I wrote my CACM Blog post this month on the terrific discussion that Shriram started in my recent post inspired by Annette Vee’s book (see original post here), “The ethical responsibilities of the student or end-user programmer.” I asked several others, besides the participants in the comment thread, about what responsibility they thought students and end-user programmers bore for their code.
One more issue to consider, which is more computing education-specific than the general issue in the CACM Blog. If we decided that K-12 students and end-user programmers need to know how to write secure programs, could we? Do we know how? We could tell students, “You’re responsible,” but that alone doesn’t do any good.
Simply teaching about security is unlikely to do much good. I wrote a blog post back in 2013 about the failings of financial literacy education (see post here) which is still useful to me when thinking about computing education. We can teach people not to make mistakes, or we can try to make it impossible to make mistakes. The latter tends to be more effective and cheaper than the former.
What would it take to get students to use best practices for writing secure programs and to test their programs for security vulnerabilities? In other words, how could you change the practice of K-12 student programmers and end-user programmers? This is a much harder problem than setting a learning objective like “Students should be able to sum all the elements in an array.” Security is a meta-learning objective. It’s about changing practice in all aspects of other learning objectives.
What it would take to get CS teachers to teach to improve security practices? Consider for example an idea generally accepted to be good practice: We could teach students to write and use unit tests. Will they when not required to? Will they write good unit tests and understand why they’re good? In most introductory courses for CS majors, students don’t write unit tests. That’s not because it’s not a good idea. It’s because we can’t convince all the CS teachers that it’s a good idea, so they don’t require it. How much harder will it be to teach K-12 CS teachers (or even science or mathematics teachers who might be integrating CS) to use unit tests — or to teach secure programming practices?
I have often wondered: Why don’t introductory students use debuggers, or use visualization tools effectively (see Juha Sorva’s excellent dissertation for a description of how student use visualizers)? My hypothesis is that debuggers and visualizers presume that the user has an adequate mental model of the notional machine. The debugging options Step In or Step Over only make sense if you have some understanding of what a function or method call does. If you don’t, then those options are completely foreign to you. You don’t use something that you don’t understand, at least, not when your goal is to develop your understanding.
Secure programming is similar. You can only write secure programs when you can envision alternative worlds where users type the wrong input, or are explicitly trying to break your program, or worse, are trying to do harm to your users (what security people sometimes call adversarial thinking). Most K-12 and end-user programmers are just trying to get their programs work in a perfect world. They simply don’t have a model of the world where any of those other things can happen. Writing secure programs is a meta-objective, and I don’t think we know how to achieve it for programmers other than professional software developers.
UTeach has published a nice blog post that explains (with graphs!) the ideas that I alluded to in my Blog@CACM post from last month. While currently CS teacher production is abysmal, UTeach prepared CS teachers tend to stay in their classrooms for more years than I might have expected. More, there is evidence that suggests that there is significant slice of the CS undergraduate population that would consider becoming teachers if the conditions were right. There is hope to imagine that we can making produce more CS teachers, if we work from the University side of the equation. Working from the in-service side is too expensive and not sustainable.
Michael Marder, Professor of Physics and Executive Director of UTeach, and Kim Hughes, Director of the UTeach Institute, write…
The number of computer science and computer science education teachers prepared per year is smaller than for any other STEM subject — even engineering and physics — and while estimates vary, it is safe to say it is on the order of 100 to 200 per year, compared to the thousands of biology or general science teachers prepared.
The U.S. has around 24,000 public and 10,000 private high schools. Only 10% to 25% have been offering computer science, so to provide all of them with at least one teacher at the current rate simply looks impossible.
New report on coding, computer science, and computational thinking has just come out from Digital Promise. I have been critical of some definitions of computational thinking (as I described in my book). I like the way Digital Promise defined them, and particularly how they connect CT to learning in other disciplines.
