Posts tagged ‘teachers’

Computer Science Teachers as Provocateurs: All learning starts from a problem

One of the surprising benefits of working with social science educators (history and economics) has been new perspectives on my own teaching. I’ve studied education for several years, and have worked with science and mathematics education researchers in the past. It hadn’t occurred to me that history education is so different that it would give me a new way of looking at my own teaching.

Last week, I was in a research meeting with Bob Bain, a history and education professor here at U. Michigan. He was describing how historians understand knowledge and what historian’s practice looks like, and how that should be reflected in the history classroom.

He said that all learning in history starts from a problem. That gave me pause. What’s a “problem” in history?

Bob explained that he defines problem as John Dewey did, as something that disturbs the equilibrium. “Activities at the Dewey School arose from the child’s own interests and from the need to solve problems that aroused the child’s curiosity and that led to creative solutions.” We don’t think until our environment is disturbed, but that environment may just be in your own head.

We each have our own stories that we use to explain the world, and these make up our own personal equilibria. Maybe students have always been told that the American Civil War was about states’ rights, and then they read the Georgia Declaration of Secession. Maybe they’ve thought of Columbus as the explorer who discovered America, and then note that he wasn’t celebrated until 1792, 300 years after his arrival. Why wasn’t he celebrated earlier, and why him and at that time? A good history teacher sets up these conflicts, disequilibria, or problems. Bob says it can be easy enough to create, simply by showing two contrasting accounts of the same historical event.

Research in the learning sciences supports this definition of learning. Roger Schank talked about the importance of learning through “expectation failure.” You learn when you realize that you don’t know something:

The understanding cycle – expectation failure – explanation – reminding – generalization – is a natural one. No one teaches it to us. We are not taught to have goals, nor to attempt to develop plans to achieve those goals by adapting old plans from similar situations. We need not be taught this because the process is so basic to what comprises intelligence. Learning is a natural act.

In progressive education, we’re told that the teacher should be a “Guide on the Side, not the Sage on the Stage.” When Janet Kolodner was developing Learning By Design, she talked about the role of teacher as coach and orchestrator. Those were roles I was familiar with. Bob was describing a different role.

I challenged him explicitly, “You’re a provocateur. You create the problems in the students’ minds.” He agreed.

Bob got me thinking about the role of the teacher in the computer science class. We can sometimes be a guide, a coach, and orchestrator — when students are working away on some problem or project. But sometimes, we have to be the provocateur.

We should always start from a problem. In science education, this is easy. Kids naturally do wonder why the sky is blue, why sunsets are more red, why heat travels along metal but not wood, and why stars twinkle. In more advanced computer science, we can also start from questions that students’ already have. I’m taking a MOOC right now because it explains things I’ve wondered about.

But in introductory classes, students already use a computer without problems. They may not see enough of real computing to wonder about how it works. The teacher has to generate a problem, inculcate curiosity — be a provocateur.

We should only teach something when it solves a problem for the student. A lecture on variables and types should be motivated by a problem that the variables and types solve. A lecture on loops should happen when students need to do something so often that copy-pasting the code repeatedly won’t work. Saying “You’re going to need this later” is not motivation enough — that doesn’t match the cycle that Schank described as natural. Nobody remembers things they will need in the future. Learning results when you need new knowledge to resolve the current problem, disequilibria, or conflict.

Note: Computer science doesn’t teach problem-solving. Dewey’s and Schank’s point is that problem-solving is a natural way in which people learn. Learning to program still doesn’t teach problem-solving skills.

June 10, 2019 at 7:00 am 1 comment

Using MOOCs for Computer Science Teacher Professional Development

When our ebook work was funded by IUSE, our budget was cut from what we proposed. Something had to be dropped from our plan of work. What we dropped was a comparison between ebooks and MOOCs. I had predicted that we could get better learning and higher completion rates from our ebooks than from our MOOCs. That’s the part that got dropped — we never did that comparison.

I’m glad now. It’s kind of a ridiculous comparison because it’s about the media, not particular instances. I’m absolutely positive that we could find a terrible ebook that led to much worse results than the absolutely best possible MOOC, even if my hypothesis is right about the average ebook and the average MOOC. The medium itself has strengths and weaknesses, but I don’t know how to experimentally compare two media.

