Orbiters is now in its 3rd incarnation. It’s gone through many changes since December — here’s a short account of some of the design challenges and solutions that have shaped those changes.
I’m taking calculus for the first time right now, and it’s got me thinking about math learning a lot, especially how to build intuition for math concepts and see them as tools for problem-solving in the real world.
As a grade school student, I always liked word problems in math class, for two reasons:
- There’s a heuristic pleasure in reading a passage and figuring out the math problem hidden in it. This is much more interesting to me than just getting the math problem by itself.
- There’s considerably less math per character in a word problem than in a block of equations. Since I suffered from fear of math in school, this was a big plus for me.
Part III: Strategies
In Part II, we continued to look at data about students in higher education and what they choose to study; we saw that, although the overall student population for all of higher education became more similar from 2002 to 2012 to the overall national population of 18-24 year-olds, student populations in engineering programs are not following the same trend.
In this section, we’ll look at two programs trying to address and remedy representational disparities in STEM fields. Though one targets K-12 students and the other post-baccalaureates, both identify similar sources for, and solutions to, the diversity problem in STEM education.
If you missed Part I of this series, find it here.
Part II: Trends
In Part I, we looked at some numbers: majors and graduates in US four-year institutions in and out of STEM fields. Those data gave us an overview of the state of STEM education in 2012 – who’s pursuing it (mostly men, to varying degrees depending on race and ethnicity) and who isn’t (mostly women across all race and ethnicity groups).
In this segment, we have two objectives. First, I’d like to provide a little more context for the discussion by looking at the value of STEM versus non-STEM degrees for the graduates who hold them. Then, we’ll look at data on higher education in the US from 2002 and 2012 to set up a longer perspective on how disparities have been changing (if indeed they have). In our efforts to make college more accessible to all Americans, have we been making progress? And when we look at STEM in particular, do we see similar patterns? Or are disparities in STEM widening when compared to higher education as a whole? Continue reading
Our economy needs STEM skills.
Not only does it need STEM skills, but it rewards people who have them – significantly more than those who don’t.
As educators, we have two major responsibilities on the STEM front:
- Create STEM exposure opportunities for students who might lack access, and
- Make those opportunities as rich and engaging as possible.
Determining how to do those things successfully and on a large scale (and not just on a case-by case basis) requires looking at some large-scale data – some of which we have, and some of which we don’t.
This multi-part series will look at some of the data we have, some of the problems those data suggest, some solutions currently in use and development, and where to look to answer our next questions.
Part I: The State of STEM
For reference, in 2012 the US resident population of 18-24 years old was 63% white, 5% Asian and Pacific Islander, 12% black, 17% Hispanic or Latino, less than 1% (0.7%) Native American/Alaskan Native, and 2% mixed-race (non-Hispanic). [Note: to my knowledge, all race and ethnicity data is self-reported, and Hispanic/Latino may refer to any race. Some citizens identify as more than one race or ethnicity, and percentages may not add up to 100 in all data sets.] Data used for the charts in this section comes from the NSF, and is freely available here. (Thanks, NSF!)
The 4-year college and university population in 2012 looked like this: Continue reading