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“FYE in 180 Days” Sauk Valley Community College Jon Mandrell, Dean of Instruction, SVCC Steve Nunez, Dean of Institutional Research, SVCC Dr. Andrea Wirgau, Assistant Director, DCCL Ferris State University

“FYE in 180 Days” Sauk Valley Community College Jon Mandrell, Dean of Instruction, SVCC Steve Nunez, Dean of Institutional Research, SVCC Dr. Andrea Wirgau,

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“FYE in 180 Days”Sauk Valley Community

College

Jon Mandrell, Dean of Instruction, SVCC

Steve Nunez, Dean of Institutional Research, SVCC

Dr. Andrea Wirgau,Assistant Director, DCCLFerris State University

Background•2-Year Community College

•Located in Dixon, IL(90 miles west of Chicago)

•4000 students annually•700 new students in the fall•300 in the spring

Where we stood…

College success course required

Could be taken anytime in 2 years

Taught by counselors – no faculty

A change in format and curriculum was a common cry

January 18 February March April May June

Campus invites Dr. David Trites to present on retention at the campuswide in-service training

“The Vital Few”

Student success is not an accident – it is the result of intentional activities taken by the college

Jan 11

The Vital Few at SVCC1. Mandatory FYE class in first semester

2. Mandatory Orientation

3. No late registration for new students (once class has met, the student cannot register)

4. Full time retention coordinator (student success coordinator)

5. Course based placement/pre-requisites and developmental

6. Tutoring/additional support for course repeaters.

7  Require a college success program for all remedial students

8. Interactive web site

9. More Bridge programs

10 Partnership with local employers for curriculum and placement

11. More productive designated faculty hours

12. More full time faculty 

One Week Later….• Proposal developed by CAO

• President grants approval

• Diverse Committee Created

• Model Schools Targeted to Visit

• Conferences Targeted

February 2013Visit four colleges with elite programs

Attend Gardner Conference

Establish framework of FYE(Mandated Orientation and College Success Course)

Create course outcomes

March April May June JulyFebruary

• Framework Established

• Late Registration Removed

• Create two subgroups to work on orientation and college success course

• Build syllabus and outline

April 2013Weekly Meetings

Subcommittee Recommendations•Curriculum and textbook•Faculty development•Policy and procedures•Assessment

April 2013:Mandatory Orientation

First-time, degree-seeking students•Send orientation assignments to students -15 sessions offered in summer

3-4 hours long•Sessions provide and overview to:

•Services•Tours of campus•Campus log-ins •Faculty panels

April 2013FYE 101

Course title established•One curriculum is set•16 weeks

•Built into Moodle - Allows data to be tracked in all sections of FYE 101

Don’t forget to pick a logo! (Warning: This can get complicated!)

March April May June July AugustFebruary

Policies and procedures created-Absences, withdrawing

Course approved by State

Instructor training days planned

Instructor recruitment begins…

March April May

June July August

Continue campus visits

Establish class sizes (30 max)

Build sections (24)

Continue recruiting instructors!

February

August 2013Instructor development

Full-time and adjunct faculty

Anyone with a Master’s currently employed by college

The more diverse, the better!

March April May June July August

Send invites for mandated orientation

Have a mock orientation

Adjust!

Host orientation June - August

February

March April May June July August

Continue refining FYE course

Continue to educate public on new mandates!

Keep everyone informed -Address concerns

February

After It Begins..• Frequent contact with instructors• Feedback and sharing – online and

face-to-face• Listen to students“Do I have to take this??”“This class is worthless.”“Is this just a way to make money?”• Make FYE data accessible• Monitor student progress and grades

FYE Student Demographics Numbers

556 first-time, degree seeking students

Gender

56.5% female

43.5% male

Age

86% 23 years or younger (“traditional”)

14% 24 years or older (“nontraditional”)

Ethnicity

85% Caucasian

9% Hispanic

3% African American

Degree seeking type

69.4% A.S. or A.A. (transfer)

30.6% A.A.S. or certificate (CTE)

Enrollment status

66% full-time

34% part-time

Average number of college classes

3.82 (excluding FYE)

HS academic record

2.88 HS GPA

19.9 ACT composite

Impact on Enrollment

➔ Mandates “should” negatively affect enrollment➔ At SVCC, a 1% drop in credit hours would shrink

tuition/fee revenue by $50,000➔ Must have “courage” to do what’s right➔ Fall 2013 “10th day” enrollment numbers

◆ headcount was down 0.4%◆ Illinois community college headcount down 2.2%

Retention Data% Completed Course

PSY 100 (2010-2013) >>>> 94.9 - 95.4%

FYE (2014) >>>> 77.7%

Fall to Spring Retention

PSY 100 (2010-2013) >>>> 76.5 - 82.2%

FYE (2014) >>>> 77.7%

Fall GPA

PSY 100 (2011-2012) >>>> 2.71 GPA for completers

FYE (2013) >>>> 2.83 GPA for completers

http://www.discovercarlisle.co.uk/business/profile/

Can FYE provide an “early alert?”

➔ Common wisdom suggests that early identification of at-risk students can help the college intervene earlier and improve retention.

➔ Ways to predict at-risk students?◆ analyze their high school transcript◆ review early semester data from FYE◆ use both!

Early alert variables➔ How is success (or failure) measured?

◆ Fall Completion Rate (%) (FCR)*● FCR = # credits passed / # credits attempted

◆ Fall Semester GPA* (FGPA)

➔ What variables might correlate to success (failure)?◆ High school GPA (HSGPA)◆ ACT composite score (ACTc)◆ Class attendance in FYE (1st four weeks) (CA)◆ Average grade in FYE (1st four weeks) (AG)

*Excludes FYE

http://blog.oup.com/2012/02/turning-data-into-dates/

Predicting Fall Completion Rateusing linear regression

Independent Variables Dependent Variable Statistical Significance R2 (variance accounted for)

HS ModelHSGPA*

FCR p<0.001 0.147(15%)

FYE ModelCA & AG

FCR p<0.001 0.392(39%)

Combined ModelCA, AG, and HSGPA

FCR P<0.001 0.388(39%)

*ACTc was not significant and not included within the model.

Google Images

Predicting Fall Completion Ratecross tabulations (1)# classes attended

samplesize

FCR %

CA n 100% 80-99% 60-79% 1-59% 0%

0-1 5 0 0 0 20% 80%

2 18 27.8% 0 0 16.7% 55.6%

3 70 38.6% 4.3% 16% 18.2% 22.9%

4 375 62.1% 3.8% 15.3% 12.7% 6.1%

Google Images

Predicting Fall Completion Ratecross tabulations (2)

Average grade on first 4 FYE assignments

sample size FCR %

AG n 100% 80-99% 60-79% 1-59% 0%

A 241 77.2% 3.3% 11.2% 5.6% 1.7%

B 50 62.0% 4% 16% 14% 4.0%

C 84 51.2% 2.4% 28.8% 17.6% 0%

D 30 53.3% 3.3% 26.6% 11.1% 6.7%

Predicting Fall GPA (FGPA)

Independent Variables

Dependent Variable

Statistical Significance of

model

R2 (variance accounted for)

HS modelHSGPA & ACTc

Fall GPA p<0.001 0.289(29%)

FYE modelAG*

Fall GPA p<0.001 0.288(29%)

Combined modelHSGPA, ACTc, & AG

Fall GPA P<0.001 0.411(41%)

*CA was not significant and not included in any models.

Conclusion & Advice•Start somewhere – whatever fits your institution best

•Visit others•Attend conferences•Set up a data accessible FYE program

•FYE data may be used as an early alert

•Continually reassess and improve