I’m particularly glad since I wouldn’t want to go up against Carol Fletcher and her creative team who are finding ways to use MOOCs successfully for CS teacher PD. You can find their recent presentation “Comparing the Efficacy of Face to Face, MOOC, and Hybrid Computer Science Teacher Professional Development” on SlideShare:

Carol sent me a copy of the paper from  the 2016″Learning with MOOCs” conference*. I’m quoting from the abstract below:

This research examines the effectiveness of three primary strategies for increasing the number of teachers who are CS certified in Texas to determine which strategies are most likely to assist non-CS teachers in becoming CS certified. The three strategies compared are face-to-face training, a MOOC, and a hybrid of both F2F and MOOC participation. From October 2015, to August of 2016, 727 in-service teachers who expressed an interest in becoming CS certified participated in one of these pathways. Researchers included variables such as educational background, teaching certifications, background in and motivation to learn computer science, and their connection to computer science through their employment or the community at large as covariates in the regression analysis. Findings indicate that the online only group was no less effective than the face-to-face only group in achieving certification success. Teachers that completed both the online and face-to-face experiences were significantly more likely to achieve certification. In addition, teachers with prior certification in mathematics, a STEM degree, or a graduate degree had greater odds of obtaining certification but prior certification in science or technology did not. Given the long-term lower costs and capacity to reach large numbers that online courses can deliver, these results indicate that investment in online teacher training directed at increasing the number of CS certified teachers may prove an effective mechanism for scaling up teacher certification in this high need area, particularly if paired with some opportunities for direct face-to-face support as well.

That they got comparable results from MOOC-based on-line and face-to-face is an achievement. It matches my expectations that a blended model with both would be more successful than just on-line.

Carol and team are offering a new on-line course for the Praxis test that several states use for CS teacher certification. You can find details about this course at https://utakeit.stemcenter.utexas.edu/foundations-cs-praxis-beta/.


* Fletcher, C., Monroe, W., Warner, J., Anthony, K. (2016, October). Comparing the Efficacy of Face-to-Face, MOOC, and Hybrid Computer Science Teacher Professional Development. Paper presented at the Learning with MOOCs Conference, Philadelphia, PA.

March 29, 2019 at 7:00 am 1 comment

The Ground Truth of Computing Education: What Do You Know?

Earlier this month, I was a speaker at a terrific event at Cornell Tech To Code & Beyond: Thinking & Doing organized by Diane Levitt (see Tweet here). I spoke, and then was on a panel with Kelly Powers, Thea Charles, Aman Yadav, and Diane to discuss what is Computational Thinking.

One of the highlights of the day for me was listening to Margaret Honey, a legendary educational technology designer and researcher (see bio here). She is President and CEO of the New York Hall of Science. One of my favorite parts of her talk was a description of the apps that they’re building to get kids to notice and measure things in their world. I even love the URL for their tools — https://noticing.nysci.org/

At the event, Diane mentioned that she was working on a blog post about her “ground truth” — what she most believed about CS education. She shared it as a tweet right after the event. It’s lovely and deep — find it here.

A couple of my favorite of her points:

Students thrive when we teach at the intersection of rigor and joy. In computer science, it’s fun to play with the real thing. But sometimes we water it down until it’s too easy—and kids know it. Struggle itself will not turn kids away from computer science. They want relevant learning experiences that lead to building things that matter to them. “I can do hard things!” is one of the most powerful thoughts a student can have.

The biggest lever we have is the one we aren’t using enough yet: preservice education for new teachers. The sooner we start teaching computer science education alongside the teaching of math and reading, during teachers’ professional preparation programs, the sooner we get to scale. It’s expensive and time-consuming to continually retool our workforce. Eventually, if every teacher enters the classroom prepared to include computer science, every student will be prepared for the digital world in which they live. This is what we mean by equity: equal access for every student, regardless of geography, gender, income, ability, or, frankly, interest.

Sara Judd answered Diane’s post with one of her own — find it here. I really enjoy it because she sees computer science like I do. It’s not just about problem-solving, but also about making things and connecting to the world.

Programming makes things.

While programming for it’s own sake can be fun for some people, (me, for instance) generally when people are programming it is because there is a thing that needs to be made. These things can be expressive pieces of visual art or music. These things can be silly fun for fun’s sake. These things can revolutionize the world, they can make our lives easier. The important thing is, they are “things.” CS doesn’t exist in a vacuum. Therefore, classroom CS should not exist in a vacuum.

I encourage more of us to do this — to write down what we believe about CS education, then share the essays. It’s great to hear goals and perspectives, both to learn new ones and also to recognize that others share how we think about it. I particularly enjoy reading these from people with different life experiences. I have a privileged life as a University CS professor. Teachers in K-12 struggle with very different things. I’m so pleased when I find that we still have similar goals for and perspectives about CS education.

January 28, 2019 at 7:00 am 1 comment

Do we know how to teach secure programming to K-12 students and end-user programmers?

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.

January 14, 2019 at 7:00 am 16 comments

Analyzing CS in Texas school districts: Maybe enough to take root and grow

My Blog@CACM for this month is about Code.org’s decision to shift gradually the burden of paying for CS professional development to the local regions — see link here.  It’s an important positive step that needs to happen to make CS sustainable with the other STEM disciplines in K-12 schools.

