Posts tagged ‘economics’
Wall Street Journal just ran an article (linked below) about people “flocking to coding classes.” The lead for the story (quoted below) is a common story, but concerning. If coding is all extra-curricular, with the (presumably expensive) once-a-week tutor, then how do the average kids get access? How do the middle and lower kids get access? Hadi Partovi and Jane Margolis talked about this on PRI’s Science Friday — CS education can’t be an afterschool activity, or we’ll keep making CS a privileged activity for white boys.
Like many 10-year-olds, Nick Wald takes private lessons. His once-a-week tutor isn’t helping him with piano scales or Spanish conjugations, but teaching him how to code.
“I always liked to get apps from the app store, and I always wanted to figure out how they worked and how I could develop it like that,” Nick says.
As the ability to code, or use programming languages to build sites and apps, becomes more in demand, technical skills are no longer just for IT professionals. Children as young as 7 can take online classes in Scratch programming, while 20-somethings are filling up coding boot camps that promise to make them marketable in the tech sector. Businesses such as American Express Co. AXP -0.57% send senior executives to programs about data and computational design not so they can build websites, but so they can better manage the employees who do.
SIGCSE Preview: Measuring Demographics and Performance in Computer Science Education at a Nationwide Scale Using AP CS Data
Barbara and I are speaking Thursday 3:45-5 (with Neil Brown on his Blackbox work) in Hanover DE on our AP CS analysis paper (also previewed at a GVU Brown Bag). The full paper is available here: http://bit.ly/SIGCSE14-APCS This is a different story than the AP CS 2013 analysis that Barbara has been getting such press for. This is a bit deeper analysis on the 2006-2012 results.
Here are a couple of the figures that I think are interesting. What’s fitting into these histograms are states, and it’s the same number of bins in each histogram, so that one can compare across.
Fitting this story into the six page SIGCSE format was really tough. I wanted to make the figures bigger, and I wanted to tell more stories about the regressions we explored. I focused on the path from state wealth to exam-takers because I hadn’t seen that story in CS Ed previously (though everyone would predict that it was there), but there’s a lot more to tell about these data.
Figure 1: Histograms describing (a) the number of schools passing the audit over the population (measured in 10K), (b) number of exam-takers over the population, and (c) percentage of exam-takers who passed.
Measuring Demographics and Performance in Computer Science Education at a Nationwide Scale Using AP CS Data
Abstract: Before we can reform or improve computing education, we need to know the current state. Data on computing education are difficult to come by, since it’s not tracked in US public education systems. Most of our data are survey-based or interview-based, or are limited to a region. By using a large and nationwide quantitative data source, we can gain new insights into who is participating in computing education, where the greatest need is, and what factors explain variance between states. We used data from the Advanced Placement Computer Science A (AP CS A) exam to get a detailed view of demographics of who is taking the exam across the United States and in each state, and how they are performing on the exam. We use economic and census data to develop a more detailed view of one slice (at the end of secondary school and before university) of computer science education nationwide. We find that minority group involvement is low in AP CS A, but the variance between states in terms of exam-takers is driven by minority group involvement. We find that wealth in a state has a significant impact on exam-taking.
We’ve heard about this problem before: Online courses don’t reach the low-income students who most need them, because they don’t have access to the technology on-ramp. This was an issue in the San Jose State experiment.
That’s because the technology required for online courses isn’t always easily accessible or affordable for these students. Although the course may be cheaper than classroom-based courses, the Campaign for the Future of Higher Education argues in a report released Wednesday low-income students might still have a harder time accessing it.
“We have to wrap our heads around the fact that we can’t make assumptions that this will be so simple because everyone will just fire up their computers and do the work,” says Lillian Taiz, a professor at California State University, Los Angeles, and president of the California Faculty Association.
Many students, Taiz says, don’t have computers at home, high-speed Internet access, smart phones, or other technologies necessary to access course content.
The US News article suggests Google Chromebooks as an answer — cheap and effective. The Indian government is trying an even cheaper tablet solution. Could you use one of these to access MOOCs?
