Below is an extended example of how retention data on students with disabilities can be used. First, such data can capture longitudinal trends in relation to students without disabilities and identify possible red flags in climate. It can also reveal the need for deeper analyses into what may be affecting retention rates. What looks like a trend occurring over a four-year period or more may be able to be explained, at least in part, by breaking down retention into subcomponent years or even specific academic periods. With retention, the global trends are only one part of the equation and are rarely the complete answer. Effective use of retention data allows for the ability to dissect trends into markers where trends began to emerge, shift, or change. These kinds of time-specific markers can be just as important to identifying and solving problems in climate as the longitudinal trends themselves.
Example: TRU
At Tabula Rasa University (TRU), the Office of Enrollment Management generates enrollment and retention figures each semester for the following groups: African American, Hispanic, Asian, Native American, Caucasian, Male, Female, and Students with Disabilities. This automated data run is based on having a group membership entered in the central record system. For students with disabilities, the Disability Support Services (DSS) office has system clearance to enter the category of disability and whether a student receives priority registration as an accommodation. The registrar and the DSS office have access to the information, but it does not appear on the general information and advising screens.
Like the temperature light on a dashboard, each year the office looks at the retention rate for students with disabilities in comparison to all other students. The rate gives them a quick indicator for campus climate. Here is an example of the data they received in the autumn of 2004:
Table 1: FULL-TIME FIRST-TIME AUTUMN 2004 SEMESTER ADMITS*
| Cumulative Persistence Rate** | |||
|---|---|---|---|
Entering Year |
(Years out) |
Without Disabilities |
With Disabilities*** |
1998 |
(6) |
59.3% |
89.3% |
1999 |
(5) |
60.1% |
77.7% |
2000 |
(4) |
62.9% |
75.7% |
2001 |
(3) |
68.4% |
75.0% |
2002 |
(2) |
72.0% |
70.7% |
2003 |
(1) |
84.1% |
83.3% |
*Full-Time First-Time Autumn Admits is the typical group used in tracking retention and performance nationally.
**Cumulative Persistence Rate is the percent of students who are currently enrolled or have graduated from that cohort.
***With Disabilities refers to students who have self-identified as having a disability and who have submitted documentation of a disability to DSS.
The Director of DSS is reviewing this data and notices that the persistence rate for students with disabilities seems to be falling behind in comparison to other students and starts wondering why. Looking closely at the table, the Director sees that the persistence rate for students without disabilities falls for cohorts that have been at the university longer, while the rate for students with disabilities seems to do the opposite. What conclusions might the Director draw?
Three viable possibilities occur to the Director:
- More students with disabilities stop out (take time off and then return to college)
- Changes to policies over time have improved the more recent retention rates of students without disabilities and have negatively impacted students with disabilities.
- With increasing numbers of students with disabilities attending college, they now reflect a range of motivation and preparation for college that is similar to students without disabilities.
The Director knows that the basic cohort persistence data in this table is a global snapshot without the necessary resolution to provide a sufficient explanation of the variability in trends. The Director also knows that research suggests that a student’s first year experience is critical to understanding retention. Therefore, to demystify the puzzle of trend data, the director asks the Office of Enrollment Management for the first-year retention rate on each of the six cohorts:
Table 2: FULL-TIME FIRST-TIME AUTUMN QUARTER ADMITS*
| First Year Retention Rate** | ||
|---|---|---|
Entering Year |
Without Disabilities |
With Disabilities*** |
1998 |
75.7% |
98.1% |
1999 |
79.0% |
92.4% |
2000 |
79.1% |
89.6% |
2001 |
81.1% |
87.5% |
2002 |
82.8% |
84.8% |
2003 |
84.1% |
83.3% |
*Full-Time First-Time Admits is the typical group used in tracking retention and performance nationally.
**First-Year Retention Rate is the percent of students retained from each cohort at the end of the first year of enrollment.
***With Disabilities refers to students who have self-identified as having a disability and who have submitted documentation of a disability to DSS.
This table of first-year retention rates provides the Director trends for students with and without disabilities that can be compared. Across the six years in question, the first-year retention rate for students without disabilities has risen by 8.4% while it has declined by 14.8% for students with disabilities. These trends strongly suggest that some change or a combination of changes over the six years in question have had a positive impact on students without disabilities and a negative impact on students with disabilities. Since research indicates that changes in first-year retention rates account for nearly all the changes in cumulative retention rates, the Director can now focus specifically on the first-year experiences of students.
There are several ways to identify the influences on the declining retention of students with disabilities. It would be useful to look at the demographics. Has the level of high school preparation (e.g., SAT, GPA, Class Rank), the freshman experience profile (e.g., residential status, choices of majors, credit loads and financial status) or the disability profile (e.g., proportion of students with learning disabilities, psychological disabilities, mobility disabilities, etc.) changed for more recent-entering cohorts? Is the profile of retained and attrited students similar? This type of data may be most effective when examined in conjunction with formal climate assessment instruments or focus groups so that a more complete picture of student experience is attained.
If after conducting a retention analysis, it appears that interviewing or surveying is needed, a person may be asking, “why not just rely on survey and interview data in the first place?”
Some reasons why not:
- A person or a group of persons at an institution can automate retention and performance data collection to create critically important dashboard indicators of the campus climate for students with disabilities. Automating data collection allows for the more efficient and focused uses of time and labor-intensive techniques such as focus groups or interviews.
- The use of quantitative or outcome data provides a guide to new questions institutional personnel may want to ask.
- Administrators, funding agencies, and state legislatures are increasingly interested in outcome measures, in particular performance and retention. As noted earlier, the higher education community is not shielded from the national movement towards greater accountability.
