Posts tagged ‘Teaspoon’

Updates: Dr. Barbara Ericson awarded ACM SIGCSE 2022 Outstanding Contributions to Education

March 2-5 is the ACM SIGCSE Technical Symposium for 2022 in Providence, RI. (Schedule is here.) I am absolutely thrilled that my collaborator, co-author, and wife is receiving the Outstanding Contributions to Education award! She is giving a keynote on Friday morning. Her abstract is below.

She’s got more papers there, on CS Awesome, on her ebooks, and on Sisters Rise Up. I’m not going to summarize them here. I’ll let you look them up in the schedule.

A couple of observations about the SIGCSE Awards this year that I love. Both Barb and the Lifetime Service to the Computer Science Education Community awardee, Simon, earned their PhD’s later in life, both within the last 10 years. Barb is the first Assistant Professor to win the Outstanding Contributions award in the 40 year history of the award.

I have one Lightning Talk. The work I’m doing these days is computing education, but it’s not in the mainstream of CS education — I focus on computing education for people who don’t want to study CS. So, I’m doing a five minute lightning talk on Teaspoon languages as provocation to come talk to me about this approach to integrating computing into non-CS subjects. You can see the YouTube version here. This is my attempt to show that each Teaspoon language can be learned in 10 minutes — I describe all of two of them in less than five minutes!

Outstanding Contribution Plenary

Friday, March 4 / 8:15 – 9:45

Ballroom A-E (RICC)

Barbara Ericson (University of Michigan)

Improving Diversity in Computing through Increased Access and Success

My goal is to increase diversity in computing. In this talk I explain why diversity is important to me. My strategy to improve diversity is to increase access and success. This work includes teacher professional development, summer camps, weekend workshops with youth serving organizations, curriculum development, helping states make systemic changes to computing education, publicizing gender and race issues in Advanced Placement Computer Science, creating free and interactive ebooks, testing new types of practice problems/tools, and offering near-peer mentoring programs.

Barbara Ericson is an Assistant Professor in the School of Information at the University of Michigan. She conducts research at the intersection of computing education, the learning sciences and HCI, to improve students’ access to and success in computing. With her husband and colleague, Dr. Mark Guzdial, she received the 2010 ACM Karl V. Karlstrom Outstanding Educator Award for their work on media computation. She was the 2012 winner of the A. Richard Newton Educator Award for her efforts to attract more females to computing. She is also an ACM Distinguished Member for Outstanding Educational Contributions to Computing.

February 24, 2022 at 7:00 am 2 comments

Updates: NSF Funding to Study Learning with Teaspoon Languages for Discrete Mathematics

A few months before the pandemic started, Dr. Elise Lockwood at Oregon State reached out to me. She’d heard that I was interested in programming for teaching non-CS subjects, and that’s what she was doing. I loved what she was doing, and we started having regular chats.

Elise is a mathematics education researcher who has been studying how students come to understand counting problems. Like “If you have three letters and four digits, how many license plates can you make?” Or “How many two letter words can you make from the letters ROCKET, if you don’t allow double letters?” She’s been exploring having students learn counting problems by manipulating Python programs to generate all the possible combinations, then counting them. (Check out her recent papers on her Google Scholar page, especially those with her student Adaline De Chenne.)

As I said, I loved what she was doing, but Python seemed heavy-handed for this. I was starting to work on our Teaspoon languages. Could we build lighter-weight languages for the same problems?

As I kept reading Elise’s papers, I started working on two possible designs.

In one of them (called Counting Sheets), we play off of students’ understanding of spreadsheets. You can just describe what you want in each column, and the system will exhaustively generate every combination:

Or you can use an “=“ formula that knows how to do very simple operations with sets. Here’s a solution to the two letter words from ROCKET without repeating problem:

This is one of the tools that we’ve been building in support for both Spanish and English keywords (like Pixel Equations, that I talked about last September):

Elise found Counting Sheets intriguing, but she was worried if it would work to make the iterative structures implicit and declarative. Would students need to see the iteration to be able to reason about the counting processes?

