Archive for December, 2015
Book released: Learner-Centered Design of Computing Education: Research on Computing for Everyone
My book in John Carroll’s Human-Centered Informatics series was just released: Learner-Centered Design of Computing Education: Research on Computing for Everyone http://dx.doi.org/10.2200/S00684ED1V01Y201511HCI033
The book is available on Amazon here. There’s a cool website with all options for getting the book here.
I’ve put a copy of the Table of Contents and Preface here: http://bit.ly/LCD-CE-Guzdial.
My goal is to provide an overview (110 pages worth) of the research (over 300 references) related to computing education for everyone. I aim to connect literature from the traditional computing education research communities (e.g., SIGCSE and ICER) to research in learning sciences, educational psychology, and human-computer interaction. There is a lot of history in the book because that’s how I like to view these things.
I spent most of 2015 writing this book, and this year set the context for the book. This was the year that Chicago, San Francisco, Arkansas, and then New York City decided to require computing for everyone. I had all those efforts in mind when I was writing, to tell what research has found about teaching computing to everyone.
I expect to be blogging on some of themes in the book in 2016. Hope you all have Happy Holidays!
CRA Report on Innovative Approaches to Computing Education
In June 2014, a workshop was held to initiate the process of exploring novel solutions in order to discuss how the community can move forward in creating a larger, a more diverse and a more able pool of computing specialists.
The report is available here. I was there, and the report does a good job of reporting on the discussion. It’s less about computing for everyone and more about making the computer scientists we have in undergraduate better — a particular challenge given the tsunami of enrollments these days.
Girls better than boys at making story-based computer games
I learned about this work at VL/HCC a couple months ago. It’s an interesting connection to the earlier post on women being better than men as programmers (see link here).
Teenage boys are perhaps more known for playing computer games but girls are better at making them, a University of Sussex study has found. Researchers in the University’s Informatics department asked pupils at a secondary school to design and program their own computer game using a new visual programming language that shows pupils the computer programs they have written in plain English. Dr Kate Howland and Dr Judith Good found that the girls in the classroom wrote more complex programs in their games than the boys and also learnt more about coding compared to the boys.
How Small a Part Research Plays in Making and Implementing Educational Policy
Thanks to Alan Fekete for this link from one of my favorite educational historians, Larry Cuban. I’ve posted here about how how education research is mostly ignored by CS teachers (see link here). Cuban is pointing out that policy makers don’t consider education research (or maybe research at all). On the other hand, mathematics and science education policy leaders have told us that the research evidence base is important in gaining consensus for standards (see link here). Maybe this is just as we might expect — the politicians don’t necessarily know the research, but they get advice from people who do.
Keep in mind that none of the above critiques of limited influence of research on policy is restricted to public schooling. Making policy in systems of criminal justice, environmental improvement–think climate change–and health improvement and clinical medicine–think of TV ads for drugs–are subject to similar political factors and personal beliefs rather than what research has found. Calls for more collaboration between university researchers and policymakers have also been heard and ignored for decades. Critics have pointed out many times that the academic culture and its rewards overlap little with the world that decision-makers face every week.
The Algorithmic Future of Education: The History of the Future of Education
I find the history of both computer science and education fascinating, so this keynote by Audrey Watters is particularly interesting for me because it’s on both. The most often highlighted line in the article is this one:
Education technology is, despite many of our hopes for something else, for something truly transformational, often a tool designed to meet administrative goals.
Audrey shows how educational technology has been used to mechanize our theoretical understanding of what’s the best kind of education.
Now some of these strengths of tutors may be supposition or stereotype. Nonetheless, the case for tutoring was greatly reinforced by education psychologist Benjamin Bloom who, in 1984, published his article “The Two Sigma Problem” that found that “the average student under tutoring was about 2 standard deviations above the average of the control class,” a conventional classroom with one teacher and 30 students. Tutoring is, Bloom argued, “the best learning conditions we can devise.”But here’s the challenge that Bloom identified: one-to-one tutoring is “too costly for most societies to bear on a large scale.” It might work for the elite, but one tutor for every student simply won’t work for public education. Enter the computer — and a rekindling of interesting in building “robot tutors.”
Source: The Algorithmic Future of Education — The History of the Future of Education — Medium
But as she points out, what we end up losing when we mechanize education is the part that is most important. The best part of a good educational experience is the most human part, which is the part which we cannot put into the computer. I recommend the whole article.
AP Computer Science Demographics Report for 2015 completed #CSEdWeek
Barbara Ericson, with the help of Phil Sands at Purdue, has now finished tabulating the demographic data for AP Computer Science for 2015 — see link here. We don’t yet have the statistical tests that Kevin Karplus asked for (see post here), but Barbara did list the percentage of Hispanic exam takers with their proportion of the population.
Our blog posts on AP CS have been picked up by Audrey Watters in her 2015 Top Ed-Tech Trends summary, in a decidedly negative light.