Advocating for computational thinking throughout the K-12 curriculum does not replace or compete with efforts to expand computer science education: on the contrary, it complements them. Where computer science is not yet offered, integrating computational thinking into existing disciplines can empower educators and students to better understand and participate in a computational world. And schools already teaching coding and computer science will benefit from weaving computational thinking across disciplines in order to enrich and amplify lessons that are beyond the reaches of computer science classes.
We offer a number of recommendations to move this work forward. Among them are advocacy campaigns, curriculum and resource development, professional development for teachers and administrators, and continued research.
I’ve been excited to see this paper finally come out in CACM. Richard Connor, Quintin Cutts, and Judy Robertson are leaders in the Scotland CAS effort. Their new curriculum re-emphasizes the “computer” in computer science and computational thinking. I have bold-faced my favorite sentence in the quote below. I like how this emphasis reflects the original definition of computer science: “Computer science is the study of computers and all the phenomena surrounding them.”
We do not think there can be “computer science” without a computer. Some efforts at deep thinking about computing education seem to sidestep the fact that there is technology at the core of this subject, and an important technology at that. Computer science practitioners are concerned with making and using these powerful, general-purpose engines. To achieve this, computational thinking is essential, however, so is a deep understanding of machines and languages, and how these are used to create artifacts. In our opinion, efforts to make computer science entirely about “computational thinking” in the absence of “computers” are mistaken.
As academics, we were invited to help develop a new curriculum for computer science in Scottish schools covering ages 3–15. We proposed a single coherent discipline of computer science running from this early start through to tertiary education and beyond, similar to disciplines such as mathematics. Pupils take time to develop deep principles in those disciplines, and with appropriate support the majority of pupils make good progress. From our background in CS education research, we saw an opportunity for all children to learn valuable foundations in computing as well, no matter how far they progressed ultimately.
A nice summary of where we’re at with CS Ed in the United States, where additional funding and effort should go, and where it shouldn’t.
Addressing the teacher shortage should be the number one use for the new funds allocated by the Trump administration, says Mark Stehlik, a computer science professor at Carnegie Mellon University. A lack of qualified teachers is the biggest barrier to CS education in the U.S., he says, and he thinks the problem is going to get worse. An earlier generation of CS educators has started to retire, and he says younger CS graduates “aren’t going into education because they can make twice or more working in the software industry.”
One solution could be to expand the reach of each CS educator through online classes. But “online curricula aren’t going to save the day, especially for elementary and high school,” Stehlik says. “A motivated teacher who can inspire students and provide tailored feedback to them is the coin of the realm here.”
Where the money should not be spent? On hardware and equipment. Laptops, robots, and 3D printers are important, says Code.org’s Yongpradit, “but they don’t make a CS class. A trained teacher makes a CS class. So money should be focused on training teachers and offering robust curriculum.”
Danielsiek et al’s development of a new test of student self-efficacy in algorithms classes;
Rich et al.’s trajectories of K-5 CS learning, which constitute an important new set of theories about how young students learn computing.
Rich et al.’s paper is particularly significant to me because it has me re-thinking my beliefs about elementary school computer science. I have expressed significant doubt about teaching computer science in early primary grades — it’s expensive, there are even more teachers to prepare than in secondary schools, and it’s not clear that it does any longterm good. If a third grader learns something about Scratch, will they have learned something that they can use later in high school? Katie Rich presented not just trajectories but Big Ideas. Like Big Ideas for sequential programming include precision and ordering. It’s certainly plausible that a third grader who learns that precision and ordering in programs matters, might still remember that years later. I can believe that Big Ideas might transfer (at least, within computing) over years.
I was struck by a recurring theme of emotion in the papers at ICER 2017. We have certainly had years where cognition has been a critical discussion, or objects, or programming languages, or student’s process. This year, I noticed that many of these papers were thinking about beliefs and feelings.
Most obvious is the Chairs Award paper by Danielsiek et al on a measure of self-efficacy, what students believe about their own success in algorithms.
Even James Prather et al’s paper about novice interactions with compiler error messages (definitely a programming language related issue) spent time considering issues of frustration.