So, I built a second Teaspoon language, called Programmed Counting. Here, the loops are explicit, like Python, but the only variable type is a set, and the words and phrases of the language come from counting problems.

Elise was a real sport, trying out the languages as I generated prototypes and finding the holes in what I was doing. We met face-to-face only once, when I went to Portland for SIGCSE 2020 — the one that got cancelled the very morning it was supposed to start. I had lunch with Elise, and we worked for a few hours on the designs. Barb and I went home the next day, and the big pandemic lockdown started right afterwards.

Will these work for learning? We don’t know — but we just got funding from NSF to find out! “We” here is me and PhD student Emma Dodoo, and we’ll be involving Adaline as a consultant. Elise is currently a rotator at NSF, so she’s involved only from the sidelines because of NSF COI issues. Our plan is to run experiments with various combinations of the Teaspoon languages (one or both), standalone and with Python. Do we need Python if we have the Teaspoon languages? Do the Teaspoon languages serve as scaffolding to introduce concepts before starting into Python?

Below is the abstract on the new IUSE grant, as an overview of the project. University of Michigan CSE Communications wrote a nice article about the work, available here. Huge thanks to Jessie Houghton, Angela Li, and Derrick White who turned my LiveCode prototypes into functioning Web versions.

Abstract for NSF

Programming is a powerful tool that scientists, engineers, and mathematicians use to gain insight into their problems. Educators have shown how programming integrated into other subjects can be a powerful tool to enhance learning, from algebra to language arts. However, the cost is learning the programming language. Few students in the US learn programming — less than 5% of high school students nationwide. Most students do not have the opportunity to use programming to support ™ learning. This project is investigating a new approach to designing and implementing programming languages in classrooms: Task-specific programming (TSP) languages. TSP languages are explicitly design for integration in specific classes, to meet teacher needs, and to be usable with less than 10 minutes of instruction. TSP languages can make the power of programming to enhance learning more accessible. This project will test the value of TSP languages in discrete mathematics, which is a gateway course in some computer science programs.

The proposed project tests the use of two different TSP languages and contrasting that with a traditional programming language, Python. The proposed work will contribute to understanding about (1) the role of programming in learning in discrete mathematics, (2) the value of task-specific languages to scaffold learning, (3) how alternative representational forms for programming influence student use of TSP languages, and (4) how the use of TSP languages alone or in combination with traditional languages enhance students’ sense of authenticity and ability to transfer knowledge.

February 23, 2022 at 7:00 am Leave a comment

Helping social studies teachers to teach data literacy with Teaspoon languages

Last year, Tammy Shreiner and I received NSF funding to develop and evaluate computational supports for helping social studies teachers to teach data literacy and computing(see post here). We’re excited about what we’re doing and what we’re learning. Here’s an update on where we’re at on the project.

Teaspoon Languages

We have a chapter in the new book by Aman Yadav and Ulf Dalvad Berthelsen Computational Thinking in Education: A Pedagogical Perspective. This is the publication where we introduce the idea of Teaspoon Languages. Teaspoon languages are a form of task-specific languages (TSP => Teaspoon — see?). Teaspoon languages:

  • Support learning tasks that teachers (typically non-CS teachers) want students to achieve;
  • Are programming languages, in that they specify computational processes for a computational agent to execute; and
  • Are learnable in less than 10 minutes, so that they can be learned and used in a one hour lesson. If the language is never used again, it wasn’t a significant learning cost and still provided the benefit of a computational lesson.

We say that we’re adding a teaspoon of computing to other subjects. The goal is to address the goal of “CS for All” by integrating computing into other subjects, by placing the non-CS subjects first. We believe that programming can be useful in learning other subjects. Our primary goal is to meet learning objectives outside of CS using programming. Teachers (and students eventually) will be learning foundational CS content — but not necessarily the content we typically teach in CS classes. All students should learn that a program is non-WYSIWYG, that it’s a specification of a computational process that gets interpreted by a computational agent, that programming languages can be in many forms, and that all students can be successful at programming.

