Posts tagged ‘teachers’
At the NCWIT Summit this year, I heard an interesting concern. If CS counts as a mathematics or science course towards high school graduation requirements, will that make CS even less diverse? Should we keep CS as a business topic (elective) where the women and under-represented minorities are?
I took up that question for my Blog@CACM post for this month: Why Counting CS as Science or Math is Not Considered Harmful. I argue that our goal is universal computational literacy, with everyone using computing in every class and everyone taking CS. I don’t really care how it gets a foothold in schools. It was fun to write about Alan Kay, Adele Goldberg, and Andy diSessa, pointing out that they were talking about these ideas a long time before computational thinking.
Gas station without pump’s post on Garth’s complaint “Teaching programming is not getting easier” intrigued me. Garth does a good job of pulling together a lot of the themes of what makes teaching CS hard today. I think that we can improve the situation. I’m particularly interested in learning how to scaffold the development of programming knowledge, and we have to find ways to create professional communities of CS teachers. There are techniques to share (worked examples, peer instruction, pair programming, Parson’s problems, audio tours), and we’re clearly not doing a good job of it yet.
In programming there are 4 homework problems over the period of a week, none of which are “easy”, and all require some problem solving and thinking. There is somewhat of an incremental progression to the problems but that step from written problem to code is always a big one. It is somewhat similar to solving word problems in math, every student’s favorite task. For programming there are no colleagues available that have as much or more experience to pull teaching ideas from, if there are any other programming teachers at all. There are no pedagogical resources anywhere online for teaching strategies. After watching a number (3) of programming teachers teach it seems the teaching strategy is pretty consistent; show and tell and hope.
Premise 1: Teaching is a human endeavor that does not and cannot improve over time.
Premise 2: Human beings are fantastic learners.
Premise 3: Humans don’t learn well in the teaching-focused classroom.
Conclusion: We won’t meet the needs for more and better higher education until professors become designers of learning experiences and not teachers.
Interesting argument linked above, but wrong.
- Premise 1: Teaching does improve with time. Gerhard Fischer published a wonderful piece many years ago that showed how skiing instruction has improved over time, and that the approaches used can be understood in terms of cognitive science.
- Premise 2: Humans are fantastic learners, but as Kirschner, Sweller, and Clark showed, humans learn much better with direct instruction.
- Premise 3: No, no one learns well in a teaching-focused classroom. However, many teachers help their students learn better in a student-centered classrooms.
- The Conclusion doesn’t follow from the premises at all.
My May 2014 Blog@CACM post, “What it takes to be a successful high school computer science teacher” sneaks up on a radical suggestion, that I’ll make explicitly here. High school computer science teachers need to be able to read and trace code. They don’t necessarily need to know much about writing code, and they certainly don’t need to know how to be software developers.
As we are developing our CSLearning4u ebook, we’re reviewing a lot of our prior research on the practices of successful CS teachers. What do we need to be teaching teachers so that they are successful? We don’t hear successful CS teachers talking much about writing code. However, the successful ones read code a lot, while the less-successful ones do not. Raymond Lister has been giving us evidence for years that there’s a developmental path from reading and tracing code that precedes writing code.
Yes, I’m talking about taking a short-cut here. I’m suggesting that our worldwide professional development efforts for high school teachers should emphasize reading and tracing code, not writing code. Our computer science classes do the reverse of that. We get students writing code as soon as possible. I’m suggesting that that is not useful or necessary for high school teachers. It is easier for them to read and trace code first (Lister’s studies) and it’s what they will need to do most often (our studies). We can reduce costs (in time and effort) of this huge teacher development effort by shuffling our priorities and focusing on reading.
(We do know from studies of real software engineers that they read and debug more than they write code. Maybe it would be better for everyone to read before writing, but I’m focusing on the high school teachers right now.)
Constructionism–the N word as opposed to the V word–shares constructivism’s connotation of learning as “building knowledge structures” irrespective of the circumstances of the learning. It then adds the idea that this happens especially felicitously in a context where the learner is consciously engaged in constructing a public entity, whether it’s a sand castle on the beach or a theory of the universe.