Thomas Price et al’s paper about when students ask for help dealt significantly with the students beliefs about whether a human or a computer tutor was more likely to be able to help them.
When Brian Dorn presented the paper by Tracie Evans Reding and himself about the teacher experience in CS professional development, he used a roller coaster as a visual metaphor at the start of his talk. It was all about the rise and fall in teacher confidence and beliefs.
I find this set of papers interesting for highlight an important research question: What’s the most significant issue influencing student success or withdrawal from computer science? Is it the programming language they use (blocks vs text, anyone?), the kind of error messages they see, the context in which the instruction is situated, or whether they use pair programming? Or is the most significant issue what the students believe about what they’re doing? And maybe all of those other issues (from blocks to pairs) are really just inputs to the function of student belief?
I review for the WIPSCE conference (an international conference on K-12 computing), and found a phrase in one of the papers I was reviewing about computing education now being mandatory in the United States. Well, not really — kinda, sorta, in someplaces. It may be hard for educators outside the US to understand the decentralized nature of computing education in the US. The individual 50 states control primary and secondary school education by law, and some of those states (notably, California, Massachusetts, and Nebraska) are “local-control” — the state itself decides to shift almost all of the education decision-making to the individual school districts (easily a hundred in a small state, multiple hundreds in large ones).
Recently the National Association of State Boards of Education has come out with a policy update about CS education in the states. Useful — except for the local control states, where the state boards of education don’t really have that much power.
While educators and parents recognize computer science as a key skill for career readiness, only five states have adopted learning standards in this area. Tides are changing, however, as the Every Student Succeeds Act (ESSA) recognizes with its call on states to provide a “well-rounded education” for students, to include computer science standards. This NASBE Policy Update outlines what states need to consider as they develop computer science standards and improve instruction, highlighting several promising state efforts already under way.
How do local control states implement reforms like computing education? In California, they’re trying to pass legislation to create an advisory board about integrating CS into education. It’s all about advice and recommendation — the state can’t make the districts do much.
California legislators are reviewing a bill that would create an advisory board to integrate computer science into education.The Assembly legislation would create a 23-person panel overseen by the state Superintendent that would deliver recommendations by September 2017 on how to improve computer science education, and establish curriculum standards for grades K-12.The panel would comprise teachers, administrators and professors across K-12 and higher education, as well as representatives from government, parent associations and student advocacy organizations. The bill is backed by Microsoft and Code.org.
Massachusetts has just come out with their new state standards. I haven’t gone through them all, but from what I’ve seen (and knowing people who helped build it), I believe that they’re really high-quality. But they’re just voluntary. The districts have to be coaxed into adopting them.
Massachusetts public schools may start using new digital literacy and computer science standards as soon as this fall. The state board of elementary and secondary education unanimously approved the standards, which are voluntary, at its monthly meeting Tuesday.”Today’s vote recognizes the importance of digital literacy and computer science to modern life, work and learning,” board chairman Paul Sagan said in a statement. “These standards will help our students think about problem solving in new ways and introduce them to valuable skills they will need in today’s economy.”
I wrote the essay in response to Idit Harel’s influential essay American schools are teaching our kids how to code all wrong. There were many responses to Idit’s essay, on social media and in other blogs. Much of the discussion focused on text programming languages vs. drag-and-drop, blocks-based languages, which I don’t think is the most critical distinction.
In this post, I respond to two of the suggestions that came up in some of these discussions. I use the five principles to review the suggestions in a kind of heuristic evaluation.
JavaScript
If we were going to teach a professional language to students, JavaScript is attractive. It’s free and ubiquitous, available in every Web browser. There are many jobs for JavaScript programmers. Because so much is built on top of it, it’s likely to remain around for many years in a compatible form. I argue in the Blog@CACM post that there are many dimensions to “real” when it comes to programming languages. “Use by professionals” is not the most important one when we talk about learners.
I recommend considering each of these five principles before choosing a programming language like JavaScript for learners.