Our chapter, “Integrating Computing through Task-Specific Programming for Disciplinary Relevance: Considerations and Examples” (see link here) offers two use cases of how we imagine teaspoon languages to work in classrooms (history and language arts in these examples). The first use case is around DV4L, our Data Visualization for Learning tool. The second is around a chatbot language that we developed —- and have long since discarded.

We develop our teaspoon languages in a participatory design process, where teachers try our prototypes in authentic tasks as design probes, and then they tell us what we got wrong and what they really want. Our current iteration is called Charla-bots and is notable for having user-definable languages. We have a variety of Charla-bot languages now, with English, Spanish, and mixed keywords.

Our vision for teaspoon languages is a contrast with the “Hour of Code” approach. The “Hour of Code” is a one hour programming activity that many schools use in every grade, typically once a year during CS Ed Week (in early December). The great idea is to build familiarity and confidence in programming by showing students real computer science every year. The teaspoon languages approach is to imagine one or two little learning programming activity in every social studies, language arts, and mathematics class every year. Each of these languages is tiny and different. The goal is that by the time that US students take a CS class (typically, in high school or undergraduate), they will have had many programming experiences, have seen a variety of types of programming languages, and have a sense that “programming isn’t hard.”

Meeting the Needs of Social Studies Teachers

The second paper, “Using Participatory Design Research to Support the Teaching and Learning of Data Literacy in Social Studies” (see link here) was just presented in October by Tammy at CUFA, the College and University Faculty Assembly 2021 of the National Council of the Social Studies. (We have a longer form of this paper that we have just submitted to a journal.) This is an exciting paper for me because it’s exactly addressing the critical challenge in our work. We can design and implement all kinds of prototype Teaspoon languages, but to achieve our goals, teachers in disciplines other than CS have to see value and adopt them.

The paper is about our workshops with practicing social studies teachers. Tammy has a goal to teach social studies teachers how to teach data literacy. She has built a large online education resource (OER) on teaching data literacy in social studies. Learning data literacy involves being able to read, comprehend, and argue with data visualizations, but also being able to create them. That’s where we come in. Her OER links to several tools for creating data visualizations, like Timeline JS, CODAP, and GapMinder. Most of them were not created for social studies teachers or classes. When we run these workshops, our tools are just in-the-mix. We offer scaffolding for using all of them. These are our design probes. The teachers use the tools and then tell us what they really want. These are our data, and we analyze them in detail —- as in this paper.

Let’s jump to the bottom line: We’re not there yet. The teachers love the OER, but get confused about why should do in their classes. They find the tools for data visualization fascinating, but overwhelming. They like DV4L a lot:

One pre-service teacher explained that they preferred our prototype over other tools because “(with the prototype DV4L) I found myself asking questions connected to the data itself, rather than asking questions in order to figure out how to work the visual.”

Recently, I held a focus group with some social studies teachers who told me that they won’t use any computational tools —- they believe in teaching data visualization, but all created with pencil and ruler. That’s our challenge: Can we be more powerful, more enticing, and easy enough to beat out pencil and ruler? Our tool, DV4L, is purpose-built for these teachers, and they appreciate its advantages — and yet, few are adopting. That’s where we need to work next.

Opportunities for Social Studies Teachers to Get Involved

If you know a social studies teacher who would want to keep informed about our work and perhaps participate in our workshops or studies, please have them sign up on our mailing list. Thank you!

Often, what teachers tell us they really want suggests new features or entirely new tools. We have two ongoing studies where we are looking for design feedback from social studies teachers. If you know social studies teachers who would like to play with something new (and we’ll pay them for their time), would you please forward these to them?

Timeline Builder

We’re looking for K-12 Social Studies teachers to try out our new timeline visualization tool, TimelineBuilder. TimelineBuilder has been made with teachers and usability in mind. In it, ‘events’ are added to a timeline using a form-based interface. Changes to the timeline can be seen automatically, with events showing up as soon as they are added.

This study will consist of completing 2 surveys and 3 asynchronous activities guided by worksheets. All participants will be compensated with a $20 gift card for survey and activity completion. There is an additional option to be invited to a focus group, which will provide additional compensation.

