As an economist by training, data has always interested me. Today, getting a decent dataset with a few million records is pretty easy. It wasn't always that way, though - I still remember how for many of my colleagues at university, their choice of thesis was actually guided by what data was available and not where their interests laid!
I firmly believe that we, as a society, need to develop our numeracy skills. Regardless of what industry you're in, knowledge has advanced to a point where it's hard to truly innovate without some grounding in mathematics. The amazing thing is that it doesn't matter where you look, maths has a role to play everywhere: sequencing the genome, more effectively managing credit, high-velocity trading, customer engagement, even resource management within the public sector!
These applications require real skills. And, while those skills take time to develop, we seem to do a depressingly effective job in turning students off on maths. Where I think we let them down is in making it relevant - it took me a good decade after I learned calculus in high school to realise the practical applications. It wasn't until I was trying to benchmark the net utility created by two different policy approaches that everything clicked. Measuring the area under the curve moved away from being an abstract concept to something that actually meant something.
It's for that reason I was so happy to hear Keitha Booth from Land Information NZ talk about how the New Zealand government is making a large effort to join the open data initiative. With my private sector hat on, her point that leveraging this data can allow companies to innovate really resonated with me. With my personal hat on though, I think it's even cooler - it makes it easier for non-mathematicians to see the power of information. It's hard not play around with the LINZ Data Service without getting alternatively interested and excited!
The greatest thing is that there's so much out there. Regardless of whether you want to play around with data from New Zealand, Australia, the UK, or the world, there's insights everywhere. Numbers aren't just abstract concepts - they model reality. What better way to make mathematics relevant to a future generation of kids than to give them the ability to interactively explore the world they live in?
Roughly a year ago, Bruce Friend, Director of SAS Curriculum Pathways, participated on a technology advisory team at a school in Raleigh, North Carolina: a place he described as a "technology-rich environment" that was not being maximized by teachers. During a lunchtime forum, he remembered one student pulling out his smartphone and asking a group of teachers to identify it.
It was a moment in which Bruce realized that schools cannot deliver the same instruction taught five, 10, 15 or 50 years ago. He shared the story in a keynote address at the Summer Technology Institute for Educators, at North Carolina Central University in Durham, North Carolina.
Continue reading "Why technology in education is important "
What does the quantum theory of football have to do with a blog about learning SAS? Well, everyone around here is abuzz about Change the Equation and STEM (if you don’t know what this is, check it out and come back to me. It’s OK, I’ll wait for you.) Here is SAS’ contribution to their video contest:
The winner of the viral video contest is also in a quantum state of uncertainty until the contest ends and the winner is announced.
The SAS Training Post writers and all of the Education Division at SAS have reasons to be interested in motivating the next generation to study STEM—after all, they’re our future users!
But my interest in this topic goes further than that of a SAS instructor. The state of education is often on my mind as I consider the future my 1- and 4-year old knee-gnawers can look forward to. Schroediner’s quarterback aside, one thing that is certain: learning does not end with the school day. A well-rounded continuing education at home is part of the solution to the problem of lagging in math and science.
Last week, Michele Reister asked me to blog about how I ended up with a career in statistics. It’s certainly not where I thought I’d end up, trying to pick a major among theatre arts, psychology, English, physics, and computer science. There were dozens of influences that led ultimately to here and now, but one that makes my point about education is this: As strange as it is, I ended up in statistics partly thanks to William Shakespeare. Iambic pentameter fed a love for how numbers and patterns play into everyday life that later bloomed with academic research in human behavior. Sometimes I’d miss the whole point of a sonnet because the grammatical gymnastics producing the rhythm were so gorgeously executed. I wasn’t a very good actor, but I love a play on numbers.
Another influence was my freshman semester statistics professor at (what is now called) Texas State University. She nurtured our interest in statistics, focusing on the theoretical and applied aspects of statistics rather than on the calculations. We never had to memorize a formula. Competing with a fellow student for top score in the class, we both realized that data analysis, as it pertains to research in behavioral sciences, is far more interesting than anything else we might be doing. One thing leads to another, and we each ended up in a quantitative field (he is now on the faculty at Texas State). One topic informs another, and creativity grows from diversity of information.
To think of knowledge as a siloed system of isolated subjects-- math, English, history, physics—is to miss the joy of learning. Learning can be part of everyday life.
In teaching my 4-year old basic math concepts, we play games with the numbers. How many jelly beans do you have if I take 3 away from your handful of 12? What if you give 3 jelly beans to each of 4 kids? How many beans is that? She makes math part of her imaginative play, and it plants the seed of learning that will hopefully serve her for a lifetime.
And just like the quantum state of the Heisman, the quantum state of future STEM professionals requires that we treat it as if we are ahead—and behind—at the same time. Teaching math and science in ways that are fun, and that inform other areas of study, might be the key to motivating students to study STEM, so that future generations can “open the box” in 10 or 20 years to find a “living” in science, technology, engineering and math inside. Now I’m going to play catch in a probability field with my favorite (electron-speed) preschooler.
Thanks for reading!!
** with apologies to my dad, a retired physicist and fair-weather armchair quarterback, who is no doubt shaking his head right now.
Back in the day, one of the required courses for all computer science majors at my alma mater (SUNY Potsdam) was Data Communications. The culminating project for that course, when I took it, was to link four PCs in a data comm network via the parallel port.
This was a very geeky project. We used soldering irons to modify cables; we implemented software layers in assembly code as well as C code, and we had to work together as a team. All of these are important skills for real world projects. But as the end result, we had a small network of four PCs linked by parallel port -- something that really had no practical use. (Remember, the parallel port was used mainly for communicating with printer devices. Your computer sends information to the printer, but those printers sent relatively little information back, aside from a BUSY or ERROR signal.)
That's not what computer science is about today. Within today's computer science departments, students work with their peers in other academic departments (and industry) to use their skills to solve problems in the domains of other disciplines. That includes math, economics, statistics, and physics -- the disciplines with obvious need for number crunching and equation solving. But it also includes the "humanities" subjects, such as English, music, and education. Just as important, the practitioners of these other disciplines learn that technology can help improve their work, and not just distract from it.
We still need the geeky projects like my data comm experience to help build the basic skills, so that as computer scientists we have that background knowledge to bring to the table. It's like how a medical student has to spend a certain amount of time with cadavers, not to become really good at working with dead people (apologies to Quincy), but to build up the knowledge needed to bring help to the living patients who can benefit from it.
That brings me to this true anecdote: A couple of weeks ago I had a phone conversation with a SAS customer who works for a major health insurance provider. He uses SAS to collect and report on data about surgical outcomes. We had a great conversation about SAS libnames, data sets, and many other geeky aspects of SAS programming. He spoke with such fluency about programming concepts that I was surprised when I later saw his credentials in his e-mail signature: he's a registered nurse.