Connect to what learners know – You could teach JavaScript as a connection to what children already know. The notation of JavaScript doesn’t look like anything that children are likely to have seen before, in contrast to Logo’s emphasis on words and sentences, Squeak eToys’ “Drive the Car,” Boxer’s simple UI boxes (what diSessa calls naive realism), and Racket/Bootstrap’s connections between algebra and S-expressions. However, JavaScript is the language of the Web today, so one could probably relate the programming activities to Web pages. Most learners are familiar with parts of a Web page, animations in a Web page, and other Web features that JavaScript can control. That might serve as a connection point for children.
Keep cognitive load low – JavaScript has a high cognitive load. I’m a JavaScript learner and am just meeting some of its weirder features. I was shocked when I first read that = is assignment, == is type-insensitive equality, and === is type sensitive equality/equivalence. So, "5"==5 is true, but "5"===5 is false. Counting the number of = and remembering what 1 vs 2 vs. 3 means is an excellent example of extraneous cognitive load. My bet is that JavaScript overwhelms children and is probably inefficient for adult learners. This means that learners are spending so much time making sense of the syntax, it takes them longer and more effort to get to the concepts (and they may lose interest before they get to the good stuff).
Be honest – JavaScript is authentic, it’s real for most senses of the term.
Be generative and productive – I don’t know if JavaScript would be generative and productive for students. I don’t know anyone teaching JavaScript as a way to teach significant ideas in CS or other STEM disciplines. My worry is that the cognitive load would be so overwhelming that you couldn’t get to the interdisciplinary or complex ideas. Students would spend too much effort counting = and fighting for loops.
We should experiment more with JavaScript, but I suspect that students would do better (struggle less with syntax, learn more, connect to other disciplines more) with a different syntax. If I were trying to get the advantages of JavaScript without the syntax cost, I’d try something like ClojureScript — freely available, as fast as JavaScript, as ubiquitous as JavaScript, used professionally, can be used to control Web pages like JavaScript (so connectable for learners), and with the syntactic similarities to mathematics that Racket enjoys.
I disagree with Rushkoff’s description of Ready, even in the title. As the first essay by David Bennahum (a “Ready Maker and Venture Partner) points out, it’s explicitly not about using a programming language.
Our efforts at Ready, a platform that enables kids to make games, apps, whatever they want, without knowing a computer language, are designed to offer a new approach to broadening access to code literacy.
Bennahum’s essay means to be provocative — and even insulting, especially to all the teachers, developers, and researchers who have been creating successful contextualized computing education:
In this new world, learning coding is about moving away from computer languages, syntax, and academic exercises towards real world connections: game design and building projects that tie into other subjects like science and social studies… This is the inverse of how computer science has been taught, as an impersonal, disconnected, abstracted, mathematical exercise.
I can see how Rushkoff could be confused. These two quotes from the Ready team seem contradictory. It’s not clear how Ready can be both about “learning coding” and “code literacy” while also allowing kids to make “without knowing a computer language.” There is no programming language in Ready. What is coding then? Is it just making stuff? I agree with Rushkoff’s concerns about Ready.
True, if people don’t have to code, they may never find out how this stuff really works. They will be limited to the programming possibilities offered by the makers of the platforms, through which they assemble ready-made components into applications and other digital experiences.
Let’s consider Ready against the five principles I propose.
Connect to what learners know – the components of Ready are the icons and sliders and text areas of any app or game. That part is probably recognizable to children.
Keep cognitive load low – Ready is all about dragging and dropping pieces to put them together. My guess is that the cognitive load is low.
Be honest – Ready is not “real” in most sense of authenticity. Yes, students build things that look like apps or games, but that’s not what motivates all students. More of Betsy DiSalvo’s “Glitch” students preferred Python over Alice (see blog post). Alice looked better (which appealed to students interested in media), but students knew that Python was closer to how professional programmers worked. Authenticity in terms of practice matters to students. No professional programmer solely drags and drops components. Programmers use programming languages.