If you are interested in participating in this study, you can complete the consent form and 1st survey here. (Plain text Link: https://forms.gle/gwxfn5bRgTjyothF6 )

Please contact Mark Guzdial (mjguz@umich.edu) or Tamara Nelson-Fromm (tamaranf@umich.edu) with any questions.

The University of Michigan Institutional Review Board Health Sciences and Behavioral Sciences has determined that this study is exempt from IRB oversight.

DV4L Scripting Study

Through our work with social studies educators thus far, we have designed the tools DV4L-Basic and DV4L-Scripting specifically to support data literacy standards in social studies classrooms. If you are a social studies middle or high school teacher, we would love to hear your feedback. If you can spare less than an hour of your time to participate in our study, we will send you a $50 gift card for your time and valuable feedback.

If you are interested but want more details, please visit/complete the consent form here: https://forms.gle/yo3yWGThQ1wnhu7g7

For questions or concerns, please contact Mark Guzdial (mjguz@umich.edu) or Bahare Naimipour (baharen@umich.edu).

References

Guzdial, M. and Tamara L. Shreiner. 2021. “Integrating Computing through Task-Specific Programming for Disciplinary Relevance: Considerations and Examples.” In Computational Thinking in Education: A Pedagogical Perspective, Aman Yadav and Ulf Dalvad Berthelsen (Eds). PDF of Submitted.

Shreiner, Tamara L., Mark Guzdial, and Bahare Naimipour. 2021. “Using Participatory Design Research to Support the Teaching and Learning of Data Literacy in Social Studies.” Presented at CUFA, the College and University Faculty Assembly 2021 of the National Council of the Social Studies. PDF

December 22, 2021 at 10:00 am 9 comments

Computer Science was always supposed to be taught to everyone, and it wasn’t about getting a job: A historical perspective

I gave four keynote talks in the last two months, at SIGITE, Models 2021 Educators’ Symposium, VL/HCC, and CSERC. I’m honored to be invited to them, but I do suspect that four keynotes in six weeks suggest some “personal issues” in planning and saying “No.” Some of these were recorded, but I don’t believe than any of them are publicly available

The keynotes had a similar structure and themes. (A lot easier than four completely different keynotes!) My activities in computing education these days are organized around two main projects:

My goal was to put both of these efforts in a historical context. My argument is that computer science was originally invented to be taught to everyone, but not for economic advantage. I see the LSA effort and our Teaspoon languages connected to the original goals for computer science. The talks were similar to my SIGCSE 2019 keynote (blog post about that talk here, and video version here), but puts some of the early history in a different perspective. I’m not going to go into the LSA Computing Education effort or Teaspoon languages here. I’m writing this up because I hope that it’s a perspective on the early history that might be useful to others.

I start out with C.P. Snow.

My PhD advisor, Elliot Soloway, would have all of his students read this book, “The Two Cultures.” Snow was a scientist who bemoaned the split between science and humanities in Western culture. Snow mostly blamed the humanities. That wasn’t Elliot’s point for having us read his book. Elliot wanted us to think about “Who could use what we have to teach, but might not even enter our classroom?”

This is George Forsythe. Donald Knuth claims that George Forthye first published the term “computer science” in a paper in the Journal of Engineering Education in 1961. Forsythe argued (in a 1968 article) that the most valuable parts of a scientific or technical education were facility with natural language, mathematics, and computer science.

In 1961, the MIT Sloan School held a symposium on “Computers and the World of the Future.” It was an amazing event. Attendees included Gene Amdahl, John McCarthy, Alan Newell, and Grace Hopper. Martin Greenberger’s book in 1962 included transcripts of all the lectures and all the discussants’ comments.

C.P. Snow’s chapter (with Norbert Wiener of Cybernetics as discussant) predicted a world where software would rule our lives, but the people who wrote the software would be outside the democratic process. He wrote, “A handful of people, having no relation to the will of society, having no communication with the rest of society, will be taking decisions in secret which are going to affect our lives in the deepest sense.” He argued that everyone needed to learn about computer science, in order to have democratic control of these processes.

