Report of Achieving the Dream Data Team

1. Report of Achieving the DreamData Team October 10, 2007

2. Contents • Methodology • Developmental Courses with Observations • High Enrollment, High Failure Courses with Observations • High Failure 2000-level Courses with Observations • Advisement • Persistence and Retention with Observations • Next Steps

3. Methodology • Achieving the Dream (AtD) defines student success in a course as a grade of A, B, C, or S; students earning a grade of D, F, U or W are defined as unsuccessful. • Initially, five Zero-level courses and five 1000-level course were identified as having a high rate of unsuccessful students and were analyzed using demographic data. • With guidance from our AtD Data Coach, the analysis shifted from demographics to other course attributes where change might have a broader impact. • Time of day • Length of course • Delivery method

4. Methodology • All Zero-level MATH and LS courses were selected since unsuccessful completion of these courses is a barrier to enrollment in college level courses. • 1000-level courses were selected by high enrollment (300 or greater) and high failure rates (30% or greater). • 2000-level courses were selected by high enrollment (100 or greater) and high failure rates (30% or greater) • All persistence and retention data is based on the ATD cohort, which includes all students who enter OCCC for the first-time in the fall semester. • AtD Data Team surfaced summary observations during meetings.

5. Developmental or Zero–Level Courses • All Zero-level MATH and LS courses were selected. • Larger percentage of students receive a D, F, or U than withdraw. • Online sections are less successful than traditional sections. • 8-week sections are more successful than 16-week. • The failure rate for College Reading I has increased over the last three years. • Night sections in Math courses are more successful than other times of the day. • Study Skills has a consistently higher failure rate in spring semesters. • Intermediate Algebra has a consistently higher failure rate in fall semester.

6. Developmental Failure Rates By Year

7. High-Enrollment, High-Failure Courses • 1000-level courses were selected by high enrollment (300 or greater) and high failure rates (30% or greater). • Math and Science courses had a greater percentage withdrawing than failing. English and History courses were the reverse. • When offered, 2-, 5-, and 8-week sections had a lower failure rate than 16-week sections. (Exceptions: CS 1103, Math 1513) • When offered, online sections had a higher failure rate than traditional sections. (Exceptions: BIO 1023, BIO 1114, SOC 1113). • Telecourse sections had a higher failure rate than any other delivery method.

8. High-Enrollment, High-Failure Courses • Failure rates in night sections are equal to or lower than morning sections. (Exceptions: MATH 1513, CHEM 1115). • The following courses show a continued increase in failure rate over time: APPM 1313, BIO 1314,CHEM 1115, ENGL 1113, HIST 1483, and HIST 1493. • Courses that have consistently lower failure rates in fall semesters: BIO 1114, BIO 1314, ENGL 1113. • ENGL 1213 has a consistently lower failure rate in spring semesters. • Courses that have increased in number of students per semester: BIO 1023, BIO 1314, POLSC 1113. • CS 1103 is the only course that has continued to decrease in number of students per semester.

9. High-Enrollment, High-Failure By Year

10. 2000 Level Courses • 2000-level courses were selected by high enrollment (100 or greater) and high failure rates (30% or greater) • According to AtD Data Coach, high failure rates in 2000 level courses are unusual for AtD schools. • Most 2000-level courses had a higher withdrawal rate than failure rate (Exceptions: ECON 2113, MGMT 2053). • Night sections had a lower failure rate than other times of the day. • When offered, 5- and 8-week sections had lower failure rates than 16-week sections. • When offered, online sections had noticeably higher failure rates than traditional sections. (Exception: GEOG 2603)

11. 2000 Level Courses • Five out of nine courses show an increase in the failure rate over time (Exceptions: ACCT-2123; ACCT 2113; COM-2213; MGMT-2053). • BUS 2023 has consistently lower failure rates in spring semesters. • GEOG 2603 has consistently lower failure rates in fall semesters. • One out of every two students who enroll in ACCT 2113 and BIO-2215 fail.

12. 2000 Level Failure Rates By Year

13. Advisement Why Advisement • Identified as key piece of student success • Opportunity to talk one-on-one with a student • Advising is both formal and informal • Advising is multi-faceted

14. Advisement OCCC DUAL MODEL OF ADVISEMENT • OCCC Administrative Procedure No. 5049 dtd 1-02-1991 • OCCC Administrative Procedure No. 5056 dtd 6-01-1996 • Advantages • Trained staff; central access; economy of scale • Disadvantages • Unclear definition of advising • Communication of responsibilities

15. Advisement

16. Advisement Areas of Concern • Communication – internal and external • Roles and procedures not clearly defined • Training for Faculty Advisors • Transition from Academic Advisor to Faculty Advisor • Self-Advisement • Loophole

17. Persistence and Retention • Fall 2004 and Fall 2005 AtD Cohorts, which includes all students who enter OCCC for the first-time in the fall semester. • Persistence is defined as a student from a fall cohort attending the following spring semester. (Fall to Spring) • Retention is defined as a student from a fall cohort attending OCCC the following fall semester. (Fall to Fall) • Looking at the demographic profile of the two AtD Cohorts in comparison to all students enrolled at OCCC’s during the same time frame, the following differences can be seen: • AtD Cohorts have a higher percentage of males. • AtD Cohorts have a higher percentage of 18-24 year olds. • AtD Cohorts have a higher percentage in all race/ethnic groups except Asian.

18. Females persisted and were retained at a higher percentage than males. • Asian and Hispanics persist and are retained at a higher rate than other minority groups or Caucasians. • Black/African Americans have a lower success rate than other minority groups or Caucasians. • Asians have a higher success rate than other minority groups or Caucasians. • Minority groups as a whole persist and are retained at a lower rate than Caucasians. This is more evident in the Fall 2005 Cohort.

19. Both persistence and retention declined from Fall 2004 Cohort to Fall 2005 Cohort in basically all areas. (Exception: 30-34 age group) • Although the persistence percent of 30-34 year olds decreased from Fall 2004 to Fall 2005, the retention rate increased. • The opposite was true for 40-44 year olds. • A student in the Fall 2004 Cohort had approximately: • three in five chance of persisting • one in two chance of being successful in spring classes • almost a two in five chance of being retained • less than a one in three chance of being successful in fall classes

20. Fall to Fall Retention

21. Retention Demographics

22. Breakout Group Process • Divide into three breakout groups. (see sheets on tables. ) • Each group should appoint a presenter and recorder. The recorder will list items in the laptop provided. • The tasks for each group are as follows: • Table 1 should brainstorm potential causes of the problems shown by the data about developmental course completion from the Data Team as well as any other data that may be relevant on developmental course failures. • Table 2 should brainstorm potential causes of the problems shown by the data about course completion in 1000-level (gatekeeper courses) and 2000-level courses from the Data Team as well as any other data that may be relevant on course completion failures. • Table 3 should brainstorm potential causes of the problems shown by the data about persistence and retention from the Data Team as well as any other data that may be relevant on retention failures. • Once you have brainstormed the list of issues or potential causes, separate them into Symptoms or Underlying Causes by adding a “S” or “U” next to the item. • Each group should then list any additional data they would like to see from the Data Team that would assist in analyzing their assigned subjects. • Save the list on the flash drive provided and each presenter will have five minutes to present to the combined group.

23. AtD Data Team Members • Alan Stringfellow • Brandi Henson • E.J. Warren • Harold Case • Joyce Morgan-Dees • Stephen Crynes • Yutika Kim

24. AtD Data Team Members LINKS • 2004 Cohort • 2005 Cohort • Zero Level • 1000 Level • 2000 Level