We’re at an interesting stage in CS education. 40-70% of high schools have CS, but the classes are pretty empty.  I use Indiana and Texas as examples because they’ve made a lot of their data available.  Let’s drill a bit into the Texas data to get a flavor of it, available here.  I’m only going to look at Area 1’s data, because even just that is deep and fascinating.

Brownsville Intermediate School District. 13,941 students. 102 in CS.

Computer_Science_Regional_Data___STEM_Center___The_University_of_Texas_at_Austin

Of the 10 high schools in Brownsville ISD, only two high schools have anyone in their CS classes.  Brownsville Early College High School has 102 students in CS Programming (no AP CS Level A, no AP CSP).  That probably means that one teacher has several sections of that course — that’s quite a bit.  The other high school, Porter Early College High School has fewer than five students in AP CS A.  My bet is that there is no CS teacher there, only five students doing an on-line class.  That means for 10 high schools and 13K students, there is really only one high school CS teacher.

Edinburg Consolidated Independent School District, over 10K students, 92 students in CS.

Computer_Science_Regional_Data___STEM_Center___The_University_of_Texas_at_Austin-3

This is a district that could grow CS if there was will.  There are 6 high schools, but two are special cases: One with less than 5 students, and the other in a juvenile detention center.  The other four high schools are huge, with over 2000 students each.  In Economedes, that are only 9 students in AP CS A — maybe just on-line?  Edinburg North and Robert R Vela high school each have two classes: AP CS A and CS1.  With 21 and 14, I’m guessing two sections.  The other has 43 and 6. That might be two sections of AP CS A and another of CS1, or two sections of AP CS A and 6 students in an on-line class.  In any case, this suggests two high school CS teachers (maybe three) in half of the high schools in the district.  Those teachers aren’t teaching only CS, but with increased demand and support from principals, the CS offerings could grow.

It’s fascinating to wander through the Texas data, to see what’s there and what’s not.  I could be wrong about what’s there, e.g., maybe there’s only one teacher in Edinburg and she’s moving from school-to-school.  Given these data, there’s unlikely to be a CS teacher in every high school, who just isn’t teaching any CS. These data are a great snapshot. There is CS in Texas high schools, and maybe there’s enough there to take root and grow.

 

October 19, 2018 at 7:00 am 2 comments

CRA Memo on Best Practices for Engaging Teaching Faculty in Research Computing Departments

I’m excited to see this memo from the Computing Research Association on the status of teaching faculty in computing departments. Computing departments are increasingly relying on teaching faculty, and it’s important to give them fair and equitable treatment.

I wrote in 2016 that “CS Teaching Faculty are like Tenant Farmers.” This memo addresses some of the issues I raised, though some are buried in the text of the memo.  I argued that teaching faculty should be involved in hiring for both traditional and teaching faculty, and that teaching faculty should serve in upper-level leadership positions.  The report does state halfway down the report, “Similarly, teaching faculty should be broadly included in faculty governance on matters related to their roles in the department, including participation in faculty meetings, voting rights on matters impacting the education mission, inclusion in evaluation of the teaching performance of other faculty, and input on hiring decisions.”  This memo is a step in the right direction.

To achieve their educational mission, computing departments at research universities increasingly depend on full-time teaching faculty who choose teaching as a long-term career. This memo discusses the need for teaching faculty, explores the impact of teaching faculty, and recommends best practices.

Essential best practices for departments include:

  • Departments should provide teaching faculty with equitable rights and resources, except in limited areas where differing job responsibilities make that inappropriate.

  • Departments should encourage teaching faculty to be equal and active partners on projects and committees with the goal of contributing to the department’s educational mission.

  • Departments should set course, preparation, student, and service loads of teaching faculty at a level that allows for innovation and quality instruction.

    ….

Source: Laying a Foundation: Best Practices for Engaging Teaching Faculty in Research Computing Departments

August 17, 2018 at 7:00 am 6 comments

The Story of MACOS: How getting curriculum development wrong cost the nation, and how we should do it better

Man: A Course of Study (MACOS) is one of the most ambitious US curriculum efforts I’ve ever heard about. The goal was to teach anthropology to 10 year olds. The effort was led by world-renowned educational psychologist Jerome Bruner, and included many developers, anthropologists, and educational psychologists (including Howard Gardner). It won awards from the American Education Research Association and from other education professional organization for its innovation and connection to research. At its height, MACOS was in thousands of schools, including whole school districts.

Today, MACOS isn’t taught anywhere. Funding for MACOS was debated in Congress in 1975, and the controversy led eventually to the de-funding of science education nationally.