In 1967, Turing laureate Peter Naur made a similar argument (quoting from Michael Caspersen’s paper): “Once informatics has become well established in general education, the mystery surrounding computers in many people’s perceptions will vanish. This must be regarded as perhaps the most important reason for promoting the understanding of informatics. This is a necessary condition for humankind’s supremacy over computers and for ensuring that their use do not become a matter for a small group of experts, but become a usual democratic matter, and thus through the democratic system will lie where it should, with all of us.” The Danish computing curriculum explicitly includes informing students about the risks of technology in society.

Alan Perlis (first ACM Turing Award laureate) made a different argument in his chapter. He suggested that everyone at University should learn to program because it changes how we understand everything else. He argued that you can’t think about integral calculus the same after you learn about computational iteration. He described efforts at Carnegie Tech to build economics models and learn through simulating them. He was foreshadowing modern computational science, and in particular, computational social science.

Perlis’s discussants include J.C.R. Licklider, grandfather of the Internet, and Peter Elias. Michael Mateas has written a fascinating analysis of their discussion (see paper here) which he uses to contextualize his work on teaching computation as an expressive medium.

In 1967, Perlis with Herb Simon and Alan Newell published a definition for computer science in the journal Science. They said that CS was “the study of computers and all the phenomena surrounding them.” I love that definition, but it’s too broad for many computer scientists. I think most people would accept that as a definition for “computing” as a field of study.

Then, we fast forward to 2016 when then-President Obama announced the goal of “CS for All.” He proposed:

Computer science (CS) is a “new basic” skill necessary for economic opportunity and social mobility.

I completely buy the necessity part and the basic skill part, and it’s true that CS can provide economic opportunity and social mobility. But that’s not what Perlis, Simon, Newell, Snow, and Forsythe were arguing for. They were proposing “CS for All” decades before Silicon Valley. There is value in learning computer science that is older and more broadly applicable than the economic benefits.

The first name that many think of when talking about teaching computing to everyone is Seymour Papert. Seymour believed, like Alan Perlis, “that children can learn to program and learning to program can affect the way that they learn everything else.”

The picture in the lower right of this slide is important. On the right is Gary Stager, who kindly shared this picture with me. On the left is Wally Feurzeig who implemented the programming language Logo with Danny Bobrow, when Seymour was a consultant to their group at BBN. In the center is Cynthia Solomon who collaborated with Seymour on the invention of the Turtle (originally a robot, seen at the top) and the development of Logo curriculum.

Cynthia was the lead author of a recent paper describing the history of Logo (see link here), which included the example of early Logo use on the upper right of this slide, which generates random sentences. Logo is named for the Greek word logos for “word.” The first examples of Logo were about manipulating natural language. Logo has always been used as an expressive medium (music, graphics, storytelling, and animation), as well as for learning mathematics (see the great book Turtle Geometry).

This is the context in which I think about the work with the LSA Computing Education Task Force. Our question was: At an R1 University with a Computer Science & Engineering undergraduate degree and an undergraduate BS in Information (with tracks in information analysis and user experience (UX) design), what else might undergraduates need? What are the purposes for computing that are broader and older than the economic advantages of professional software development? We ended up defining three themes of what LSA faculty do with computing and what they want their students to know:

  • Computing for Discovery – LSA computational scientists create models and simulate them (not just analyze data that already exists), just as Alan Perlis suggested in 1961.
  • Computing for Expression – Computing has created new ways for humans to express themselves, which is important to study and to use to explore, invent, and create new forms of expression, as the Logo community did starting in the 1960’s.
  • Computing for Justice – LSA scholars investigate how computing systems can encode and exacerbate inequities, which requires some understand of computing, just as C.P. Snow talked about in 1961.

We develop our Teaspoon languages to meet the needs of teachers in teaching non-CS and even non-STEM classes. We argue that there are computing education learning objectives that we address with Teaspoon languages, even if they don’t include common languages features like for, while, and if statements. A common argument against our work in Teaspoon languages is that we’re undertaking a Sisyphean task. Computing is what it is, programming languages are what they are, and education is not going to be a driving force for changing anything in computing.

And yet, that’s exactly how the desktop user interface was invented.