- Seymour Papert and Idit Harel “Situating Constructionism”
Most researchers exploring constructionism study children. Mitchel Resnick, Yasmin Kafai, Uri Wilensky, Amy Bruckman, Idit Harel, and other academic offspring of Seymour Papert have studied how children learn through construction in a variety of media, from Scratch to e-textiles. The semi-annual Constructionism and Creativity Conference talks about “students” not “children” on the Constructionism history page, but the proceedings from the 2012 conference show that it’s about children’s learning, both formal and informal.
I’ve grown up constructionist-by-association, rather than by training. I got to work with Seymour and with Mitchel for a short time on the design for LCSI Microworlds. Yasmin is one of my oldest friends, from even before she went to work with Idit and Seymour. I worked from a constructionist perspective here at Georgia Tech with Amy Bruckman and Janet Kolodner.
Nowadays, I work mostly with adult learners — undergraduates, end-user programmers, and high school teachers. There’s nothing in Seymour’s definition that prohibits applying constructionism to adults. Their learning should be “especially felicitous” when they are “constructing a public entity.” But I don’t think that constructionism for adults is the same as constructionism for children.
I can identify examples (as an existence proof) that constructionism can work for adults as well as children.
- Teachers know that if you want to learn a new subject, sign up to teach the new subject. Constructing the course and teaching it to others is a great way of developing that knowledge.
- Programmers take on new projects to learn a new method, language, context, or community. My former PhD student, Mike Hewner, wanted to know what professional game development was like. Because he’s an exceptional software engineer, he was able to land himself an internship with a game company one summer (with no prior game experience), explicitly to learn game development.
I see three big differences in adult constructionism from child constructionism, and they’re related.
(1) Saving Face I’m learning to play the ukulele. I bought it about a few months ago, and am playing it daily. I’m learning a huge amount, both in terms of the skill and concepts needed to play, but also at a meta level about music. The ukulele makes me think about timing, strumming, and chord patterns in a different way, and now I listen to all kinds of stringed instruments in a different way. It’s helping me to sing better, since I can more easily hear when I’m at the wrong pitch and I hear rhythm differently when I’m strumming.
But I am not learning to play ukulele as a public artifact. I’m frightened by the thought of playing in public. Only my family has ever heard me play.
Adele Goldberg worked on one of the iterations of the UK Open University’s introductory computing course, and she told me that distance learning opportunities were most important for adults. She pointed out that adults work for decades to develop their careers and their prestige. It’s really hard for them to then put their hands up in a physical classroom to ask a question and risk being found out as not knowing. There’s a recent Freakonomics podcast that claims that the three hardest words to say in the English language are: “I don’t know.”
Constructionism for kids is all about the public aspect. The Scratch website plays a role in students sharing their work, downloading others’ projects, remixing and sharing back what they found. Collaboration and public sharing has always played a big role in stories of constructionist learning. Maybe this is why work in Constructionism tends to focus at the youngest children, because the social standing and peer pressure issues increase as the kids get older.
Adults have face in a different way than children. We can still learn from construction, but we might not want it to be as public in the same way as children. We might not want to even publicly remix, or others might learn what we’re doing.
(2) Presumption of Expertise I’ve mentioned before in this blog that I’ve been singing in my church choir. I often feel ignorant — and embarrassed at my ignorance. There is so much about singing in a choir that is assumed when you are an adult, from how to sing into a microphone to how to harmonize by hearing the melody. We teach these things to children, because we know that they don’t have the basics. We expect them to be novices at most things.
As an adult engaging in an activity, we are presumed not to be novices. If you sing in a choir, the assumption is that you must have sung in choirs before –“You all know the basics.” But if you’re starting out in a new domain, you may not. Even when I admit my ignorance (hard to do because of the issue of face) and ask questions, the director quickly forgets my lack of background — a couple things get explained, and then the presumption of expertise comes back. I look like all the other adults there. It’s not like a classroom of similarly-aged students where the teacher can assume a similar background. Adults have radically different backgrounds. I recently served on the advisory board for a science and engineering learning project that used Lego robotics context. The most common teacher professional development question was about the Lego. These teachers had not played with Lego as children, were uncomfortable with it, and had to spend extra (unexpected from the researchers’ perspective) time to learn to use Lego.
