Archive for January, 2011
The Art of Science Learning
Do you buy this claim, that reasoning is the same cognitive activity as imagining? I don’t. There’s clearly an intersection (e.g., as in manipulating visual imagery, as described in the quote), but it seems to me that reasoning involves a critical component, a requirement to apply discipline, that imagining does not. In fact, exercising imagination (as in brainstorming) might be hindered by too much criticism. But I want my students to be critical reasoners when they are working through their code — I want them to say, “That doesn’t make sense” and “Why should that happen?”
For many years we’ve advocated the notion of teaching as an art (The Art of Teaching Science), and this new NSF initiative offers teachers and researchers an opportunity to look at science teaching through the lens of the arts. In our book, we connected with the views of Jacob Bronowski, in his writings, and his video program (The Ascent of Man), suggesting that artistry in teaching is related to human imagination and creativity, and one’s willingness to expriment and play. Throughout his professional life, Bronowski drew similarities between art and science, and used examples from the history of science to help us understand this. Here, Bronowski offers this pedagogical suggestion:
Many people believe that reasoning, and therefore science, is a different activity from imagining. But this is a fallacy, and you must root it out of your mind. The child that discovers, sometime before the age of ten, that he can make images and move them around in his head has entered a gateway to imagination and to reason. Reasoning is constructed with movable images just as certainly as poetry is. You may have been told, you may still have the feeling that E = mc2 is not an imaginative statement. If so, you are mistaken.
Closing down computer science at the Minnesota State University
Max Hailperin passed on this story to the SIGCSE-Members list. He added that: “About 40 students will graduate from the program in May. But that will leave about 40 who haven’t. They hope to get those students through within two years. But even if they do, the students may be forced to take upper-level computer science classes from faculty who may not have taught them before.” Interesting that Aviation was going to be cancelled, too, but the local business community worked to save that program. But not CS.
It’s been a bit blue in Minnesota State University’s computer science department.
But it’s not hard to understand why.
“Everyone in the department has either been fired, retired or has resigned,” said Dean Kelley, one of those faculty members. “Two took retirement — one effective last year, one this year — one who was on a leave of absence and has resigned. As for the remaining three, the word they used was ‘retrenched.’”
Computer science as a functioning program at MSU will cease to exist at the end of this semester. So will astronomy (although they’ll still have a minor and will still offer low-level astronomy courses). And the word “journalism” will disappear entirely from the mass communications program as it transforms itself into a program of mass media.
Other programs have been retired as well. All of it, of course, was done in hopes of mitigating the damage that will be dealt to higher education across the state when the $6 billion budget shortfall is dealt with. For MSU, that means trimming roughly $10 million.
The decline effect and the scientific method : The New Yorker
Education has never been much for replication studies, but given what this article says about psychology, I’d bet that we would have trouble replicating some of our earlier education findings. I don’t see that this article condemning the scientific method as much as condemning our ability to find, define, and control all independent variables. The world changes, people change. Anything which relies on a steady-state world or human being is going to be hard to replicate over time.
Before the effectiveness of a drug can be confirmed, it must be tested and tested again. Different scientists in different labs need to repeat the protocols and publish their results. The test of replicability, as it’s known, is the foundation of modern research. Replicability is how the community enforces itself. It’s a safeguard for the creep of subjectivity. Most of the time, scientists know what results they want, and that can influence the results they get. The premise of replicability is that the scientific community can correct for these flaws.
But now all sorts of well-established, multiply confirmed findings have started to look increasingly uncertain. It’s as if our facts were losing their truth: claims that have been enshrined in textbooks are suddenly unprovable. This phenomenon doesn’t yet have an official name, but it’s occurring across a wide range of fields, from psychology to ecology. In the field of medicine, the phenomenon seems extremely widespread, affecting not only antipsychotics but also therapies ranging from cardiac stents to Vitamin E and antidepressants: Davis has a forthcoming analysis demonstrating that the efficacy of antidepressants has gone down as much as threefold in recent decades.
via The decline effect and the scientific method : The New Yorker.
