I’ve been waiting to share the news with a wider audience. I have started a new role as Director of Analytics for the City of Chicago. Chicago has a ridicuously strong and wide-ranging open-data community, with strong support from the mayor to a group of volunteers who meet weekly to hack on city data. Instead of being a volunteer myself, I will be working with many of the sample people in a new capacity.
I am tremendously excited to enter this new role and am very lucky. Government, research, and policy have been in my interests for a long time. I am lucky to be working during this exciting phase where governmental bodies are using data and research to improve the quality of life for citizens, increase transparency, and improve services.
So, this blog has been quiet lately, but I hope to post small bits of analysis on Chicago throughout my daily work. Hopefully I can dedicate more time to write on the behind-the-scenes of creating data visualizations and analysis.
This past June the National Labor Relations Board (NLRB) sought written opinions on whether the board should reconsider the Brown University case which prohibited unionization at private universities. The request was only surprising in that it came so late in the President Obama’s administration, caused by the Senate Republicans stubborn refusal to nominate NLRB members. But it only delayed the inevitable, that students will be able to unionize at private universities.
How does a community college major relate to the eventual industry of employment? Now you can interact and explore the relationship between Iowa community college students and their eventual employment sector or your computer or mobile device. This is an update to a static poster I developed a couple of years ago.
There is good reason to explore data like this, both in Iowa and nationally. Education is a pathway which leads to a variety of outcomes, but arguably, career-oriented majors should lead to employment in a related sector. For the employers sake, they would probably like to hire their workers from training programs. Read more…
I was invited to give a brief talk to the urology department at Northwestern University on data visualization. Recently, you see, many of the residents presented posters at large conferences. When it was time to create posters and graphs, many of them begun to ask: “does this look OK? What can I do to make it clearer?” This presentation discusses some practical approaches to creating data visualizations. The emphasis is on medical applications, but the provided examples can easily work in other circumstances.
Before leaving the Iowa Department of Education, I had the pleasure of working with Andrew Ryder on his dissertation, which studied the pathway from the GED to community college in Iowa.
Andrew spent a considerable amount of time looking for a dissertation topic. After some serious contemplation and some dead-ends, he eventually settled on the GED. He had some personal ties to the GED as his brother earned a GED before obtaining a job as an electrician. It was also relevant to current policy, where Iowa–following an initiative by Obama–adopted a goal of dramatically increasing the number of community college degrees over the next decade. Since Iowa already has relatively high educational attainment, a serious question is where these graduates going to come from. The GED program is a viable pathway, but unfortunately, the results were not good:
Among 11,675 Iowa high school dropouts who enrolled in the General Education Development (GED) preparation program during the 2003-04 fiscal year, fewer than a third (31.5 percent or 3,680) earned a GED by the end of the 2009 fiscal year. Just 12.9 percent of them (1,504) went on to enroll in community college, and only 2 percent (229) completed a community college credential by the end of June 2010.
Though, this may not be surprising. Prior research has suggested that the benefits of the GED are largely sheepskin. That is, the paper is providing the benefit, not necessarily the skills learned in the GED. For employers, the GED is a signal of the employees characteristics, even though that may not be the case. Behind the GED diploma, however, are people who usually have more noncognitive skills than other high school dropouts. However, there is not a large cognitive gain as a result of GED courses. Afterall, the median time to earn a GED is a little over 20 hours–how much can one really learn in that time?
The GED is not particularly strong on mathematics. The mathematics portion plateaus at geometry; hardly the rigor that college faculty are expecting from students. A newly revised GED test will, hopefully, fix those issues. From a policy perspective, the high school drop-out population is a prime target to upgrading the human capital in the United States. Unfortunately, the GED is largely ignored in contemporary education policy.
Oh, and the recently minted Doctor Ryder won the Council for the Study of Community Colleges’ “dissertation of the year” for this study. He produced the excellent graphic shown above, which highlights the excellent job he did. Careful, sometimes complex, analysis (survival analysis), applied to a pertinent policy question, with careful consideration on easily communicating the results through a single graphic.
The website is going to be changing domains this weekend. I’ll be moving to Dreamhost and away from WordPress.com. I will be making the move in order to accommodate some exciting new projects for the website. But, as these things go, there may be some service interruptions. Everything should be ready by Sunday, June 3rd.
My R interface has been pretty basic in the last few years. I have usually stuck to the R console. Yes, I’ve tried Emacs with ESS; a staple, but it is so unbearably antiquated that I always gave up on its significant learning curve. GUI packages–especially Rstudio–offer viable alternatives, but I feel the GUI lets me lose focus of the code. I have been envious of TextMate for Mac, but alas, I’m not a Mac user. Recently, though, I’ve moved to Sublime Text 2. With some nudging, I have been able to mimic the typical R console environment in the more-powerful Sublime Text program.
Education scholar, Gary Rhoads, was the lead author on a report released by Center for the Future of Higher Education, an organization that Dr. Rhoads leads. The main thrust is the troubling decline in community college funding and it’s impact on student access. Specifically, that the reducing the budget has put caps on programs and created a conflict with the community college “open admissions” policies. However, in attempting to argue this, the report makes an odd claim: “Enrollment in community colleges across the country is plateauing and declining despite rising student demand.”
I agree with the thesis, but not the logic. Dr. Rhoads attempts to tie the recent enrollment declines to limited budgets. “Enrollment in community colleges across the country is plateauing and declining,” he argues, “despite rising student demand.” Dr. Rhoads seems insistent on this latter part, but here is where I get lost. Although demand is much higher than 5 years ago, many states have had declining enrollments since two years ago.
Starting a project where you need to make a series of graphs or a visualization can be frustrating. One of the hardest tasks is to find a theme, a style which you want to use. Though minimalism is the dominate “style” in data visualization, there is a lot of approaches to any graphical approaches. So I’ve started a blog, Data Nouveau, to browse sources of influence for data projects.
It will mostly include graphs and data visualizations, but will also use other sources–such as art and movies–for ideas, such as color palette. Essentially, I hope it will serve as a sort of free style magazine for those starting new projects. I’m also accepting submissions of any interactive, static graphing style, data visualization project, or anything that might help someone choose a color palette, graphing style, or layout for their own project.
My new publication in November’s IR Applications, which is published by the Association for Institutional Research:
This paper explores the relationship between student major and industry of employment and its application to higher education accountability. Data provided by statewide longitudinal data systems (SLDS) have enabled state educational agencies and colleges to follow students into the workforce. While most studies have focused on wage outcomes, this study shows how to use SLDS data to understand the correlation between major and industry. The transition into the workforce is an important outcome since it is an assessment of a college’s ability to develop specific, targeted sectors of the economy. We use SLDS data from Iowa to follow community college alumni from 2002 through 2008.
Find it here.