Tag Archives: Programming patterns: the story of the Jacquard loom

Teaching kids to code with cultural research and embroidery machines

Leave a reply
Caption: University of Washington researchers taught a group of high schoolers to code by combining cultural research into various embroidery traditions with “computational embroidery.” The method teaches kids to encode embroidery patterns on a computer through a coding language called Turtlestitch. Here, a student stitched plants with code, then hand-embroidered a bee. Credit: Kivuva et al./SIGCSE

Textiles and computing are more closely linked than most of us realize. It was a surprise (to me, anyway) to learn that the Jacquard loom was influential in the development of the computer (see this June 25, 2019 essay “Programming patterns: the story of the Jacquard loom” on the Science and Industry Museum in Manchester [UK] website). As for embroidery, that too has an historical link to computing (see my May 22, 2023 posting “Ada Lovelace’s skills (embroidery, languages, and more) led to her pioneering computer work in the 19th century“).

The latest embroidery link to computing was announced in a March 14, 2024 news item on phys.org, Note: A link has been removed,

Even in tech-heavy Washington state, the numbers of students with access to computer science classes aren’t higher than national averages: In the 2022–2023 school year, 48% of public high schools offered foundational CS [computer science] classes and 5% of middle school and high school students took such classes.

Those numbers have inched up, but historically marginalized populations are still less likely to attend schools teaching computer science, and certain groups—such as Latinx students and young women—are less likely than their peers to be enrolled in the classes even if the school offers them.

To reach a greater diversity of grade-school students, University of Washington researchers have taught a group of high schoolers to code by combining cultural research into various embroidery traditions—such as Mexican, Arab and Japanese—with “computational embroidery.” The method lets users encode embroidery patterns on a computer through an open-source coding language called Turtlestitch, in which they fit visual blocks together. An electronic embroidery machine then stitches the patterns into fabric.

…

A March 14, 2024 University of Washington news release (also on EurekAlert), which originated the news item, describes the research in more detail, Note: Links have been removed,

“We’ve come a long way as a country in offering some computer science courses in schools,” said co-lead author F. Megumi Kivuva, a UW doctoral student in the Information School. “But we’re learning that access doesn’t necessarily mean equity. It doesn’t mean underrepresented minority groups are always getting the opportunity to learn. And sometimes all it means is that if there’s one 20-student CS class, all 3,000 students at the school count as having ‘access.’ [emphases mine] Our computational embroidery class was really a way to engage diverse groups of students and show that their identities have a place in the classroom.”

In designing the course, the researchers aimed to make coding accessible to a demographically diverse group of 12 students. To make space for them to explore their curiosities, the team used a method called “co-construction” where the students had a say each week in what they learned and how they’d be assessed.

“We wanted to dispel the myth that a coder is someone sitting in a corner, not being very social, typing on their computer,” Kivuva said.

Before delving into Turtlestitch, students spent a week exploring cultural traditions in embroidery — whether those connected to their own cultures or those they were curious about. For one student, bringing his identity into the work meant taking inspiration from his Mexican heritage; for others, it meant embroidering an image of bubble tea because it’s her favorite drink, or stitching a corgi.

Students also spent a week learning to embroider by hand. The craft is an easy fit for coding because both rely on structures of repetition. But embroidery is tactile, so students were able to see their code move from the screen into the physical world. They were also able to augment what they coded with hand stitching, letting them distinguish what the human and the machine were good at. For instance, one student decided to code the design for a flower, then add a bee by hand.

“There’s a long history of overlooking crafts that have traditionally been perceived as feminized,” said co-lead author Jayne Everson, a UW doctoral student in the Paul G. Allen School of Computer Science & Engineering. “So combining this overlooked art that is deeply technical with computing was really fun, because I don’t see computing as more or less technical than embroidery.”

The class ran for six weeks over the summer, and researchers were impressed by the interest it elicited. In fact, one of the main drawbacks researchers found was that six weeks felt too short, given the curiosity the students showed. Since the technology is affordable — the embroidery machine is $400 and the software is free — Kivuva plans to tailor the course to be approachable for kindergarteners to 5th-grade refugee students. Since they were so pleased with the high student engagement, Kivuva and Everson will also run a workshop on their method at the Computer Science Teachers Association [CSTA] conference this summer.

“I was constantly blown away by the way students were engaging when they were given freedom. Some were staying after class to keep working,” said Everson. “I come from a math and science teaching background. To get students to stick around after class is kind of like, ‘Alright, we’ve done it. That’s all I want.’”

Additional co-authors on the paper were Camilo Montes De Haro, a UW undergraduate researcher in the iSchool, and Amy J. Ko, a UW professor in the iSchool. This research was funded by the National Science Foundation, Micorosoft, Adobe and Google.

I wanted to know a little more about equity and access and found this in the introduction to the paper (link to and citation for the paper follow or there’s the PDF of the paper),

Efforts to broaden participation in computing at the K-12 level have
led to an increasing number of schools (53%) offering CS, however,
participation is low. Code.org reports that 6% of high school, 3.9%
of middle school, and 7.3% of primary school students are enrolled
[ 4]. Furthermore, historically marginalized populations are also
underrepresented in K-12 CS [4 , 9]. Prior work suggests that there
are systemic barriers like sexism, racism, and classism that lead to
inequities in primary and secondary computing education [9].