Alan Kay (another Turing laureate in this story), Adele Goldberg, and Dan Ingalls led the development of Smalltalk in Xerox PARC in the 1970’s. The goal for Smalltalk was to realize Alan’s vision of a Dynabook, using the computer as a tool for learning. The WIMP (overlapping Windows, Icons, Menus, and mouse Pointer) interface was invented in order to achieve computing education goals. For the purposes of education, the user interface that you are using right now was invented.

The Smalltalk work tells us that we don’t have to accept computing as it is. Computing education today focuses mostly on preparing students to be professional software developers, using the tools of professional software development. That’s important and useful, but often eclipses other, broader goals for learning computing. The earliest goals for computing education are different from those in most of today’s computing education. We should question our goals, our tools, and our assumptions. Computing for everyone is likely going to look different than the computing we have today which has been defined for a narrow set of goals and for far fewer people than “all.”

November 26, 2021 at 10:00 am 21 comments

Media Computation today: Runestone, Snap!, Python 3, and a Teaspoon Language

I don’t get to teach Media Computation1 since I moved to the University of Michigan, so I haven’t done as much development on the curriculum and infrastructure as I might like if I were teaching it today. I did get a new version of JES (Jython Environment for Students) released in March 2020 (blog post here), but have rarely even started JES since then.

But using Jython for Media Computation is so 2002. Where is Media Computation going today?

I’ve written a couple of blog posts about where Media Computation is showing up outside of JES and undergraduate CS. Jens Moenig has been doing amazing things with doing Media Computation in Snap! — see this blog post from last year on his Snap!Con keynote talk. SAP is now offering a course From Media Computation to Data Science using Snap! (see link here). Barbara Ericson’s work with Runestone ebooks (see an example blog post here) includes image manipulation in Python inside the browser at an AP CS Principles level (see example here). The amazing CS Awesome ebook that Beryl Hoffman and Jen Rosato have been doing with Barb for AP CS A includes in-browser coding of Java for the Picture Lab (see example here).

I was contacted this last January by Russ Tuck and Jonathan Senning. They’re at Gordon College where they teach Media Computation, but they wanted to do it in Python 3 instead of Jython. You can find it here. It works SO well! I miss having the image and sound explorers, but my basic demos with both images and sounds work exactly as-is, with no code changes. Bravo to the Gordon College team!

On the right is Python 3 code doing Media Computation. On the left are two images -- the original in the middle, and a red-reduced image on the far left.

Most of my research these days is grounded in Task-Specific Programming languages, which I’ve blogged about here (here’s a thread of examples here and here’s an announcement of funding for the work in social studies). We now refer to the project as Teaspoon Computing or Teaspoon Languages — task-specific programming => TSP => Teaspoon. We’re adding a teaspoon of computing into other subjects. Tammy Shreiner and I have contributed a chapter on Teaspoon computing to a new book by Aman Yadav and Ulf Dalvad Berthelsen (see announcement of the book here).

We have a new Teaspoon language, Pixel Equations, that uses Media Computation to support an Engineering course in a Detroit Public School. Here, students choose a picture as input, then (1) enter the boolean equations for what pixels to select and (2) enter equations for new red, green, and blue values for those pixels. The conditionals and pixel loops are now implicit.

In several of our tools, we’re now exploring bilingual or multilingual interfaces, inspired by Sara Vogel’s work on translanguaging (see paper here) and Manuel Pérez-Quiñones’s recent work on providing interfaces for bilingual users (see his TED talk here and his ACM Interactions paper here). You can see in the screenshot below that colors can be referenced in either English or Spanish names. We’re now running participatory design sessions with teachers using Pixel Equations.

I’m planning a series of blog posts on all our Teaspoon languages work, but it’ll take a while until I get there.


  1. For new readers, Media Computation is a way of introducing computing by focusing on data abstractions used in digital media. Students write programs to manipulate pixels of a picture (to create photo filters), samples of a sound (e.g., to reverse sounds), characters of a text, and frames of a video (for video special effects). More at http://mediacomputation.org

September 6, 2021 at 7:00 am 5 comments


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