Student Retention at
Community Colleges
An Exercise in Data
Visualization
America's community colleges play an essential role in preparing people
for the jobs of the twenty-first century. Students, young and old, come
to community colleges for courses in a remarkable array of subjects.
They can gain basic skills in math and reading, take college level
courses in calculus and chemistry, learn job-related requirements in
auto repair, welding, nursing, and many other subjects. Faculty and
adminitrators are continually working to improve the prospects for
retention and progression of the many students who are lacking in basic
skills, pressed by the responsibilities of work and supporting
families, and otherwise at jeopardy for dropping out.
The Community College Research Center (CCRC)
at Columbia University Teachers College has been one of the centers for quantitative research
in community college retention studies. They have issued a series of
CCRC Briefs, one of which is the subject for this page's exercise in
data visualization. Brief 45,
Student Progression Through Developmental
Sequences in Community Colleges, dated September 2010
and referred to herein as CCRC 45, is a particularly useful
meta-study. CCRC 45 presents several tables, well laid out but
challenging to understand. I saw this as an opportunity to use on of my
favorite programming languages, Python, to quickly develop helpful
interpretive visualization.
Here is the data from Table 1 of CCRC 45:
Table 1: Enrollment in and Completion of Developmental Sequences
Math
| Developmental
Courses |
Never Enrolled |
Enrolled -
Lost |
Enrolled -
Failed or Withdrew |
Completed
Sequence |
Total (N) |
Total (%) |
| 1 level Below |
37% |
2% |
17% |
45% |
56,551 |
42% |
| 2 levels below |
24% |
13% |
32% |
32% |
38,153 |
27% |
| 3+ levels
below |
17% |
23% |
44% |
17% |
43,886 |
31% |
| Total |
27% |
11% |
29% |
33% |
141,590 |
100% |
Reading
| Developmental
Courses |
Never Enrolled |
Enrolled -
Lost |
Enrolled -
Failed or Withdrew |
Completed
Sequence |
Total (N) |
Total (%) |
| 1 level Below |
33% |
5% |
12% |
50% |
5,341 |
69% |
| 2 levels below |
21% |
13% |
24% |
42% |
16,983 |
32% |
| 3+ levels
below |
27% |
19% |
25% |
29% |
8,825 |
9% |
| Total |
30% |
8% |
16% |
46% |
78,149 |
100% |
Personally, I find it difficult to compare and contrast using these two
tables. I hope you will find the two graphics below to be of assistance
in understanding Table 1. They are built for information, not for beauty.
Math:
Reading:
The Python program for generating these two graphics can be found here. It is written in the spirit of Python, that it is able to do simply whatever it can do.
You can reach me at my hotmail dot com account: cassiodorus
last update 24Mar2012