Be generative and productive – Ready completely fails this goal. There is no language, no notation. There is no tool to think with. It’s an app/game builder without any affordances for thinking about mathematics, science, economics, ecology, or any other STEM discipline. There’s a physics engine, but it’s a black box (see Hmelo and Guzdial on black box vs glass box scaffolding) — you can’t see inside it, you can’t learn from it. They build “models” with Ready (see this neurobiology example), but I have a hard time seeing the science and mathematics in what they’re building.
Test, don’t trust – Ready offers us promises and quotes from experts, but no data, no results from use with students.
Ready is likely successful at helping students to make apps and games. It’s likely a bad choice for learners. I don’t see affordances in Ready for computational literacy.
The final review period is June 8-29. Do engage with the review. Whatever comes out of this is likely to influence the standards for K-12 CS education in the United States for the next five to ten years.
I’m not so happy with the framework, but I recognize that it’s a collaborative process where no one is going to be completely happy (see previous post about the framework). A source of difficulty for building the framework is that we are so early in CS Education in the United States. We are optimizing for the current state, at time when that state is rapidly changing.
Here’s an instance of the general problem. Last time I was at a framework meeting as an advisor, I pushed hard to include the concept of the word bit as a learning objective in the framework. Even as quantum computing is developed, the Claude Shannon notion of a bit as a fundamental unit of information is still relevant and useful — it’s one of the foundational ideas of computing. The suggestion was vehemently rejected by the writers because current teachers fear binary. I tried to argue that we can talk about bits (e.g., what is information, how we can store/represent bits, and how we can encode information in bits) without talking about binary, but the writers argued that teachers will perceive bits as being about binary and reject it. I pointed out that the word bit did appear in the document, just not explained. It’s hard to talk about computing without talking about “bits.” In response, every instance of the word bit was removed from the framework document.
We have so few teachers today in schools (e.g., no state has high school CS teachers in more than even 30% of their high schools, we likely need ten times the number of current teachers in order to provide CS education to everyone in the United States), and we’re still just figuring out how to develop new CS teachers. Should we really make decisions about the next 5-10 years based on what current teachers dislike? Especially when too few of those teachers have had significant teacher professional development? Maybe we do — we might need to keep those teachers engaged in order to grow the programs to create more teachers.
The goals of the K-12 CS framework review process are to provide transparency into the development of the K-12 CS framework and include feedback from a diverse range of voices and stakeholders. If you haven’t already, please sign up for framework updates.Individuals and institutions are invited to be reviewers of the K-12 CS framework. Institutions, such as state/district departments of education and organizations (industry, companies, non-profits), are responsible for selecting an individual or a group to represent the institution.
I saw on Facebook that Hadi Partovi was at Congress. Now I see why — there’s an effort underway to get Congress to fund more in CS education. I’m wondering what they want to get funded. Incentives for teachers? Professional development? Pre-service education? Does someone know the details?
Despite this groundswell, three-quarters of U.S. schools do not offer meaningful computer science courses. At a time when every industry in every state is impacted by advances in computer technology, our schools should give all students the opportunity to understand how this technology works, to learn how to be creators, coders, and makers — not just consumers. Instead, what is increasingly a basic skill is only available to the lucky few, leaving most students behind, particularly students of color and girls.
How is this acceptable? America leads the world in technology. We invented the personal computer, the Internet, e-commerce, social networking, and the smartphone. This is our chance to position the next generation to participate in the new American Dream.
I’ve mentioned the K12 CS Framework Process a couple of times before (see this blog post). It’s now available for public comment.
Individuals and institutions are invited to be reviewers of the K-12 CS framework. Institutions, such as state/district departments of education and organizations (industry, companies, non-profits), are responsible for selecting an individual or a group to represent the institution. Reviewers can choose to participate in one or both of the two review periods:
Feb 3 to Feb 17: Review of the 9-12 grade band concepts and practices
March 14 to April 1: Review of the entire K-12 concepts and practices
There will be a public webinar (save this link) to launch the first review period on Feb 3 at 8pm ET / 5pm PT. Learn about the development of the framework and how to provide an effective review.
