Tag Archives: computational thinking

Math Anxiety and Me: A Tale of a Lost Opportunity

Numbers have never been my friends. I remember weeping over my “math” (really, arithmetic) homework in fourth grade. The assignment was to fill in a twelve-by-twelve grid with the multiplication table. I was in my room laboriously multiplying each pair of numbers when my father came up and found me. He pointed out that I could easily fill out each column by simply adding the number at the top of the column to the number in the current cell as I worked my way down (5 times 1 is 5, 5 times 2 is 10, 5 times 3 is 15, etc—each time I am simply adding 5). It was astonishing to me that I could do this task with simple addition, and I was actually sure that he was showing me a way to cheat. I took the hint, of course, and was quickly finished, but I never shook the feeling that numbers were opaque, frustrating, and needed to be approached by devious means.

In seventh grade I discovered logic, and it fascinated me. I spent a lot of time thinking about logic, paradoxes, syllogisms, and oxymorons. I didn’t know that this was a field of study, or that I would be able to find books on this. I just played with it myself and enjoyed the sort of thinking it made me do.

Some of my greatest moments of suffering in school were in math class. I was totally unengaged, had no intrinsic interest, and had mostly unpleasant teachers. When I think of high school math the image that comes into my head is of Mr. Groninger, a large, sagging, grey man who droned on and on and never seemed to notice me or my disaffection. My High School grades in math were pretty good, but won at the cost of drudgery.

During my High School years we adopted a pet monkey, and late in High School my career ambition was to be a primatologist. This was the culmination of a series of career ambitions: first, at five, a witch; second, at nine, a vertebrate paleontologist (I loved the bones at the anthropology museum); third, as a teenager, a doctor. I remember when I was five lying in bed designing the piece of hardware that would be needed to fasten my child’s umbrella to the stick of my broom—but why I did not become an engineer is a story for another day.

Between my junior and senior years in High School I got a summer job working for a young primatologist, Tom Struhsaker, at Rockefeller University in New York City. I lived in my grandparents’ guest room and spent all day, every day punching cards, putting my supervisor’s data on the activity cycle of vervet monkeys into machine-readable form. The following summer, the summer of 1969, I was back again, but this time he handed me a book on Fortran, gave me the formulas necessary to perform statistical computations on the data, and sent me over to the computer area. The Control Data computer filled a whole large room, and I remember my astonishment when I learned that when the university obtained the computer, a man came with it, issued by the company. I don’t remember being unwelcome there, though I was probably the youngest person and the only female around. But the space was made for the computer, not for the people, so it wasn’t really a place you could hang out.

I taught myself enough Fortran to perform the calculations my supervisor needed, and I actually enjoyed myself and got a sense of satisfaction. I was doing something useful in a field that interested me, and what I liked about programming was that I never had to do any arithmetic! I got to do all the thinking about how to set up the problem, and then the computer took care of the unpleasantness of calculation. It was an experience I remember with fondness. At the end of the summer, I even duplicated all the data cards on my own time, partly to have a record of all my hard labor, but also so I could continue to work on the data set in college.

My first year at Harvard, I took calculus, chemistry, and a primate behavior course with one of my idols, a primatologist whose books I owned and had read. Wipe out! I did not do well in calculus, despised chemistry (lecture course of 500, no visible relevance to things that interested me), and could not raise a glimmer of interest from the Great Primatologist, despite writing a paper for which I used the data on vervet monkeys. Oh well. I was interested in philosophy and sociology and got a far warmer welcome there, so I crafted a joint major and had a good time with my classes from then on.

Right after college in 1974 I worked at the Boston Children’s Museum as an intern. I was one of a crop of interns, all or almost all female, and I volunteered to work in the computer area because none of the other interns could imagine doing so. The museum had a PDP-11 and one guy, Bill Mayhew, who sat all day in a closet sized office. Bill put some special programs on the computer that only I could access, so that when I was working with kids I could use things other than the idiot-proof software that ran on the public access computers. I had a good time and the kids and adults, most of whom had never seen a computer before, were amazed.