Constructionism depends on learning in the context of construction. The goal of the learning isn’t the construction itself. It’s construction as something to think with. As Seymour put it, you can’t think about thinking without thinking about something. But if you don’t know how to construct, then most of the activities of construction don’t fall into the background, and then it’s hard to think about the artifact being constructed and to learn from that process. Children learn through Lego and Scratch after they get the basics of how to put blocks together (in both physical and virtual forms). Adult teachers who learn from constructing lectures and adult programmers who learn from constructing software only learn after they’re comfortable with course design and programming. When you first design a course, you’re learning about course design, and less about the content. Few people will learn to program by joining an open source development effort.
The problem of expecting expertise shows up often in undergraduate education. In undergraduate computer science courses, we expect students to know about mathematic concepts from algebra, trigonometry, geometry, and even calculus. If students don’t know those concepts, we expect them to “pick them up” on their own, and their grades suffer. When they fail, we complain that “these students don’t have the right background.” If they don’t have the basic background, it’s hard to move forward. Think about it from a developmental perspective, instead of our more common judgmental “hold the standard” perspective. Where does the student get the knowledge that we expect but they “missed”? If an adult misses the basics, is that it? They’ve simply missed out for this lifetime? How does an adult fit in learning Algebra 1 (for example) if he missed out earlier?
Because of the presumption of expertise, we adult learners tend to gravitate to constructionist learning opportunities where we do know the basics. Teachers have taught before, so they can learn by teaching something new. Mike Hewner is an excellent software engineer, so simply shifting to a new domain was an enjoyable challenge.
Or, we tackle project where adults with no expertise are expected, like learning a foreign language or introductory web design. But if I as an adult decided to learn how to build a bookcase from lumber, it’s not clear where I’d go to get the basic knowledge of carpentry that I lack. Go to the local DIY store and there’s an assumption that you did shop as a kid and that you know how to hammer and saw efficiently.
Maybe this is why it’s so hard for adults to jump into a new career, to start over, to construct new prestige. We lose face because we give up our former prestige. But as we live longer, there is time enough to develop new prestige, a new face.
(3) Time and Responsibility. I saved the most obvious difference for last. In our modern society, we do the majority of formal education before our citizens develop responsibilities around home, family, and career, when they can devote time to learning. Adults are swamped with responsibilities and do not have much time to devote to learning.
Constructionism is not an efficient form of learning. Learning can happen “irrespective of the circumstances of the learning” (as Seymour says). One can learn from reading a book or attending a lecture. Building through construction can be a motivating context for learning, and it can lead to deep learning. But there are more efficient forms of learning, like individual tutoring and guided instruction. We can get better learning from mastery learning.
Adults need efficient learning. Efficient learning fits better into the time available. Learning occurs more efficiently with a teacher or mentor, who can design learning, guide learning, provide useful feedback, and cut-off dead-ends and wasted time. But the first two differences make it more difficult for adults to get the guidance that a good teacher can provide. Adult learners are less likely to seek out a teacher and ask their questions. It’s hard for teachers to recognize adult learner’s needs, because they presume expertise.
Sure, some adults will spend lots of time in “inefficient” constructionist learning activities, like model railroads, recreational mathematics, and the Society for Creative Anachronism. What are the conditions under which that happens? Obviously, leisure time is necessary — time that the adult feels can be spared from other responsibilities. What if the adult wants to learn something “real” (e.g., something that aids in meeting responsibilities, like perhaps skills towards a new job or promotion), then they are unlikely to choose a constructionist route. They might choose a MOOC, or some vocational form of learning that is more authentic.
Conclusion: I do believe that constructionism is an “especially felicitous” way to learn. It’s fun to learn through constructionism. Constructionist learning tends to be deep learning. We do want adults to be able to use constructionist learning.
