Posts tagged ‘Media Computation’
Every University Student should Learn to Program: Guzdial Arguing for CS for All in Higher Education
A colleague recently approached me and said, “It would be useful if Universities got involved in this CS for All effort. All Universities should offer courses aimed at everyone on campus. There should be a systematic effort to get everyone to take those classes.”
I agree, and have been making this argument for several years now. I spent a few minutes gathering the papers, blog posts, and book where I’ve made that argument over the last decade and a bit.
In 2002, Elliot Soloway and I argued in CACM that we needed a new way to engage students in intro programming: Teaching the Nintendo Generation to Program.
In 2003, I published the first paper on Media Computation: A media computation course for non-majors.
In 2004, Andrea Forte led the team studying the Media Computation class at GT:Computers for communication, not calculation: Media as a motivation and context for learning and A CS1 course designed to address interests of women.
In 2005, Andrea Forte and I presented empirical evidence about the courses we’d designed for specific audiences: Motivation and nonmajors in computer science: identifying discrete audiences for introductory courses. I published a paper in CACM about how the courses came to be at Georgia Tech: Teaching computing to everyone.
In 2008, I offered the historical argument for teaching everyone to program: Paving the Way for Computational Thinking.
We’ve published several papers about our design process: Imagineering inauthentic legitimate peripheral participation: an instructional design approach for motivating computing education and Design process for a non-majors computing course.
My 2013 ICER paper was a review of a decade’s worth of research on Media Computation: Exploring hypotheses about media computation
My keynote at VL/HCC 2015 was on how computing for all is a requirement for modern society: Requirements for a computing-literate society
My 2015 book is, to a great extent: an exploration of how to achieve CS for All: Learner-Centered Design of Computing Education: Research on Computing for Everyone.
In blog posts, it’s been a frequent topic of conversation:
- In 2011, I argued that it makes more sense to require CS at universities before pushing into K-12, because then all pre-service teachers have some CS which makes later PD much easier and cheaper: https://computinged.wordpress.com/2015/11/30/require-cs-at-universities-before-k-12-computational-community-for-everyone/ and https://computinged.wordpress.com/2011/05/17/if-you-want-cs-in-high-school-require-cs-in-college/
- In 2013, I pointed out that CS is becoming increasingly valuable outside of CS: https://computinged.wordpress.com/2013/12/10/why-are-english-and-lots-of-other-majors-studying-computer-science/
- One of my earlier Blog@CACM posts was on how students learn things in MediaComp that informs them about their world, not just about CS: http://cacm.acm.org/blogs/blog-cacm/26343-media-computation-for-creativity-and-surprises/fulltext
- On how CS is a value-added to a liberal education: http://cacm.acm.org/blogs/blog-cacm/101738-computer-science-as-value-added-to-a-liberal-education/fulltext
I don’t know how to convince University CS departments to do just about anything, but here are my contributions to the dialogs that I hope are happening at Colleges and Universities worldwide about how to prepare students to engage in computational literacy.
My Blog@CACM post for this month is on JES, the Jython Environment for Students, which at 14 years old and over 10,000 downloads, is probably one of the oldest, most used, and (by some definition) most successful pedagogical Python IDE’s.
The SIGCSE Members list recently had a discussion about moving from Python 2 to Python 3. Here’s a description of differences. Some writers asked about MediaComp. With respect to the Media Computation libraries, one wrote:
I’m sad about this one, because we use and like this textbook, but I think it’s time to move to Python 3. Is there a compatible library providing the API used in the text?
Short answer: No. There are no compatible Media Computation libraries for CPython 2 or 3.
We keep trying. The latest attempt to build Media Computation libraries in CPython is here: https://github.com/sportsracer48/mediapy. It doesn’t work on all platforms yet, e.g., I can’t get it to load on MacOS.
We have yet to find a set of libraries in Python that work cross-platform identically for sample-level manipulations of sounds. For example, PyGame’s mixer object doesn’t work exactly the same on all platforms (e.g., sampling rates aren’t handled the same on all platforms, so the same code plays different speed output on different platforms). I can do pixel-level manipulations using PIL. We have not yet tried to find libraries from frame manipulations of video (as individual images). I have just downloaded the relevant libraries for Python 3 and plan to explore in the future, but since we can’t make it work yet in Python 2 (which has more mature libraries), I doubt it will work in Python 3.
I complained about this problem in my blog in 2011 (see post here). The situation is better in other languages, but not yet in Python.
- I have been building Media Computation examples in GP, a blocks-based language (see post here).
- Jeff Gray’s group at U. Alabama has built Blockly-like languages Pixly and Tunely for pixel and sample level manipulations.
- Cynthia Lee at Stanford has been doing Media Computation in her classes in MATLAB and in C++
- The Calico project supports Media Computation in IronPython (based on Python 3) and many other languages, because it builds on .NET/MONO which has good multimedia support.
When we did the 4th edition of our Python Media Computation textbook, I looked into what we’d have to change in the book to move to Python 3. There really wasn’t much. We would have to introduce
Last week, I attended the Computing Research Association (CRA) Snowbird conference of deans and chairs of computing. (See agenda here with slides linked.) I presented on a panel on why CS departments should embrace computing education research, and another on what CS departments can do to support the CS for All initiative. I talked in that second session about the leadership role that universities can play in creating state partnerships and influencing state policy (see the handout for my discussion table).
