GothamSchools — daily independent reporting on NYC public schools

guest perspective

Lengthy Commutes and Academic Progress

Students at my school who travel long distances come to school less often, I concluded earlier this month. But what does their commute mean for their academic achievement?

In the second phase of my study, I examined how the length of a student’s commute relates to his academic progress. Again, I looked only at the self-contained special education students at my school, Columbus High School in the Bronx, and I used credit accumulation as the tool to measure progress. My results show that the negative impact of a long commute on attendance is magnified when looking at credit accumulation.

Here’s the bottom line:

picture-40

Having looked at these numbers and through the raw student data, I noticed that for the students traveling farther to school there was a subset of students outperforming others — the students taking work-study programs or internships. Among the 180 self-contained I students studied, 28 participate in one of three vocational programs. These students often seemed to be able to beat the relationship between the commute, attendance and credit accumulation.

picture-411

Of these 28 students, three take the yellow bus, three live close to school, eight are in the 15-29 minute range, and the remaining 14 live 30 minutes or more from school.

Here are the same results depicted another way:

picture-42

One of my most troubling findings is that even accounting for the commute and participation in special programs, the farther students live from the school the more slowly they accumulate credit.

As I began to notice this phenomenon I frequently went a step further in ARIS, the city’s school data system, and checked out the students’ test scores. Anecdotally (I have not formally measured this yet), the students with the longest commutes appear to be at increased risk of having scored at level 1, or far below grade level, in all subjects in which they were tested in the lower grades and of having made little or no academic progress in the middle grades. I plan to test this hypothesis more thoroughly.

The reality is that most students coming longer distances to Columbus are coming from further south in the Bronx, where poverty increases. I can’t help wondering whether students from this area experience greater challenges in general, or whether those who are most challenged in those neighborhoods are not being sent to local schools for some reason. There are no longer any zoned high schools in the South Bronx. Of the schools there, many do not provide small, self-contained special education classes. Those schools that do provide such classes are serving considerable percentages of students — particularly those schools that are larger in size and are have both 15:1 and 12:1:1 classes to the students whose special education plans indicate that these class sizes will best meet their needs.

I cannot help but think about what my findings might say about Columbus’s progress report. Last year high schools received an extra credit point on their progress reports if at least 45.7 percent of all special education students earned more than 11 credits in the year. They got two extra points if 56.3 percent of students or more earned that many credits. I couldn’t help but observe that (had the fall’s credit accumulation trend carried through to the spring) if Columbus had been judged on our yellow bus, local and vocational students, we would receive two extra points for outstanding credit accumulation for this group of students — but with the more distant students included, Columbus received no bonus points in closing the achievement gap for special education students. But if commute distance for this group is as significant as it appears to be, is this the school’s fault?

Once again, I recognize that this is a small study of just one set of students at one school. A project of much larger scope would be needed to reveal whether these relationships exist across a broad spectrum of New York City schools. This study does, however, suggest several possibilities for raising attendance and improving outcomes for self-contained students — neighborhood schools, the school bus, and vocational programs.

  • the solution?

    Brilliant! I applaud your efforts and this inquiry. Great piece of work.

  • http://nyceducator.com NYC Educator

    Great work. It’s funny things can be so simple and yet elude Joel Klein, Bill Gates, Arne Duncan, and all the hedge fund managers who run education in the United States.

  • Peter

    Christine: Well done! I suspect if we explored credit accumulation by student residence zip code we would find a similar pattern. Also if we could match scanning wait time with credit accumulation we’d find the same pattern.

    In too many schools first period classes are poorly attended, frequently due to long travel times and lengthy waits at scanning.

  • EFM

    According to your data the vocational students beat the correlation between distance, attendance and credit accumulation. Could this be due to increased motivation on the students’ part ? If so, offering a wider range of vocational programs, rather than focusing so intently on performance in academic programs, may offer a better solution for teenagers at risk of dropping out.

  • Christine Rowland

    I’m having trouble deciding what to focus on next. Should I investigate this particular group more deeply, or see if the same patterns exist for other vulnerable subgroups of students or the school population as a whole? With this project, the more I learn the more questions I have.
    Peter’s idea of using zip codes is a speedy way to do things and may make the project easier for an educator in another school to replicate.

  • Christine Rowland

    EFM – point well taken on work study/vocational programs. I’ve thought about writing on this topic since the hard data alone misses many of the critical issues around matching students with prorgams that are good fits for them. We are fortunate enough to be able to place students at The Hebrew Home for the Aged, in child care facilities and with the Co-op Tech program. The Hebrew Home is notable for having employed a number of our students after they graduate – even with IEP diplomas. Those former students may have long commutes to work, but they deeply appreciate their jobs (which come with benefits), and the residents and staff at the Hebrew Home appreciate them too.

  • Matthew

    Christine,

    Bravo for the effort.

    One challenge you face in assessing the implications of your findings is whether this is a case of correlation or causation.  A common problem in statistical analysis, so I don’t mean to criticize you for any failings.   

    Children who live further from your school could have weaker family supports, could come from poorer families, could have lower scores and skills coming into your school. A whole host of reasons that might explain the difference.  

    So I think you need to look at a multi-variable regression to tease out what it is about these kids that makes it harder from them.  It may very well be the commuting time.  But it’s hard to conclude that definitively, based on the data you have presented so far.

    Keep up the good work.

    Matthew

  • Christine Rowland

    Thanks Matthew. At this point I can only show correlation based on the data. To find causation I’d need a lot more evidence (and probably a larger study). It would also be interesting to look at students who have to take more than one train or bus. It is probable that the lengthier commutes involve issues around train service – I’m not sure how much time if any hopstop builds in for service disruptions. This could account for tardiness that could contribute to loss of credit in a student’s first class of the day.

    As mentioned in the article, socio-economic issues likely bear a role on the findings. My challenge is how to measure that factor. Any thoughts?

Tips, questions, feedback?

Contact us at .

Word from Our Sponsor

Follow GothamSchools

RSS
Subscribe to the daily email digest:

Chalk It Up

Recent Comments

10 comments so far today

Events Calendar

Archives

May 2013
M T W T F S S
« Apr  
 12345
6789101112
13141516171819
20212223242526
2728293031