Constructionism can work for adults, but it’s more challenging. There are different issues than with children. Adults have less time to spend on learning and more responsibilities. They may not have the basic construction skills and knowledge in the medium of choice for constructionist learning, which is necessary to learn through construction. They are less likely to ask for and receive the help that makes learning for effective and efficient. They are less likely to share, if that sharing might expose their lack of understanding. Constructionism is a particularly fun way to learn, but the costs of constructionism may be greater for adults than the utility provided.
As we live longer, the challenges of learning as adults becomes more of a problem. If people are going to live to 80 or 90, it’s less believable that you will learn all the basics you will ever need for whatever career(s) you might be interested in by the time you are 21. There’s time enough for a second career. We need to make opportunities sufficient to learn for that career, too.
The Economist does a nice job of capturing succinctly the history of teaching computing in schools, the explosion of interest worldwide, and the greatest challenges to making it work.
Above all, the new subject will require teachers who know what they are doing. Only a few places take this seriously: Israel has about 1,000 trained computer-science teachers, and Bavaria more than 700. Mathematics and computer-science graduates generally choose more lucrative trades; the humanities and social-science graduates who will find themselves teaching coding will need plenty of support. Britain is skimping: it is introducing its new curriculum in a rush, and preparing teachers has mostly been left to industry groups such as Computing at School, which helped put together the syllabus. If coding is to take its rightful place in the classroom, it cannot be done on the cheap.
Cameron Fadjo at Google has been leading the development of a customized search engine for identifying K-12 computer science materials. He asked me to share it with all of you:
Are you a K-12 classroom teacher or after school program volunteer looking for computer science education materials (such as lessons, tutorials, worksheets, or videos)? Visit CS4HS (http://cs4hs.com/resources/) or Google for Education (http://www.google.com/edu/tools-and-solutions/index.html#stem-cs) to access the ‘Search Engine for K-12 Computer Science Education’, a new customized search developed by Google to help you find K-12 coding, computer programming, or computer science resources for your classroom or extra-curricular program.
Really interesting idea — Code.org’s Pat Yongpradit sent a note to all of CSTA, asking CS teachers to help provide hints for Code.org tutorials. By reaching out to CSTA, they’re doing better than crowd-sourcing. They’re CS-teacher-sourcing.
We’ve had millions of students try the Code.org tutorials. They’ve submitted over 11 million unique computer programs as solutions to roughly 100 puzzles.
We’ve mapped out which submissions are errors (ie they don’t solve the puzzle), and which are sub-optimal solutions (they solve the puzzle, but not efficiently).
Today, erroneous user submissions receive really unhelpful error feedback, such as “You’re using the right blocks, but not in the right way”. We want your help improving this, by providing highly personal feedback to very specific student errors. Watch the video below to see what we mean.
I’ve mentioned before that Yasmin Kafai and Michael Kölling will be keynoters there. Barbara and I will also be there, offering a MediaComp Python workshop.
2014 CSTA Annual Conference
July 14-15, 2014 Pheasant Run Resort, St. Charles, Illinois
The CSTA annual conference is a professional development opportunity for computer science and information technology teachers who need practical, classroom-focused information to help them prepare their students for the future.
- Explore issues and trends relating directly to your classroom
- Learn, network and interact
- Choose from various workshops and breakout sessions
Some of this year’s session topics include:
- Advanced Placement Computer Science
- Computational Thinking
- Increasing Enrollment in Computer Science
- Yasmin Kafai, Professor of learning sciences at the University of Pennsylvania.
- Michael Kölling, Professor at the School of Computing, University of Kent, in Canterbury, UK.
Pre-registration is required and will be accepted for the first 500 teachers. The registration deadline is June 26, 2014. Also, please note that you must complete the payment portion of the online form in order to be fully registered for the conference!
Thanks to the generous donations of our sponsors, the registration fee of $75 (+$60 per workshop) includes lunch, resource materials, and a closing session raffle. The 2014 CSTA Annual Conference is made possible by the generous support of Oracle and Universal Technical Institute.