When I decided I wanted to go to graduate school, I had been out of college for three years or so, so I thought I better brush up a bit before taking the Graduate Record Exam. My scores on the math section of the test were actually higher than my verbal scores (a first for me) because that’s where I’d put my studying effort, and because I finally had a reason—an extrinsic reason for sure, but a reason nonetheless—to study math: I really wanted to get into a good graduate school.

As a first year student in the Department of Urban Studies and Planning at MIT, I got the top grade in the introductory statistics class. But I still remember a discussion with the instructor, as we walked down the hallway after class. He told me he didn’t believe in this “math anxiety” stuff and thought it was all a lot of silliness. But I, his female star student, considered myself someone with math anxiety. To me, though, statistics was about looking beyond number to patterns, and using data to answer questions I was interested in. Finally I understood why I was studying what I was studying in the number-world, and I wanted to learn it because it was a tool I could do something with. The professor was not a good teacher for people without an intrinsic interest in and aptitude for math (in other words, for most of the students who go into a planning program) but he had two really good section teachers who became longtime friends.

I also took a macroeconomics course from Nobelist Robert Solow. Because he was teaching MIT undergraduates, about 80% of the class was equations. I zoned out. But after the math, he would always say in English what he had just said in mathematics. I got an A in the course, without ever writing an equation, because I had understood the material in a different but valid way.

So what’s the moral of the story? I was pretty good at philosophy, programming, and logical thinking. I hated “math.” I think I learned a lot of the  skills relevant to many computing fields by doing things other than math. I think I could have been a good programmer, though perhaps not a good computer scientist. Can we afford to risk losing people like me by insisting that math and computer science are joined at the hip?




Filed under computing, gender, learning, mathematics

Something Old, Something New

I’ve been spending a lot of time lately around people who think about creativity and innovation. Actually, it’s hard to avoid these topics. They seem so interwoven with life in 21st century America. But amid the rage for novelty and change, I have to wonder what we are losing. Maybe there were some good ideas that got lost along the way; perhaps part of our job is to reclaim wisdom with which we have lost touch, and try it on again in a new context, a new century.

While spending this time around the creativity and innovation folks, I’ve been thinking a lot about how certain sorts of everyday creativity–and creation–go unnoticed, or at least are undervalued. I’m leading an extracurricular activity, Sewing for Engineers, this year at the Olin College of Engineering, and I’m reminded how much skill and reasoning is involved in sewing. Patternmaking, thinking in 3D, characteristics of materials, order of operations, function, fine motor skill combined with structural knowledge. Sewing is a form of engineering, too, but less respected, perhaps, because of its association historically with women’s work, or because of its literal “softness.”

So how do we retrieve, uncover this sophisticated hidden knowledge?

Although women have made gains in most areas of STEM (Science, Technology, Engineering, and Mathematics) in the US over recent decades, one area where women’s participation has actually fallen is in computer science. Advocates seeking to counter this trend have tried to change the image of computing culture and to convince girls that “robots are cool.”

Our work with Performamatics (http://teaching.cs.uml.edu/Performamatics), which brings together arts and computing faculty for joint undergraduate teaching, suggests an alternative approach with many benefits: bringing the fiber arts together with computing in a deep way that potentially enriches both fields. Quilting is associated with family, security, warmth, tradition, culture, artistry, craft—and women. Further, because so many cultures have rich quilting traditions (in the US, for example, many African American quilts are prized collectors items) underrepresented ethnic groups can also be positively affected by quilting as a gateway to computing. Quilting, valuable for its own sake, is also a potential route to technical fluency and careers.

Quilting and computing have many potential points of contact: like much indigenous and traditional art there are many mathematical ideas embedded in quilts (see for example http://www.ted.com/talks/ron_eglash_on_african_fractals.html.) Similarly, “computational thinking” can be seen in the production even of handmade quilts. Today many quilters are also using computer controlled sewing machines and Computer Aided Design (CAD). Finally, the work on “computational garments” is equally applicable to quilts. There is a wealth of knowledge and engagement here waiting to be discovered.

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Filed under arts, computing, creativity, fiber arts, gender