Taking a test helps with learning
Really interesting result! Flies in the face of the original Worked Examples research by Sweller et al., but not the later work that emphasized skills testing as well as examples. It supports the claims of Peer Instruction, the idea of lots of mini-quiz-like questions mixed into the lecture.
Taking a test is not just a passive mechanism for assessing how much people know, according to new research. It actually helps people learn, and it works better than a number of other studying techniques.
The research, published online Thursday in the journal Science, found that students who read a passage, then took a test asking them to recall what they had read, retained about 50 percent more of the information a week later than students who used two other methods.
One of those methods — repeatedly studying the material — is familiar to legions of students who cram before exams. The other — having students draw detailed diagrams documenting what they are learning — is prized by many teachers because it forces students to make connections among facts.
These other methods not only are popular, the researchers reported; they also seem to give students the illusion that they know material better than they do.
via Test-Taking Cements Knowledge Better Than Studying, Researchers Say – NYTimes.com.
Computers are Systems, not Languages – Ian Bogost
I find this whole idea bizarre — that degree-granting programs would really believe that learning a programming language as being at all comparable to learning a natural language. Ian does a good job addressing the issues. I wonder if we in CS made a mistake when we called our notations “languages.” They’re notations. They are not used for the same purposes as natural languages. They describe different things. Maybe we led people astray by calling them languages.
Last year I learned about a rumor swirling around the comparative literature department at UCLA, where I did my PhD. Supposedly I had managed to get C++ to count as one of the three languages required for the degree. It’s not true, for the record, but it is a topic that comes up from time to time—substituting programming languages for natural languages. Many of us who work in computing and the humanities claim that knowledge of computation is essential background for all discussions that hope to bridge the two, not just for those who intend to make things for computers.
New Myro Languages
Doug Blank just sent out this report on where the IPRE robot education technology Myro was going — the movement into new languages and platforms is pretty exciting!
This is a note to let you know the status of three new versions of Myro,
the API to interact with the Fluke and Scribbler. For more information on
any of these projects, please feel free to use this mailing list.
1) Myro in C++. This project has been developed at the University of
Tennessee at Knoxville, by Bruce MacLennan, John Hoare, and others. Mayro
in C++ is ready to use. For more information, please see:
http://wiki.roboteducation.org/Myro_in_CPlusPlus
2) Myro in Java. This project is underway at DePauw University by Doug
Harms. Myro in Java is under development and ready for testers. For more
information, please see:
http://wiki.roboteducation.org/Myro_in_Java
3) Myro in the Pyjama Project. Pyjama is a new scripting environment for
Python, Ruby, Scheme, and more. This is the latest version of Myro from
the IPRE. Pyjama is designed to run very easily on multiple platforms, and
with multiple languages. Pyjama is under development and ready for
testers. Form more information, please see:
The pages at http://wiki.roboteducation.org/ will begin to change to
reflect these exciting developments and alternatives.
I invite users and developer of all of these systems to further describe
the projects, and provide additional details.
-Doug
Less than half of students at science competency
I don’t know which is scariest:
- (A) That only 27% of Georgia’s 4th graders are at competency for science learning.
- (B) That the national average is only 32%.
- or (C) That the definition of science competency is pretty amazingly low.
For a 4th grader, an example of skills demonstrated at “Proficiency” is “Recognize that gravitational force constantly affects an object.” Really? Most 4th graders don’t know that?
In a conference call on today’s release of national 2009 science scores of grades 4 and 8 and 12, members of the governing board of the the National Assessment of Educational Progress decried the one percent of students scoring at the top level. There was also concern over the growing number of students scoring below the most basic levels.
At the two grade levels where Georgia students’ test results were released, less than one-third are demonstrating solid academic performance and competency in science.
In Georgia, 27 percent of fourth graders performed at or above the proficient level on science, compared to the national average of 32 percent. In eighth grade, 27 percent performed at or above proficient, compared to 29 percent nationally. Twelfth grade scores were not released by state.
via NAEP science: Less than half of students at competency | Get Schooled.