I’ll look at the whole “learn-to-code” push in an upcoming post, but I will note here: “Nationally, 37,327 students took the AP CS A exam in 2014,” Mark Guzdial observed. “This was a big increase (26.29%) from the 29,555 students who took it in 2013.” “Barbara Ericson’s 2015 AP CS demographics analysis: Still No African-Americans Taking the AP CS Exam in 9 States.” And Code.org teamed up with the College Board: because everyone needs to learn to code and then hand over money to the College Board for an AP test on the subject. Boom.
We don’t analyze AP CS A in order to market for the College Board. We analyze AP CS A exam demographics because it’s the only operational definition we have found of the state of computing education across the United States. From our work in “Georgia Computes!” we know that AP CS A tracks closely all other computing education in Georgia. AP CS A is a dipstick to get a sense for who’s in the high school CS population.
Blog Post #2000: Barbara Ericson Proposes: Effectiveness and Efficiency of Adaptive Parsons Problems #CSEdWeek
My 1000th blog post looked backward and forward. This 2000th blog post is completely forward looking, from a personal perspective. Today, my wife and research partner, Barbara Ericson, proposes her dissertation.
Interesting side note: One of our most famous theory professors just blogged on the theory implications of the Parsons Problems that Barb is studying. See post here.
Barb’s proposal is the beginning of the end of this stage in our lives. Our youngest child is a senior in high school. When Barbara finishes her Human-Centered Computing PhD (expected mid-2017), we will be empty-nesters and ready to head out on a new adventure.
Title: EVALUATING THE EFFECTIVINESS AND EFFICIENCY OF PARSONS PROBLEMS AND DYNAMICALLY ADAPTIVE PARSONS PROBLEMS AS A TYPE OF LOW COGNITIVE LOAD PRACTICE PROBLEM
Barbara J. Ericson
Ph.D. student
Human Centered Computing
College of Computing
Georgia Institute of Technology
Date: Wednesday, December 9, 2015
Time: 12pm to 2pm EDT
Location: TSRB 223
Committee
————–
Dr. James Foley, School of Interactive Computing (advisor)
Dr. Amy Bruckman, School of Interactive Computing
Dr. Ashok Goel, School of Interactive Computing
Dr. Richard Catrambone, School of Psychology
Dr. Mitchel Resnick, Media Laboratory, Massachusetts Institute of Technology
Abstract
———–
Learning to program can be difficult and can result in hours of frustration looking
for syntactic or semantic errors. This can make it especially difficult to prepare inservice
(working) high school teachers who don’t have any prior programming
experience to teach programming, since it requires an unpredictable amount of time for
practice in order to learn programming. The United States is trying to prepare 10,000
high school teachers to teach introductory programming courses by fall 2016. Most
introductory programming courses and textbooks rely on having learners gain experience
by writing lots of programs. However, writing programs is a complex cognitive task,
which can easily overload working memory, which impedes learning.
One way to potentially decrease the cognitive load of learning to program is to
use Parsons problems to give teachers practice with syntactic and semantic errors as well
as exposure to common algorithms. Parsons problems are a type of low cognitive load
code completion problem in which the correct code is provided, but is mixed up and has
to be placed in the correct order. Some variants of Parsons problems also require the
code to be indented to show the block structure. Distractor code can also be provided
that contains syntactic and semantic errors.
In my research I will compare solving Parsons problems that contain syntactic and
semantic errors, to fixing code with the same syntactic and semantic errors, and to writing
the equivalent code. I will examine learning from pre- to post-test as well as student
reported cognitive load. In addition, I will create dynamically adaptive Parsons problems
where the difficulty level of the problem is based on the learners’ prior and current
progress. If the learner solves one Parsons problem in one attempt the next problem will
be made more difficult. If the learner is having trouble solving a Parsons problem the
current problem will be made easier. This should enhance learning by keeping the
problem in the learner’s zone of proximal development as described by Vygotsky. I will
compare non-adaptive Parsons problems to dynamically adaptive Parsons problems in
terms of enjoyment, completion, learning, and cognitive load.
The major contributions of this work are a better understanding of how variants of
Parsons problems can be used to improve the efficiency and effectiveness of learning to
program and how they relate to code fixing and code writing. Parsons problems can help
teachers practice programming in order to prepare them to teach introductory computer
science at the high school level and potentially help reduce the frustration and difficulty
all beginning programmers face in learning to program.
Blog Post #1999: The Georgia Tech School of Computing Education #CSEdWeek
Three and a half years, and 1000 blog posts ago, I wrote my 999th blog post about research questions in computing education (see post here). I just recently wrote a blog post offering my students’ take on research questions in computing education (see post here), which serves to update the previous post. In this blog post, I’m going to go more meta.
In my CS Education Research class (see description here), my students read a lot of work by me and my students, some work on EarSketch by Brian Magerko and Jason Freeman, and some by Betsy DiSalvo. There are other researchers doing work related to computing education in the College of Computing at Georgia Tech, notably John Stasko’s work on algorithm visualization, Jim Foley’s work on flipped classrooms (predating MOOCs by several years), and David Joyner and Ashok Goel’s work on knowledge-based AI in flipped and MOOC classrooms, and my students know some of this work. I posed the question to my students:
If you were going to characterize the Georgia Tech school of thought in computing education, how would you describe it?