Andy Ko was in both sessions with me, and he’s already written up a blog post about his experiences, which match mine closely (including the feeling of being an imposter). I recommend reading his post.
Here, I’m sharing a key insight I saw and learned at Snowbird. Before the conference even started, our Senior Associate Dean for the College of Computing, Charles Isbell, challenged me to name another field that is overwhelmed with majors AND offers service courses to so many other majors. (Maybe biology because of pre-meds?) Computer Science is increasingly the provider of courses to non-CS majors, and those majors want something different than CS majors.
The morning of the first day was dedicated to the enrollment surge. CRA has been gathering data at many institutions on the surge, and Tracy Camp did a great job presenting some of the results. (Her slides are now available here, so you don’t have to rely on my pictures of her slides.) Here’s the bottomline: Student growth has been enormous (across different types of institutions), without a matching growth in faculty. The workload is increasing.
But here’s the surprise: Much of the growth in course enrollment is not CS majors. A large percentage of the growth is in other majors taking CS classes. The below graph is for “mid-level” CS courses, and there are similar patterns in intro and upper-level courses.
Tracy also presented a survey of students (slides available here), which was really fascinating. Below is a survey of (a lot) of intro students at several institutions. All the differences described are significant at p<0.05 (not 0.5 as it says). The difference in what non-majors want and CS majors was is interesting. Majors want (significantly more than non-majors) to “make a lot of money.” Non-majors more significantly want to “Give back to my community” and “Take time off work to care for family.”
U. Illinois has the most innovative program I have heard of for meeting these new needs. They are creating a range of CS+X degree programs. First, these CS+X programs are significant parts of the “X” departments.
But these stats blew me away: CS+X is now 30% of all of CS at U. Illinois (which is a top-5 CS department), and 50% of all admitted first years this year! And it’s 28% female.
It’s pretty clear to me that the future of computing education is as much about providing service to other departments as it is about our own CS major. We have suspected that the growth is in the non-majors for awhile, but now we have empirical evidence. I’ve been promoting the idea of contextualized-computing education, and the notion that other majors need a different kind of CS than what CS majors need. We need to take serious the education of non-CS majors in Computer Science.
AccessComputing and DO-IT does terrific work. I get the question in the title a lot with MediaComp, since it’s a curriculum that lends itself towards producing just visual or just audio products, while exploring the same computing concepts.
With the increasing demand for computing professionals, it’s important that students with disabilities are included in computing courses. This video includes profiles of successful computing students and professionals who happen to have disabilities. Learn how accommodations, assistive technology, and universal design strategies can make computing courses accessible to students with disabilities.
Runtime: 10:24 minutes
JES 5.02 is now released at https://github.com/gatech-csl/jes/releases/tag/5.020. I have links to all the main downloads at http://mediacomputation.org .
Fixes in JES 5.02 (with many thanks to HenryStevens and sportsracer48 for fixes):
- Fixes a problem if you quit during raw_input that you can’t do another raw_input
- Makes the Sound explorer fully functional again
- Fixes colorizing
- Makes autosave work again
- Fixes a threading error if you hit return too rapidly in the Command Area
- Unicode characters in input file get flagged. (Jython can’t execute a line with unicode characters on it.)
You can find all the fourth edition Powerpoint slides (including a 68Mb zip of all of them) at http://coweb.cc.gatech.edu/mediaComp-teach/60. I’ve put some of the Peer Instruction question slides into the chapter PPT slide decks, but you can find more at the instructors-only website (see the Media Computation website for more on the teacher website).
Most of the changes are in the early chapters. Chapter 3 on text and language manipulation is all new. The latter chapter PPT slide decks have a few new slides in each deck, including:
- Creating state-preserving versions of picture manipulation functions in Chapter 16 on Functional Programming
- Subclassing Picture and Sound to move functions into methods in Chapter 17 on Object-oriented Programming
- Recursive turtle patterns, which are possible with an improved Turtle class in JES 5 in Chapter 17
Cool example of using JES to access external data!
I’ve been teaching CCT 374: Technologies for Knowledge Media course this term. It seemed a natural fit to use a Media Computation approach to teach Python programming. The students have a term project where they had to design an application that uses City of Toronto Open Data. Just about every team decided to make something that involved displaying something on a map. So, I had to figure out how to display arbitrary maps programmatically, as simply as possible. Using the Google Maps API would have been beyond most of the students. Then I found a blog post with a Python program to retrieve static images from Google Maps.
I have adapted the code from the blog post to work within JES (Java Environment for Students) using the Media Computation libraries. I’ve made the code available on a gist.
Sorting Is Boring: Computing Education Needs to Join the Real World, like MediaComp and worked examples
Agree that we get it backwards in computing education. We ought to do more with worked examples (a form of “word problems”) — see the argument here. The point of Media Computation has always been to focus on relevance — what the students think that a computer is good for, not what the CS teacher thinks is interesting (see that argument here).
There are people who love math for math’s sake and devote themselves to proving 1 + 1 = 2. There are more people, however, who enjoy using math to prescribe medication and build skyscrapers. In elementary school, we use word problems to show why it’s useful to add fractions (ever want to split that blueberry pie?) or find the perimeter of a square. We wait until college, when math majors choose to devote four years towards pure math, to finally set aside the word problems and focus on theory. We do so because math is a valuable skill that is used in so many different professions and contexts, and we don’t want kids to give up on math because they don’t think it’s useful.
So, why does computer science start with theory and end with word problems?