Archive for September, 2013

Education Research Questions around Live Coding: Vygotskian and Non-Constructionist

I posted my trip report on the Dagstuhl Seminar on Live Coding on Blog@CACM (see the post here).  If you don’t want to read the post, check out this video as a fun introduction to live coding:

I have a lot more that I want to think through and share about the seminar. I’m doing a series of blog posts this week on live coding to give me an opportunity to think through some of these issues.

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I saw four sets of computing education research questions in live coding. These are unusual research questions for me because they’re Vygotskian and non-Constructionist.

Live coding is about performance. It’s not an easy task. The live coder has to know their programming language (syntax and semantics) and music improvisation (e.g., including listening to your collaborator and composing to match), and use all that knowledge in real-time. It’s not going to be a task that we start students with, but it may be a task that watching inspires students. Some of my research questions are about what it means to watch the performance of someone else, as opposed to being about students constructing. I’ve written before about the value of lectures, and I really do believe that students can learn from lectures. But not all students learn from lectures, and lectures work only if well-structured. Watching a live coding performance is different — it’s about changing the audience’s affect and framing with respect to coding. Can we change attitudes via a performance?

Vygotsky argued that all personal learning is first experienced at a social level. Whatever we learn must first be experienced as an interaction with others. In computing education, we think a lot about students’ first experience programming, but we don’t think much about how a student first sees code and first sees programming. How can you even consider studying a domain whose main activity you have never even seen? What is the role of that coding generating music, with cultural and creative overtones? The social experience introducing computing is important, and that may be something that live code can offer.

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Here are four sets of research questions that I see:

  1. Making visible. In a world with lots of technology, code and programmers are mostly invisible. What does it mean for an audience to see code to generate music and programming as a live coder? It’s interesting to think about this impact for students (does it help students to think seriously about computing as something to explore in school?) and for a more general audience (how does it change adults’ experience with technology?).
  2. Separating program and process. Live coding makes clear the difference between the program and the executing process. On the first day, we saw performances from Alex MacLean and Thor Magnusson, and an amazing duet between Andrew Sorensen at Dagstuhl and Ben Swift at the VL/HCC conference in San Jose using their Extempore system. These performances highlighted the difference between program and process. The live coders start an execution, and music starts playing in a loop. Meanwhile, they change the program, then re-evaluate the function, which changes the process and the music produced. There is a gap between the executing process and the text of the program, which is not something that students often see.
  3. Code for music. How does seeing code for making music change student’s perception of what code is for? We mostly introduce programming as engineering practice in CS class, but live coding is pretty much the opposite of software engineering. Our biggest challenges in CS Ed are about getting students and teachers to even consider computer science. Could live coding get teachers to see computing as something beyond dry and engineering-ish?  Who is attracted by live coding?  Could it attract a different audience than we do now?  Could we design the activity of live coding to be more attractive and accessible?
  4. Collaboration. Live coding is a collaborative practice, but very different from pair programming. Everybody codes, and everybody pays attention to what the others are doing. How does the collaboration in live coding (e.g., writing music based on other live coders’ music) change the perception of the asocial nature of programming?

I’ll end with an image that Sam Aaron showed in his talk at Dagstuhl, a note that he got from a student in his Sonic Pi class: “Thank you for making dull lifeless computers interesting and almost reality.” That captures well the potential of live coding in computing education research — that activity is interesting and the music is real.

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September 30, 2013 at 5:38 am 5 comments

What will programmers have to know by 2040?

Interesting claim below.  Do we believe that being able to build a JIT compiler will be a critical threshold for programming in 2040?  Or will programming become so much a literacy, that there will be people who can just write grocery lists and letters to Grandma and there will be Shakespeares?  I’m predicting a broader spread, not a higher bar.

The FizzBuzz problem described below is pretty interesting, a modern day version of the Rainfall problem.  I will bet that the results claimed for FizzBuzz are true, but I haven’t seen any actual studies of it yet.

While that may be true today, what will matter far more in the future is the quality of programmers, not the quantity. Any programmer who can’t hack together a JIT compiler in 2040 will be as useless as a programmer who can’t solve FizzBuzz today.

via Neil Fraser: News: Programming TNG.

September 27, 2013 at 1:38 am 5 comments

CS loses an advocate for CS Ed: Mary Jean Harrold 1947 — 2013

My colleague Mary Jean Harrold lost her battle with cancer last week.  Mary Jean worked hard for women in computing, and was always a strong supporter of efforts to improve and broaden computing education.  The classes I’m now teaching in TA preparation were originally proposed by Mary Jean and a committee she chaired — she thought it was important that we produce PhD’s who know something about teaching and communicating ideas.  She will be missed.

Harrold also was a fierce advocate for women and minorities in computing fields.  At Georgia Tech, she was the NSF ADVANCE Professor in the School of Computer Science for 10 years, from 2001 to 2011; she also was a member of the Leadership Team and Director of the Georgia Tech Hub for the National Center for Women and Information Technology (NCWIT).  Outside Georgia Tech, Harrold served many years (several as co-chair) on the CRA’s Committee on the Status of Women in Computing Research (CRA-W), whose goal is to increase the number of women in computer science research and education.  She was instrumental in establishing the biennial Software Engineering Educators’ Symposium (SEES), which aims to forge ties between faculty at minority-serving colleges and software engineering researchers.

via In Memoriam: Mary Jean Harrold 1947 — 2013 | News | Communications of the ACM.

September 26, 2013 at 1:36 am Leave a comment

Where are the black students in STEM in Georgia?

Perhaps the saddest table I’ve ever read in my local paper.  “Mathematics II” is Sophomore year (10th grade, 15 years old) in high school mathematics.  APS is Atlantic Public Schools.  I live in Dekalb county.  No wonder we can’t get more Black students into AP CS, if we can’t get past Sophomore year mathematics.