We talked some about the contrasts. Work at CMU emphasizes cognitive science and cognitive tutoring technologies. Work at the MIT Media Lab is constructionist-based.
Below is my interpretation of what I wrote on the board as they called out comments.
- Contextualization. The Georgia Tech School of Computing education emphasizes learning computing in the context of an application domain or non-CS discipline.
- Beyond average, white male. We are less interested in supporting the current majority learner in CS.
- Targeted interventions. Georgia Tech computing education researchers create interventions with particular expectations or hypotheses. We want to attract this kind of learner. We aim to improve learning, or we aim to improve retention. We make public bets before we try something.
- Broader community. Our goal is to have a broaden participation in computing, to extend the reach of computer science.
- We are less interested in making good CS students better. To use an analogy, we are not about raising the ceiling. We’re about pushing back the walls and lowering the floors, and sometimes, creating whole new adjacent buildings.
- We draw on learning sciences theory, which includes cognitive science and educational psychology (e.g., cognitive load theory).
- We draw on social theories, especially distributed cognition, situated learning, social cognitive theory (e.g., expectancy-value theory, self-efficacy).
I might have spent hours coming up with a list like this, but in ten minutes, my students came up with a good characterization of what constitutes the Georgia Tech School of Thought in Computing Education.
The Tech Industry, Building Consensus, and Changing the Education Canon
My most recent Blog@CACM post is on the K-12 CS Education Framework stakeholder’s meeting I attended last month in Chicago — see link here. The parts of the meeting where I learned the most were the first three talks, from Michael Lach, Heidi Schweingruber, and Michael Gilligan on mathematics and science education standards and what those efforts have to teach us in computer science. That’s what I wrote the Blog@CACM post on.
At the break, I congratulated Mike Lach on an excellent talk. I told him that I appreciated his message that we have to go slow. The CS education effort is the first attempt in decades to change the American Education Canon — what we teach everyone in US public schools. He agreed, and pointed out that the last time we changed the canon was in response to the Civil Rights Movement. I was confused. He explained that the Civil Rights Movement led to the creation of the African-American History Month. That’s the last time that something got added to all US elementary schools. He said that we should be glad that there’s not that kind of anger and violence fueling the push for CS education — but on the other hand, there’s also not that same kind of consensus about the importance of CS education.
Consider the two recent Google-Gallup poll reports. From one, we learn that parents think that computer science is about applications and Web search (see report here). In the second, we learn that parents (once they are told what computer science really is) want it for their kids, but administrators and principals are less enthusiastic (see report here). Commentators on the latter report have interpreted the result as suggesting that school leaders “underestimate demand” (see article here) and may be out of touch with what parents want.
There’s another way to read these two reports together. Parents don’t really know what CS is, and they don’t understand what they’re trading off when they say that want CS education. They want their kids to know CS, but at what cost? School leaders have to deal with implementation issues, and they don’t see enough demand for computing education to give it a slice of their meager budgets.
Computing education is being discussed today because of the technology industry. We would not be talking about CS in K-12 without technology industry needs. It’s the NYC tech industry who pushed for the initiative there (see their open letter). It’s the tech industry funding Code.org (see funders here). That’s not necessarily a bad thing to have the tech industry funding the effort to put computer science in schools, but it is a different thing than having a national consensus about changing public school education to include computer science. What I hear Mike Lach and others in mathematics and science education saying is that we need to build consensus if we want the implementation of CS education in schools to succeed.
A Call for Corporate Action to Meet Labor Needs and Diversify Computing
Valerie Barr wrote a recent blog post about the state of the labor pool for STEM workers, especially in computing. I particularly liked her point about the need to provide learning opportunities to bring women back who have left the tech industry. Caroline Simard’s report on the needs of female mid-level tech managers (see blog post here) is what got me thinking about ebooks originally. Caroline’s female mid-level tech managers needed to learn about new technologies, while still balancing a demanding job and more family responsibilities than their male counterparts. That’s where I saw a need for something like our ebooks, to provide computing learning opportunities that fit into busy lives (see ebook post). I see Valerie calling for something similar — we need more pathways to learn about computing for adults (see blog post here), and those pathways might help us to broaden participation in computing.
It is true that the industry changes quickly in some ways, with new tools, new approaches, and new languages. But there is a rich pool of potential employees who are being completely overlooked. The many women who have left tech positions could be brought back in and given training to bring them up to speed on the newest languages and development practices. But this is a reasonable approach only if, at the same time, the tech industry makes a commitment to improving climate. There is no point in bringing back people who left tech if they are simply going to want to leave again in another 5 years. In fact, I imagine that bringing back a group of tech veterans who have greater maturity and experience could do wonders to improve climate in some of the tech companies. But the companies have to commit. And they have to recognize that you can still be a cutting edge agile company even if the average age of your employees ticks up a bit.
Computing Ed Research - Guzdial's Take 
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