Progress Report: April 21, 2015

This past week, I have been using the data I have collected in Stata to see what I could find. I made a model for estimating how many uiuc transfer students an IL community college would have, but every model had Parkland Community College as an outlier, so I made one for all schools besides Parkland. After that, I tried to create a model of IL community colleges' graduation and transfer rates based on school characteristics. My transfer model without Parkland had an Adjusted R^2 of around .85, while the school performance model had an adjusted R^2 around .60, so I was relatively happy with them.

Then I tried to use the data to check how the Engineering Pathways program effects engineering transfers to UIUC, with much less success. First, I tried to model which schools would qualify for the program, but my best model predicted less than half of the schools. This suggests that school qualification for the program is based factors other than school characteristics, perhaps state politics or personal relationships. And while Pathways schools tend to have more engineering transfers, the effect is small, averaging a little over 2 more transfers, and Pathways status has no effect on percent of engineering transfers to uiuc out of total uiuc transfers. If I were to do a section on Pathways in my final paper, it would probably reflect more on how ineffective it is.

My goal now is to start writing up my analysis in paper form, and hopefully get a rough draft within the next week or two. I'll let you know its progress in future posts.

Literature Overview and Data Set update

I have updated my data set with a variables page, it is the second one. The updated data set is here. I've started trying to use Stata to see if I can find any interesting relationships. I'll let you know how that has been going next week.

I also updated my Literature review. If you have the time, could you skim it for about 5 minutes, just to see if the format is correct. I'm worried it may sound too much like an essay, rather than a literature review. The update can be found here.

If there's anything more I should be doing, please let me know. Thanks.

Data Update

My updated data set can (hopefully) be found here. It contains all the data I used, most of it summarized on sheet 1, titled "All IL Public." All the data is from 2012. Illinois Transfer information is from the university and can be found on their website under 2012. Driving distances were found using Google Maps. Overall college data was found using College Measures. As a note, Google uses slightly different formulas, so variance and standard deviation do not show up. If you want the original copy, please comment.
I have decided to broaden my focus away from Engineering Pathways specifically and towards Illinois Community College Students overall. I want to see what makes them successful individually and specifically at getting students transferred into UIUC. My plan is to upload this data into Stata, which will hopefully make analysis easier. I will let you know how this turns out in latter posts.

Literature Overview (Draft)

Literature Review Rough Draft

The above links to a rough draft of my Literature Review. You cannot edit this one, but if you want one to edit, please email me.

Criticism would obviously be appreciated, especially on substance and formatting. Is this more or less the style you want and are there any topics I should cover more?

Thanks.

Progress Report: March 20

I think I have come up with a potential thesis topic: the UIUC Engineering Pathways program. I want to study how it is the same and/or different from the normal transfer process. I would focus on: if and how their backgrounds and pre-UIUC results differ from other transfer and native students, and try to find strengths and weaknesses of the program. Some downsides that I can see are that the university does not track transfer students differently after they arrive on campus, and potential difficulty getting data on Pathways students directly. But I think it would be useful to know how designated programs may help or hurt students.

To start I collected data from College Measures (collegemeasures.org) about the Community Colleges that are connected to the Pathways program, as well as general information about Illinois community colleges . I also found information on UIUC transfer students overall (http://www.pb.uillinois.edu/Documents/transferchars/2012/2012-Transfer-Characteristics.pdf) . Both sets of data were for 2012, and can be found summarized here.

For spring break, it intend to look more into the Engineering Pathways program: checking it's requirements, finding out how many students utilize it, etc. I will also try to find similar programs both at UIUC and other universities to compare and contrast their set up. Perhaps there has been some scholarship already on guaranteed transfer programs, so I will try to find what others have done. Finally, I want to use the data I collected to see if the chosen Community Colleges are any different from others in Illinois, and if Pathway students are any different from other transfer students.

Hopefully this is a reasonable topic for my senior thesis. Any comments would be appreciated.

Progress Report: March 1-March 7

Through my readings and interview with Joe Kulapan, I decided I wanted to do something on the topic of transfer students, especially from community colleges. I would like to see how community colleges help and/or hurt student's chances at bachelor degrees. To do this, I would need data that follows individual students from school to school. Several of the articles I have read have used the National Education Longitudinal Study: 1998-2000, which would work because it tracked students across all their schools, and could give a full picture of student's lives. I hoped that I would be able to use it, so I borrowed the data from the library. It seems, however, that either the data is only cross-sectional and does not give individual results, or I am unable to extract this individual data due to technological incompetence. Either way, it has been disheartening not being able to use that data, and I am not sure where I can find good data on this subject.

So I see my options as trying to find other data, to approach this subject from a more theoretical perspective, or to switch to some other sub-topic in graduation. Any advice would be appreciated. Thanks.

Alternative paths to college completion: Effect of attending a 2-year school on the probability of completing a 4-year degree: Jonathan Sandy, Arturo Gonzalezb, Michael Hilmer

This paper tries to find the effect of attending a 2-year college before attending a 4-year university has on Bachelor degree rates. It uses the National Longitudinal Survey, class of 1972 (NLS72); the 1994 round of the Beginning Postsecondary Study (BPS); and the 1992 round of the sophomore cohort of the High School and Beyond (HSB) as separate data sources to see if their results are consistent. It also uses Oaxaca's method to attempt to separate any potential differences between those who start at 2- year institutions and those who start at 4-year institutions by whether it is due to variations in student quality or variations in institution quality.

The most interesting part for my purposes was the analysis of the HSB data, as this was the data used by Adelman in his first toolbox study. He found transferring from a 2-year to a 4-year institution while earning more than 10 credits at both increased graduation rates. Would these researchers find the same results? They did not, in fact, they found that chances of graduating were 19.3% lower for those who attended 2-year institutions first, and that about 48% of this was due to lower student quality while about 52% was due to lower institution quality. Why the opposite results?

For Sandy, et al., mother some college, father some college, gpa above a B average, female, verbal and quantitative SAT scores, and hours worked were all significant controls. For Adelman, high school performance, having children, continuous enrollment, 1st year grades, dropping many courses first year and overall, and grade trend were all significant controls. He also found sex, whether a student worked or not, and starting at a 4-year university were insignificant, while Socioeconomic status (SES), which Sandy, et al. try to represent with parental education, was only significant at the .1 level.

Given the differences in the findings despite seeming to use the same data, it appears that one of the controls must explain the differences between these findings. In my eyes, the two major factors that Adelman accounted for that Sandy, et al. did not are the subject having a child and continuous enrollment. Between these, it seems like continuous enrollment, one of the biggest factors of Adelman's model, is the likely culprit. Perhaps 2-year students who go directly into 4-year programs have more momentum, or have lower opportunity costs, or were more motivated in the first place, or some other factor that means they are more likely to graduate than those who wait between finishing at a 2-year and attending a 4-year institution. Another potential factor is in the way transfer is described; Adelman requires at least 10 credits from each institution. Perhaps students struggle from the transition from 2-year to 4-year, and thus never complete even 10 credits from the later, still including them in Sandy, et al.'s analysis, but not Adelman's.

Either way, this shows how tangled all this data is and how seemingly similar assessments of  the same data can show wildly different results.