

2002

2003

2004

2005

2006

2007

2009

2010

2011

0.0%

5.0%

10.0%

15.0%

20.0%

25.0%

30.0%

35.0%

OUComparison

THE IMPORTANCE OF KEEPING UP TO DATE WITH POLITICS

Page 28: Essential Data for Admissions Advisers

1993

1996

1998

2000

2002

2004

2006

2009

0.0

10.0

20.0

30.0

40.0

50.0

60.0

OUComparison

Perc

enta

ge P

oint

sMARIJUANA SHOULD BE

LEGALIZED

Page 29: Essential Data for Admissions Advisers

1995

1997

1999

2001

2003

2005

2009

2011

0.0

10.0

20.0

30.0

40.0

50.0

60.0

OUComparison

DRANK BEER DURING HIGH SCHOOL YEAR

Page 30: Essential Data for Admissions Advisers

Class Oakland Selected Peers

First-Year 25% 16%

Seniors 58% 45%

MORE THAN 15 HOURS PER WEEK WORKING OFF CAMPUS

Page 31: Essential Data for Admissions Advisers

2003 2005 2007 2009 20112.9

2.95

3

3.05

3.1

3.15

3.2

3.25

OUPeer

“THE ENVIRONMENT EMPHASIZES SPENDING SIGNIFICANT AMOUNTS

OF TIME ON ACADEMIC WORK”

Average NSSE Response (Freshmen)

“Quite a Bit”

“Very Much” (4.0)

“Some” (2.0)

Page 32: Essential Data for Admissions Advisers

TIME SPENT ON ACADEMIC WORK

11-15 HoursPer Week

6-10 Hours Per Week (3.0)

2007 2009 20113.3

3.4

3.5

3.6

3.7

3.8

3.9

4

4.1

OUPeer

Page 33: Essential Data for Admissions Advisers

Part V

ACADEMIC SUCCESS INDICATORS

Page 34: Essential Data for Admissions Advisers

2003 2004 2005 2006 2007 2008 2009 2010 20115

8

11

14

17

20

23

PERCENTAGE OF FULL TIME FTIACS WITH 1ST SEMESTER GPAS LESS THAN 2.0

Page 35: Essential Data for Admissions Advisers

1992

1994

1996

1998

2000

2002

2004

2006

2008

2010

50%

55%

60%

65%

70%

75%

80%

85%

90%

FT-FTIAC RETENTION TO SECOND YEAR

Page 36: Essential Data for Admissions Advisers

6-YEAR GRADUATION RATE BY ACT SCORE

Page 37: Essential Data for Admissions Advisers

6 YEAR GRADUATION RATE BY HS GPA

Page 38: Essential Data for Admissions Advisers

FIRST YEAR RETENTION RATE BY ACT SCORE

Page 39: Essential Data for Admissions Advisers

FIRST YEAR RETENTION BY HS GPA

Page 40: Essential Data for Admissions Advisers

What questions do you have for me?What questions do you have for OIRA?What data do you use on a regular basis?What information do you need?What tools do you need to turn your data into information?

QUESTIONS