A_Georgia_Tech_researcher_asks__Where_are_the_black_students...___Get_Schooled___www.ajc.com

71 percent of the 2,500 black students in APS who took the Mathematics II exam in 2011, failed and only 1 percent, 25 students, passed with distinction (Pass Plus). By contrast, only 21 percent of white students failed with 79 percent passing and 23 percent of those passing with distinction.

via A Georgia Tech researcher asks: Where are the black students… | Get Schooled | www.ajc.com.

September 25, 2013 at 1:32 am 6 comments

PostDoc Best Practices: For Programs Supporting PostDocs in Computer Science

Post-docs are becoming more common in computer science.  A new effort is aiming to help the community learn how to support these post-docs.

Developing new talent to carry out high impact research is of paramount importance to the Computer Science & Engineering research enterprise.  An appointment as a postdoctoral researcher is an increasingly common starting point for a research career.  The National Science Foundation (NSF) Computer & Information Science and Engineering (CISE) Directorate and the CCC recognize the critical importance in having an excellent postdoc training experience to help junior researchers advance their careers.

With NSF’s backing, the CCC is announcing a program to develop, implement and institutionalize the implementation of best practices for supporting postdocs. This program will award grants to institutions or consortia of institutions to implement best practices for strengthening the postdoc experience in computer science and computing-related fields.  These supporting programs will enable PhD graduates to transition effectively to research roles in a variety of sectors.

via PostDoc Best Practices | The Website for Programs Supporting PostDocs in Computer Science.

September 24, 2013 at 1:52 am Leave a comment

Knowing more doesn’t necessarily lead to correct reasoning: Politics changes problem-solving

Thanks to Elizabeth Patitsas for this piece.  Fascinating experiment — people solve the exact same math problem differently if the context is “whether a skin cream works” or “whether gun control laws work,” depending on their politics.  The statement below is an interesting interpretation of the results and relates to my questions about whether computing education research actually leads to any change.

For study author Kahan, these results are a fairly strong refutation of what is called the “deficit model” in the field of science and technology studies—the idea that if people just had more knowledge, or more reasoning ability, then they would be better able to come to consensus with scientists and experts on issues like climate change, evolution, the safety of vaccines, and pretty much anything else involving science or data (for instance, whether concealed weapons bans work). Kahan’s data suggest the opposite—that political biases skew our reasoning abilities, and this problem seems to be worse for people with advanced capacities like scientific literacy and numeracy. “If the people who have the greatest capacities are the ones most prone to this, that’s reason to believe that the problem isn’t some kind of deficit in comprehension,” Kahan explained in an interview.

via Science Confirms: Politics Wrecks Your Ability to Do Math | Mother Jones.

September 23, 2013 at 1:13 am 2 comments

Lessons Learned From First Year College MOOCs at Georgia Tech (and SJSU)

Karen Head has finished her series on how well the freshman-composition course fared (quoted and linked below), published in The Chronicle. The stats were disappointing — only about 238 of the approximately 15K students who did the first homework finished the course. That’s even less than the ~10% we saw completing other MOOCs.

Georgia Tech also received funding from the Gates Foundation to trial a MOOC approach to a first year of college physics course.  I met with Mike Schatz last Friday to talk about his course.  The results were pretty similar: 20K students signed up, 3K students completed the first assignment, and only 170 finished.  Mike had an advantage that Karen didn’t — there are standardized tests for measuring the physics knowledge he was testing, and he used those tests pre-post.  Mike said the completers fell into three categories: those who came in with a lot of physics knowledge and who ended with relatively little gain, those who came in with very little knowledge and made almost no progress, and a group of students who really did learn alot.  They don’t know why nor the relative percentages yet.

The report from the San Jose State University MOOC experiment with a remedial mathematics course came out with the argument:

The researchers also say, perhaps unsurprisingly, that what mattered most was how hard students worked. “Measures of student effort trump all other variables tested for their relationships to student success,” they write, “including demographic descriptions of the students, course subject matter, and student use of support services.”

It’s not surprising, but it is relevant.  Students need to make effort to learn.  New college students, especially first generation college students (i.e., whose parents have never gone to college), may not know how much effort is needed.  Who will be most effective at communicating that message about effort and motivating that effort — a video of a professor, or an in-person professor who might even learn your name?

As Gary May, our Dean of Engineering, recently wrote in an op-ed essay published in Inside Higher Ed, “The prospect of MOOCs replacing the physical college campus for undergraduates is dubious at best. Other target audiences are likely better-suited for MOOCs.”

On the freshman-composition MOOC, Karen Head writes:

No, the course was not a success. Of course, the data are problematic: Many people have observed that MOOCs often have terrible retention rates, but is retention an accurate measure of success? We had 21,934 students enrolled, 14,771 of whom were active in the course. Our 26 lecture videos were viewed 95,631 times. Students submitted work for evaluation 2,942 times and completed 19,571 peer assessments (the means by which their writing was evaluated). However, only 238 students received a completion certificate—meaning that they completed all assignments and received satisfactory scores.

Our team is now investigating why so few students completed the course, but we have some hypotheses. For one thing, students who did not complete all three major assignments could not pass the course. Many struggled with technology, especially in the final assignment, in which they were asked to create a video presentation based on a personal philosophy or belief. Some students, for privacy and cultural reasons, chose not to complete that assignment, even when we changed the guidelines to require only an audio presentation with visual elements. There were other students who joined the course after the second week; we cautioned them that they would not be able to pass it because there was no mechanism for doing peer review after an assignment’s due date had passed.

via Lessons Learned From a Freshman-Composition MOOC – Wired Campus – The Chronicle of Higher Education.

September 21, 2013 at 1:29 am 14 comments

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