New GaComputes Reports for CE21
Next week is the first NSF Computing Education for the 21st Century Community Meeting, in New Orleans, organized and hosted by NCWIT. In preparing for that meeting, we gathered some of our evaluation work into handouts, and now we’ve uploaded them to our website. Some of the new things that might be of interest to readers here (Warning: Most of these are technical reports, not peer-reviewed publications! The technical reports summarize analyses — lots of data, little explanation):
- We generated this as a summary for high school principals about the work going on in the School of Interactive Computing around CS Ed: 2010 CS Education flyer
- A really interesting report coming out of the statewide survey of CS1 students that we did last year. Trevisan, B., McKlin, T., & Guzdial, M. (2011). Factors Influencing CS Participation: Introductory Computer Science Students Describe What Led Them to Computing. (GaComputes! Technical Report). Atlanta: The Findings Group, LLC.
- An analysis of survey results that helps us identify the factors that influence women and members of under-represented groups in pursuing computing. Engelman, S., McKlin, T., & Guzdial, M. (2011). Conditions that encourage participation in computer science (GaComputes! Technical Report). Atlanta: The Findings Group, LLC.
- An analysis of where we are with respect to AP CS Level A in Georgia. Engelman, S., McKlin, T., & Ericson, B, Guzdial, M. (2011). Georgia Computes! Advanced Placement Analysis (2010).(GaComputes! Technical Report). Atlanta: The Findings Group, LLC.
- This is some of the raw data that influenced the recent blog post on contexts in workshops, talking about robots, Alice, Scratch, Pleo dinosaurs, and PICO Crickets. Engelman, S., McKlin, T., & Ericson, B., & Guzdial, M. (2011).Georgia Computes! Roll-Up Analysis: Student Workshops August 2009 to August 2010. (GaComputes! Technical Report). Atlanta: The Findings Group, LLC.
- This is an assessment instrument that we use in the Operation: Reboot project (aiming at helping unemployed IT workers become computing teachers) to evaluate their attitudes toward teaching. Trevisan, B., Engelman, S., McKlin, T., Ericson, B.& Guzdial, M. (2011). Operation Reboot’s Teaching Opinion Survey (GaComputes! Technical Report). Atlanta: The Findings Group, LLC.
Teacher’s free-speech rights stop at the classroom door
Every American has the right to free-speech, but this court finding says that the School Board’s instruction on what to teach overrides the teacher’s right to free speech, at least in the classroom. What does that mean for faculty? With whom does ultimate responsibility for the college classroom lay? Can my Dean say to teach in a certain way, and I’ll be liable if I don’t?
Teachers have no First Amendment free-speech protection for curricular decisions they make in the classroom, a federal appeals court ruled on Thursday.
“Only the school board has ultimate responsibility for what goes on in the classroom, legitimately giving it a say over what teachers may (or may not) teach in the classroom,” the U.S. Court of Appeals for the 6th Circuit, in Cincinnati, said in its opinion.
via Court: No Teacher Speech Rights on Curriculum – The School Law Blog – Education Week.
Student patterns: When are the quizzes due?
I mentioned that I’m doing Video Quizzes in my class this semester. I’m recording ~5 minute bits of interaction with Java (e.g., a tour of a method and a demonstration of its use), then asking students questions about the interaction (e.g., how did I fix this error in that video?). I’ve got all the video pages hooked up with Google Analytics. Given the average time usage per day report below, can you tell when the first two quizzes were due? Deadlines are forcing functions for activity. I’m fairly pleased by theseearly results– students are actually viewing the videos to answer the questions I’m posing them.
Tell us your CSEd Week Stories
The CSEdWeek effort is wrapping up last year, and starting on next. They’re trying to collect stories on what happened this year. If you could, please share your story.
If you held an event or did an activity for the week tell us your story (and if you held an event or did an activity and didn’t pledge, go ahead and pledge first and then tell us your story);
via Computer Science Education Week Extends Its Reach | CSEDWeek.org.
Somewhere, C.P. Snow is smiling
I’m surprised that the article doesn’t reference The Two Cultures.
Called Citizen Science, the new program is the brainchild of Bard’s president, Leon Botstein, who is himself an artist — the music director and conductor of the American Symphony Orchestra. Dr. Botstein has accused colleges of shirking their responsibility to create a well-rounded citizenry.
