1. “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

2. 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

3. 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

4. January 18FebruaryMarchAprilMayJune 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

5. The Vital Few at SVCC 1. 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

6. One Week Later …. Proposal developed by CAO President grants approval Diverse Committee Created Model Schools Targeted to Visit Conferences Targeted

7. February 2013 Visit four colleges with elite programs Attend Gardner Conference Establish framework of FYE (Mandated Orientation and College Success Course) Create course outcomes

8. MarchAprilMayJuneJulyFebruary Framework Established Late Registration Removed Create two subgroups to work on orientation and college success course Build syllabus and outline

9. April 2013 Weekly Meetings Subcommittee Recommendations Curriculum and textbook Faculty development Policy and procedures Assessment

10. 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

11. April 2013 FYE 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!)

12. MarchAprilMayJuneJulyAugustFebruary Policies and procedures created -Absences, withdrawing Course approved by State Instructor training days planned Instructor recruitment begins…

13. MarchAprilMayJuneJulyAugust Continue campus visits Establish class sizes (30 max) Build sections (24) Continue recruiting instructors! February

14. August 2013 Instructor development Full-time and adjunct faculty Anyone with a Master’s currently employed by college The more diverse, the better!

15. MarchAprilMayJuneJulyAugust Send invites for mandated orientation Have a mock orientation Adjust! Host orientation June - August February

16. MarchAprilMayJuneJulyAugust Continue refining FYE course Continue to educate public on new mandates! Keep everyone informed -Address concerns February

17. 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

18. 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

19. 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 “10 th day” enrollment numbers ◆ headcount was down 0.4% ◆ Illinois community college headcount down 2.2%

20. 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/

21. 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!

22. 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/

23. Predicting Fall Completion Rate using linear regression Independent VariablesDependent VariableStatistical Significance R 2 (variance accounted for) HS Model HSGPA* FCRp<0.001 0.147 (15%) FYE Model CA & AG FCRp<0.001 0.392 (39%) Combined Model CA, AG, and HSGPA FCRP<0.0010.388 (39%) *ACTc was not significant and not included within the model. Google Images

24. Predicting Fall Completion Rate cross tabulations (1) # classes attended sample size FCR% CAn100%80-99%60-79%1-59%0% 0-1500020%80% 21827.8%0016.7%55.6% 37038.6%4.3%16%18.2%22.9% 437562.1%3.8%15.3%12.7%6.1% Google Images

25. Predicting Fall Completion Rate cross tabulations (2) Average grade on first 4 FYE assignments sample sizeFCR% AGn100%80-99%60-79%1-59%0% A24177.2%3.3%11.2%5.6%1.7% B5062.0%4%16%14%4.0% C8451.2%2.4%28.8%17.6%0% D3053.3%3.3%26.6%11.1%6.7%

26. Predicting Fall GPA (FGPA) Independent Variables Dependent Variable Statistical Significance of model R 2 (variance accounted for) HS model HSGPA & ACTc Fall GPAp<0.001 0.289 (29%) FYE model AG* Fall GPAp<0.001 0.288 (29%) Combined model HSGPA, ACTc, & AG Fall GPAP<0.0010.411 (41%) *CA was not significant and not included in any models.

27. 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