…

Here’s a link to and a citation for the paper,

Cultural-Centric Computational Embroidery by F. Megumi Kivuva, Jayne Everson, Camilo Montes De Haro, and Amy J. Ko. SIGCSE 2024: Proceedings of the 55th ACM [Association of Computing Machinery] Technical Symposium on Computer Science Education V. 1March 2024Pages 673–679 DOI: https://doi.org/10.1145/3626252.3630818 Published: 07 March 2024

This paper is open access.

The Computer Science Teachers Association (CSTA) 2024 conference mentioned in the news release is being held in Las Vegas, Nevada, July 16 -19, 2024.

Ada Lovelace’s skills (embroidery, languages, and more) led to her pioneering computer work in the 19th century

Leave a reply

This is a cleaned up version of the Ada Lovelace story,

A pioneer in the field of computing, she has a remarkable life story as noted in this October 13, 2014 posting, and explored further in this October 13, 2015 posting (Ada Lovelace “… manipulative, aggressive, a drug addict …” and a genius but was she likable?) published to honour the 200th anniversary of her birth.

In a December 8, 2022 essay for The Conversation, Corinna Schlombs focuses on skills other than mathematics that influenced her thinking about computers (Note: Links have been removed),

…

Growing up in a privileged aristocratic family, Lovelace was educated by home tutors, as was common for girls like her. She received lessons in French and Italian, music and in suitable handicrafts such as embroidery. Less common for a girl in her time, she also studied math. Lovelace continued to work with math tutors into her adult life, and she eventually corresponded with mathematician and logician Augustus De Morgan at London University about symbolic logic.

Lovelace drew on all of these lessons when she wrote her computer program – in reality, it was a set of instructions for a mechanical calculator that had been built only in parts.

The computer in question was the Analytical Engine designed by mathematician, philosopher and inventor Charles Babbage. Lovelace had met Babbage when she was introduced to London society. The two related to each other over their shared love for mathematics and fascination for mechanical calculation. By the early 1840s, Babbage had won and lost government funding for a mathematical calculator, fallen out with the skilled craftsman building the precision parts for his machine, and was close to giving up on his project. At this point, Lovelace stepped in as an advocate.

To make Babbage’s calculator known to a British audience, Lovelace proposed to translate into English an article that described the Analytical Engine. The article was written in French by the Italian mathematician Luigi Menabrea and published in a Swiss journal. Scholars believe that Babbage encouraged her to add notes of her own.

In her notes, which ended up twice as long as the original article, Lovelace drew on different areas of her education. Lovelace began by describing how to code instructions onto cards with punched holes, like those used for the Jacquard weaving loom, a device patented in 1804 that used punch cards to automate weaving patterns in fabric.

Having learned embroidery herself, Lovelace was familiar with the repetitive patterns used for handicrafts. Similarly repetitive steps were needed for mathematical calculations. To avoid duplicating cards for repetitive steps, Lovelace used loops, nested loops and conditional testing in her program instructions.

…

Finally, Lovelace recognized that the numbers manipulated by the Analytical Engine could be seen as other types of symbols, such as musical notes. An accomplished singer and pianist, Lovelace was familiar with musical notation symbols representing aspects of musical performance such as pitch and duration, and she had manipulated logical symbols in her correspondence with De Morgan. It was not a large step for her to realize that the Analytical Engine could process symbols — not just crunch numbers — and even compose music.

…

… Lovelace applied knowledge from what we today think of as disparate fields in the sciences, arts and the humanities. A well-rounded thinker, she created solutions that were well ahead of her time.

If you have time, do check out Schlombs’ essay (h/t December 9, 2022 news item on phys.org).

For more about Jacquard looms and computing, there’s Sarah Laskow’s September 16, 2014 article for The Atlantic, which includes some interesting details (Note: Links have been removed),

…, one of the very first machines that could run something like what we now call a “program” was used to make fabric. This machine—a loom—could process so much information that the fabric it produced could display pictures detailed enough that they might be mistaken for engravings.

Like, for instance, the image above [as of March 3, 2023, the image is not there]: a woven piece of fabric that depicts Joseph-Marie Jacquard, the inventor of the weaving technology that made its creation possible. As James Essinger recounts in Jacquard’s Web, in the early 1840s Charles Babbage kept a copy at home and would ask guests to guess how it was made. They were usually wrong.

.. At its simplest, weaving means taking a series of parallel strings (the warp) lifting a selection of them up, and running another string (the weft) between the two layers, creating a crosshatch. …

The Jacquard loom, though, could process information about which of those strings should be lifted up and in what order. That information was stored in punch cards—often 2,000 or more strung together. The holes in the punch cards would let through only a selection of the rods that lifted the warp strings. In other words, the machine could replace the role of a person manually selecting which strings would appear on top. Once the punch cards were created, Jacquard looms could quickly make pictures with subtle curves and details that earlier would have take months to complete. …

… As Ada Lovelace wrote him: “We may say most aptly that the Analytical Engine weaves algebraical patterns just as the Jacquard-loom weaves flowers and leaves.”

For anyone who’s very curious about Jacquard looms, there’s a June 25, 2019 Objects and Stories article (Programming patterns: the story of the Jacquard loom) on the UK’s Science and Industry Museum (in Manchester) website.