“The most terrifying problem in American university education is the profound lack of scientific literacy for the people we give diplomas to who are not scientists or engineers,” he said. “The hidden Achilles’ heel is that while we’ve found ways to educate scientists in the humanities, the reverse has never really happened. Everybody knows this, but nobody wants to do anything about it.”
via Bard College Freshmen Get Crash Course in Science – NYTimes.com.
Predictions on Future CS1 Languages
A recent article in InfoWorld on up-and-coming languages got me thinking about the future of CS1 languages. They went on at some length about Python, which I think most people consider to be the up-and-coming CS1 language.
There seems to be two sorts of people who love Python: those who hate brackets, and scientists. The former helped create the language by building a version of Perl that is easier to read and not as chock-full of opening and closing brackets as a C descendant. Fast-forward several years, and the solution was good enough to be the first language available on Googles AppEngine — a clear indication Python has the kind of structure that makes it easy to scale in the cloud, one of the biggest challenges for enterprise-grade computing.Python’s popularity in scientific labs is a bit hard to explain, given that, unlike Stephen Wolframs Mathematica for mathematicians, the language never offered any data structures or elements explicitly tuned to meet the needs of scientists. Python creator Guido von Rossum believes Python caught on in the labs because “scientists often need to improvise when trying to interpret results, so they are drawn to dynamic languages which allow them to work very quickly and see results almost immediately.”
via 7 programming languages on the rise | Developer World – InfoWorld.
There have only really been three “CS1 languages,” the way that I’m using the term: Pascal, C++, and Java. All three programming languages were used in a large (over 50%) percentage of CS1 (intro CS for CS majors in post-secondary education in the US, and AP in high school) classes. All three were AP CS languages.
Pascal at one point was probably in over 80-90% CS1 courses. Not everyone jumped immediately to C++, but C++ was in the majority of CS1 classes. I know that because, when our Java MediaComp book came out, our publisher said that Java had just pulled even with C++ in terms of percent of the market — that means C++ had to have been in lots of classes. Java is the dominant language in CS1 classes today, but it’s declining. Python’s market share is rapidly growing, 40% per year the last three years. While it’s not clear that the new AP CS nor the AP CS Level A would ever adopt Python, Python might still gain the plurality of all CS1 languages. I doubt that any language will ever gain more than 30-40% of the CS1 market again — there are (and will be) too many options for CS1 languages, and too many entrenched interests. Faculty will stick with one, and may skip a plurality, e.g., I’ve talked to teachers at schools where they stuck with C++ but now are switching to Python.
I have two specific predictions to make about future CS1 languages, based on observations of the last three and the likely fourth.
- All future CS1 languages will be in common use in industry.
- No language will gain a plurality of CS1 courses unless it existed at the time of the last transition.
The transition from Pascal to C++ led to the greatest spike in AP CS Level A tests taken in Georgia. Until 2010, that was largest number of AP CS exams taken in Georgia. The transition from C++ to Java had nowhere near that kind of impact on the test numbers in Georgia. What might have led to so much more interest in the Pascal -> C++ transition? Pascal was a language that was not (perceived to be) common in industry, while C++ was. I don’t think that people perceived such a huge difference between C++ and Java. I believe that the sense that C++ was vocationally useful, was approved of by industry, had a huge positive impact on student interest in the test.
In this blog, we have often touched on the tension between vocational and academic interests in computer science classes. Vocational most often wins, especially in the majority schools. The elite schools might play with BYOB Scratch in their intro courses (but notice — even at Harvard and Berkeley, it’s for the non-majors, not for those who will major in CS), and community colleges might use Alice to ease the transition into programming, but the vast majority of schools in the middle value industry-approval too much to adopt a pedagogical language for their CS majors.
The implication of the first prediction is that, if Scratch or Alice are ever adopted for the new AP CS, only schools on the edges of the distribution will give CS major credit for it, because most schools will not adopt a CS1 language that isn’t useful for programming in industry. That isn’t necessarily a bad thing for the new AP CS — to succeed, schools must agree to give some credit for it, not necessarily CS major. Another implication is, if my prediction holds true, Scheme will never gain a plurality in CS1 courses.