The Indian government realized a few years ago that the technology industry had no motivation to cater to the needs of the poor. With low cost devices, the volume of shipments would surely increase, but margins would erode to the point that it wasn’t worthwhile for the big players. So, India decided to design its own low-cost computer. In July 2010, the government unveiled the prototype of a $35 handheld touch-screen tablet and offered to buy 100,000 units from any vendor that would manufacture them at this price. It promised to have these to market within a year and then purchase millions more for students.
An interesting experiment, with a deeply disturbing result.
The poor often behave in less capable ways, which can further perpetuate poverty. We hypothesize that poverty directly impedes cognitive function and present two studies that test this hypothesis. First, we experimentally induced thoughts about finances and found that this reduces cognitive performance among poor but not in well-off participants. Second, we examined the cognitive function of farmers over the planting cycle. We found that the same farmer shows diminished cognitive performance before harvest, when poor, as compared with after harvest, when rich. This cannot be explained by differences in time available, nutrition, or work effort. Nor can it be explained with stress: Although farmers do show more stress before harvest, that does not account for diminished cognitive performance. Instead, it appears that poverty itself reduces cognitive capacity. We suggest that this is because poverty-related concerns consume mental resources, leaving less for other tasks. These data provide a previously unexamined perspective and help explain a spectrum of behaviors among the poor. We discuss some implications for poverty policy.
The Washington Post series on “The Tuition is Too Damn High” has been fascinating, filled with interesting data, useful insights, and economic theory that I hadn’t met previously. The article linked below is about “Baumol’s cost disease” which suggests an explanation for why wages might increase when productivity does not. It’s an explanation that some have used to explain the rise in tuition, which Post blogger Dylan Matthews rejects based on the data (in short: faculty salaries aren’t really rising — the increase in tuition is due to other factors).
But I actually had a concern about an earlier stage in his argument. It’s absolutely true that our labor intensive methods do not lead to an increase in productivity in terms of number of students, while MOOCs and similar other methods can. However, we can gain productivity in terms of quality of learning and retention. We absolutely have teaching methods, well-supported with research, that lead to better learning and more retention — we can get students to complete more classes with better understanding. In the end, isn’t THAT what we should be measuring as productivity of an educational enterprise, not “millions of customers served” (even if they don’t complete and don’t learn)?
Performing a string quartet will always require two violinists, a violist and a cellist. You can’t magically produce the same piece with just two people. Higher education, for at least the past few millennia, has seemed to fall in this category as well. “What just happened in my classroom is not very different from what happened in Plato’s academy,” quips Archibald. We’ve gotten better at auditorium-building, perhaps, but lecturers generally haven’t gotten more productive.
I’m interested in the discussions about corporate involvement in higher education, but am still trying to understand all the issues (e.g., who has a bigger stake and greater responsibility for higher education, industry or government). The point made below is one that I have definite opinions about. If we’re trying to improve higher education, why not try to make it more effective rather than just lower cost? I disagree with the below that we have to have 16:1 student:teacher ratios to have effective learning. We can increase those student numbers, with good pedagogy, to still get good learning — if we really do focus on good learning. Why is all the focus on getting rid of the faculty? Reducing the labor costs by simply removing the labor is unlikely to produce a good product.
There is a lot wrong in this apples to oranges comparison, but the point is obvious—cutting labor costs is the path to “education reform,” not research and improved pedagogy. This is “reform” we need to reject when applied to public education. I say this without reservation: when it comes to education, you pay for what is most effective. Period. If small class sizes produce better teaching and learning, then that’s what you support when appropriate. Whatever your approach, stop conflating economic restructuring and education reform; it’s dishonest.
Semester Online sounded like a nice idea — getting liberal arts focused institutions to share their online course offerings. The pushback is interesting and reflects some of the issues that have been raised about sustainability of online education as a replacement for face-to-face learning or even as an additional resource.
While Dr. Lange saw the consortium as expanding the courses available to Duke students, some faculty members worried that the long-term effect might be for the university to offer fewer courses — and hire fewer professors. Others said there had been inadequate consultation with the faculty.
When 2U, the online education platform that would host the classes, announced Semester Online last year, it named 10 participants, including Duke, the University of Rochester, Vanderbilt and Wake Forest — none of which will be offering courses this fall. “Schools had to go through their processes to determine how they were going to participate,” said Chance Patterson, a 2U spokesman, “and some decided to wait or go in another direction.”