Please note that all workshops are “bring your own laptop” and that workshop registration is limited to 30-40 participants; so be sure to register early to get your workshop choice.
Register at: www.cstaconference.org
For more information contact: firstname.lastname@example.org
Announced on the CSTA website. There are relatively few pre-service CS Ed programs in the United States.
Bard College Master of Arts in Teaching Program, a CSTA sponsoring school, is accepting applications for the 2014-2015 preservice program.
Bard College’s preservice teaching program offers a one-year, 63 credit Master of Arts in Teaching degree and NYS Initial Teaching Certification, grades 7-12 for math, biology, history, and English. Applications are being accepted for the program now through April 30th.
Responding to a nationally recognized need for computer science curriculum in our public schools, the Bard MAT Program is offering a unique curriculum for math teachers with a commitment to teaching computer science in secondary public schools. The student dedicated to becoming a mathematics and computer science teacher values the Bard MAT Program’s commitment to the discipline with its substantive research projects in mathematics, computer science, and math/cs education. Students will work with computer science teachers in the middle and high schools in New York’s Hudson Valley, preparing for teaching careers in computer science.
The article below describes a political furor over appointing someone to lead an effort to support computing education — who doesn’t herself understand much about computing.
But this is a general problem, and is probably a problem for engineering education, too. Most US politicians in Washington DC don’t have STEM backgrounds. Few know anything about engineering. Fewer still know anything about computer science. Even if they really want to support STEM, engineering, and computing education, not knowing what it is themselves makes it more challenging for them to make good choices.
The row over Tory cronies in taxpayer-backed positions look set to intensify after it emerges the boss of the government’s coding education initiative cannot code — or even give a decent explanation of what is involved. Figures behind the scheme include Michael Gove, who is at the centre of the furore over Conservative placemen in Whitehall and the ‘quangocracy’.
Conservative activist Lottie Dexter was ridiculed by IT experts and educationalists for her clueless performance on Newsnight — in which she claimed that teachers could be trained how to educate students in computer programming “in a day”
It is widely acknowledged that for New York City to prosper in the 21st century, its middle and high schools must teach computer science. What is not so well known is that there are no computer science teachers in New York—at least not on paper.
The state does not recognize computer science as an official subject, which means that teachers do not get trained in it while they are becoming certified as instructors.
That’s one reason public-school students have little exposure to the skills needed to snag computer software programming jobs, which are expected to grow faster than any other profession during the next decade.
Out of 75,000 teachers in New York City public schools, fewer than 100 teach computer science. While state officials are trying to modernize the education syllabus, industry leaders have been filling in the gap with a handful of innovative efforts that illustrate the ad hoc nature of the solution to the shortfall of qualified teachers. But it will be years before all 800 of New York’s middle schools and high schools can offer even a single computer science class.
An interesting blog post by an important CS researcher in programming languages and software engineering, but with a deep misperception about teaching. Teaching is not presentation. Making “production” better doesn’t make the teaching more effective. Student engagement pedagogies are likely to make teaching more effective, but it’s still an open question how to make those happen in a MOOC.
But the presenter of a MOOC is not likely to be a passive player in the same sense. Video is a dynamic medium, that used well can establish a significant emotional connection between the speaker and the audience. This is already clear in some MOOCs, and as production gets better and better this emotional quality of the courses will only improve.
What’s more, MOOC instructors are always at their best. They never have an off day. They never have a pressing grant deadline. All those bad takes got edited out. The students will also always hear them clearly, and when they don’t, the MOOC instructor will patiently repeat what they said. As many times as the student wants.
There’s a new computer science curriculum rolling out in the UK for elementary school students (thanks to the Computing at Schools effort), and Microsoft is making a big push to help the adoption.
Steve Beswick, senior director of Education at Microsoft UK, said: “We welcomed the news of the new computing curriculum alongside others in the industry because it is absolutely critical for the future success of our young people. The challenge now is to ensure that primary teachers are equipped to deliver it by September.”
“That’s why we are launching our First Class Computing programme now, which, through new materials, teacher training, and our ongoing work with the education community, can help a new generation of teachers inspire young people.”