The second implication is based on an observation of the timing of the four languages. Each existed as the previous was adopted for the AP CS Level A, which is a reasonable point at which to claim that the language had reached plurality. C++ existed (since 1983) when the AP CS Level A was started in Pascal (1988, I think). C++ was adopted in 2001, and Java came out in 1995. AP CS Level A shifted to Java in 2003, and Python 1.0 came out in 1989, with Python 2.0 (the one receiving the most interest) in 2000. It takes a lot of time to develop that industry use, and to build up the sense that the new language may be worth the pain in shifting.
The implication is that, whatever the next CS1 language will be (after Python), it exists today, as Python reaches plurality. Maybe Ruby, or Scala –more likely Ruby, given the greater industry penetration. Any language that we might invent for CS1 must wait for the next iteration. Scratch, Alice, and Kodu are unlikely to ever become CS1 languages, because it is unlikely that industry will adopt them. Few professional programmers will get their jobs due to their expertise in Scratch, Alice, or Kodu. That absolutely should not matter to CS1 instructors. But it does.
Revisited: My Students Know Far Less
Beth Simon made an excellent recommendation after my report on my first Peer Instruction lesson: Was it really a bad question that students misinterpreted? Why not ask the students? You would expect that students would most likely give me the answer on this survey that they thought I wanted. This was the first slide of the day.
Here’s the distribution of responses:
I did several more “clicker” questions today in lecture, and I’m getting a better sense of what works and what doesn’t work. (Something that doesn’t work: My <expletive deleted> Lenovo TabletPC that refused to wake up at the start of class, requiring me to reboot, and losing 10 minutes of lecture! ARGH!) I asked students to write in a piece of code today (rewrite a FOR loop as a WHILE loop). The answers were actually pretty good, but the writing took a long time. I won’t do that often.
One of the general insights I’m getting is about the large variance in the class. Here’s another question I asked in class (before the Java nitpickers let loose — we’re using DrJava, they’ve seen that code works fine without semi-colons, and in fact, we had just done these three lines verbatim with variable “fred” instead of “mabel”):
And the responses:
Most of the class grokked this one, but 5 of the 22 students who responded (some told me after class that they didn’t even respond) are pretty confused. That’s over 20%.
I chatted with several of the students after class today. They’re very confused, despite having read the first two chapters of the book (they claim) and taken the quiz. (I’m using out-of-class Video Quizzes, where students watch a videotape of me using Java, then answer questions about it.) My main insight into their confusion: After only one semester of CS classes, reading code is not an automatized skill. That’s not surprising, but it’s not something that I’d thought much about. The students told me that they’re metaphorically “sounding out” the code. They’ve thinking through what’s a method (and translating that into a MATLAB or Python “function”) and what’s a class and what’s valid Java syntax with semi-colons. That’s taking them time, and sometimes, they’re responding before they’re really confident about what they read.
Peer Instruction is taking me extra time: To get the slides onto Ubiquitous Presenter, to only present from my TabletPC, to write questions and insert them into slides, and to take time from lecture (for students to answer, to discuss, to respond again). I still think it’s worthwhile, and I plan to continue trying it.
How new COMPETES law may help education and hurt research
I’ve been hearing a lot about the new COMPETES law and how much it helps education programs. This article raises a serious concern. The new education programs are mandates on NSF, and with the new Congress, increases in NSF’s budget are unlikely. A possible (likely?) outcome, then, is that research programs would be cut back to fund the new mandates.
The reauthorization also tells NSF to begin several new education initiatives. One asks NSF to replicate the successful UTEACH program at the University of Texas, Austin, that trains STEM majors to become science and math teachers in public schools. Others would encourage high school students to help university scientists collect data for NSF-funded projects, allow for a competitive grants program to support research on improving graduate education, and create industry internships for undergraduates in STEM fields. All of them would require new funding, however—some $10 million a year for the UTEACH replication, for example—meaning that NSF officials are extremely unlikely to move ahead unless Congress appropriates the money for that particular activity.
via How New COMPETES Science Law Broadens NSF Education Programs – ScienceInsider.
Computing Ed Research - Guzdial's Take 
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