Find different instructions for individuals and facilitators of group reviews, including an informational session kit for review group facilitators at http://k12cs.org/review. Visit this page after 9 am on Feb 3rd and you’ll be able to access the framework draft and an online feedback form for the first public review
Sincerely,
Lian Halbert, K-12 CS Framework development staff
P.S. Are you attending SIGCSE 2016 in Memphis this March 2-5? We will hold a Birds of a Feather session on Thursday March 3 for all SIGCSE attendees – feel free to invite folks so they can learn about the K-12 CS framework.
Surprising result! We knew that AP CS was growing quickly (see Code.org blog post), but AP Physics just took a giant leap forward. I wonder why that is, and what we can learn from that.
The number of students taking the physics test doubled between 2014 and 2015. The College Board, the nonprofit that administers the AP program, said that represents the largest annual growth in any AP course in history.
Google has just released a new report on K-12 CS Education. It’s linked at the bottom. I’m going to quote from a new Wired article that describes one of the big bottomlines.
In a big survey conducted with Gallup and released today, Google found a range of dysfunctional reasons more K-12 students aren’t learning computer science skills. Perhaps the most surprising: schools don’t think the demand from parents and students is there.
Google and Gallup spent a year and a half surveying thousands of students, parents, teachers, principals, and superintendents across the US. And it’s not that parents don’t want computer science for their kids. A full nine in ten parents surveyed viewed computer science education as a good use of school resources. It’s the gap between actual and perceived demand that appears to be the problem.
Searching for Computer Science: Access and Barriers in U.S. K-12 Education
To understand perceptions of computer science and associated opportunities, participation, and barriers, we worked with Gallup, Inc. to survey over 1,600 students, 1,600 parents, 1,000 teachers, 9,600 principals, and 1,800 superintendents. We found:
Exposure to computer technology is vital to building student confidence for computer science learning.
Opportunities to learn computer science at schools is limited for most students. When available, courses are not comprehensive.
Demand for CS in schools is high amongst students and parents, but school and district administrators underestimate this interest.
Barriers to offering computer science in schools include testing requirements for other subjects and limited availability and budget for qualified teachers.
ECEP now has a page with resources for gathering data for a landscape report — see below.
Where is your state now? The resources linked below can help you quickly find state-level data about the status of computer science education in your state. These are good starting points for putting together a landscape report that answers common questions on CS education in your state.
Barb and I went to this last year, and it was terrific — diverse and high-quality.
Call for Papers and Participation:
WiPSCE 2015
We invite you to submit a paper, report, or poster for the 10th Workshop in Primary and Secondary Computing Education (WiPSCE 2015) and join us inLondon, United Kingdom, on November 9-11, 2015. WiPSCE aims at improving the exchange of research and practice relevant to teaching and learning in primary and secondary computing education, teacher training, and related research.
Important 2015 Dates
Submission deadline: Monday, June 1
Re-submission deadline: Monday, June 8
Notification of acceptance: Monday, July 27
Submission of revised manuscripts: Monday, September 15
Early Registration deadline: Monday, October 19
Original submissions in all areas related to primary and secondary computing education are invited in the following categories:
Full paper (6–10 pages): expected to meet one of two categories – empirical research papers and philosophical research papers
Work in progress (3-4 pages): unpublished original research in progress
Practical report (4-6 pages): unpublished, original projects in the field of “primary and secondary computing education”
Posters (2 page abstract)
Topics include:
Learning: attitudes, beliefs, motivation, misconceptions, learning difficulties, student engagement with educational technology (e.g., visualization), conceptualization of computing
Teaching: teaching approaches, teaching methods, teaching with educational technology
New report on coding, computer science, and computational thinking has just come out from Digital Promise. I have been critical of some definitions of computational thinking (as I described in my book). I like the way Digital Promise defined them, and particularly how they connect CT to learning in other disciplines.
Computing Ed Research - Guzdial's Take 
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