Peter Dow’s 1991 book Schoolhouse Politics: Lessons from the Sputnik Era is a terrific book which should be required reading for everyone involved in computing education in K-12. Dow was the project manager for MACOS, and he’s candid in describing what they got wrong. It’s worthwhile understanding what happened so that we might avoid it in computing education. I just finished reading it, and here are some of the parts that I found particularly insightful.

First, Dow doesn’t dismiss the critics of MACOS. Rather, he recognizes that the tension is between learning objectives. What do we want for our children? What kind of society do we want to build?

I quickly learned that decisions about educational reform are driven far more by political considerations, such as the prevailing public mood, than they are by a systematic effort to improve instruction. Just as Soviet science supremacy had spawned a decade of curriculum reform led by some of our most creative research scientists during the late 1950s and 1960s, so now a new wave of political conservatism and religious fundamentalism in the early 1970s began to call into question the intrusion of university academics into the schools…Exposure to this debate caused me to recast the account to give more attention to educational politics. No discussion of school reform, it seems, can be separated from our vision of the society that the schools serve.

MACOS was based in the best of educational psychology at the time. Students engaged in inquiry with first-hand accounts, e.g., videos of Eskimos. The big mistake the developers made was they gave almost no thought to how it was going to get disseminated. Dow points out that MACOS was academic researchers intruding into K-12, without really understanding K-12. They didn’t plan for teacher professional development, and worse, didn’t build any mechanism for teachers to tell them how the materials should be changed to work in real classrooms. They were openly dismissive of the publishers who might get the materials into the world.

On teachers: There was ambivalence about teachers at ESI. On the one hand the Social Studies Program viewed its work as a panacea for teachers, a liberation from the drudgery of textbook materials and didactic lessons. On the other, professional educators were seen as dull-witted people who conversed in an incomprehensible “middle language” and were responsible for the uninspired state of American education.

On publishers: These two experienced and widely respected publishing executives listened politely while Bruner described our lofty education aspirations with characteristic eloquence, but the discussion soon turned to practical matters such as the procedures of state adoption committees, “tumbling test” requirements, per-pupil expenditures, readability formulas, and other restrictions that govern the basal textbook market. Spaulding and Kaplan tried valiantly to instruct us about the realities of the educational publishing world, but we dismissed their remarks as the musings of men who had been corrupted by commercialism. Did they not understand that our mission was to change education, not submit to the strictures that had made much of instruction so meaningless? Could not men so powerful in the publishing world commit some of their resources to support curriculum innovation? Had they no appreciation of the intellectual poverty of most social studies classrooms? I remember leaving that room depressed by the monumental conservatism of our visitors and more determined than ever to prove that there were ways to reach the schools with good materials. Our arrogance and naivete were not so easily cured.

By 1971, Dow realizes that the controversies around MACOS could easily have been avoided. They had made choices in their materials that highlighted the challenges of Eskimo life graphically, but the gory details weren’t really necessary to the learning objectives. They simply hadn’t thought enough about their users, which included the teachers, administrators, parents, and state education departments.

My favorite scene in the book is with Margaret Mead who tries to help Dow defend MACOS in Congress, but she’s frustrated by their arrogance and naivete.

Mead’s exasperation grew. “What do you tell the children that for?…I have been teaching anthropology for forty years,” she remarked, “and I have never had a controversy like this over what I have written.”

But Mead’s anger quickly returned. “No, no, you can’t tell the senators that! Don’t preach to them! You and I may believe that sort of thing, but that’s not what you say to these men. The trouble with you Cambridge intellectuals is that you have no political sense!”

Dow describes over two chapters the controversies around MACOS and the aftermath impacts on science education funding at NSF. But he also points out the problems with MACOS as a curriculum. Some of these are likely problems we’re facing in CS for All efforts.

For example, he talks about why MACOS was removed from Oregon schools, using the work of Lynda Falkenstein. (Read the below with an awareness of the Google-Gallup and EdWeek polls showing that administrators and principals are not supportive of CS in schools.)

She concluded that innovations that lacked the commitment of administrators able to provide long-term support and continuing teacher training beyond the initial implementation phase were bound to faster regardless of their quality. Even more than controversy, she found, the greatest barrier to successful innovation was the lack of continuity of support from the internal structure of the school system itself.

I highly recommend Schoolhouse Politics. It has me thinking about what it really takes to get any education reform to work and to scale. The book is light on evaluation evidence that MACOS worked. For example, I’m concerned that MACOS was so demanding that it may have been too much for underprepared students or teachers. I am totally convinced that it was innovative and brilliant. One of the best curriculum design efforts I’ve ever read about, in terms of building on theory and innovative design. I am also totally convinced that it wasn’t ready to scale — and the cost of that mistake was enormous. We need to avoid making those mistakes again.

June 18, 2018 at 7:00 am 6 comments

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