Posts tagged ‘teachers’

Why don’t high schools teach CS: It’s the lack of teachers, but it’s way more than that (Miranda Parker's dissertation)

Back in October, I posted here about Miranda Parker’s defense. Back then, I tried to summarize all of Miranda’s work as a doctoral student in one sentence:

Readers of this blog will know Miranda from her guest blog post on the Google-Gallup polls, her development of SCS1 as a replication of a multi-lingual and validated measure of CS1 knowledge, the study she did of teacher-student differences in using ebooks, and her work exploring the role of spatial reasoning to relate SES and CS performance (work that was part of her dissertation study).

That was a seriously run-on sentence for an impressive body of work.

On Friday, December 13, I had the great honor of placing an academic hood on Dr. Parker*.

I haven’t really talked too much about Miranda’s dissertation findings yet. I really want to, but I also don’t want to steal the thunder from her future publications. So, with her permission, I’m going to just summarize some of my favorite parts.

First, Miranda built several regression models to explain Georgia high schools teaching computer science in 2016. I predicted way back at her proposal that the biggest factor would be wealth — wealthy schools would teach CS and poorer schools wouldn’t. I was wrong. Yes, that’s a statistically significant factor, but it doesn’t explain much.

The biggest factor is…teaching computer science in 2015. Schools that taught CS in 2015 were many times more likely to be teaching in 2016. Schools have to get started! Hadi Partovi made this argument to me once, that getting started in schools was the biggest part of the battle. Miranda’s model supports his argument. There’s much more to the story, but that’s the biggest takeaway for me on the quantitative analysis.

But her model only explains a bit over 50% of the variance. What explains the rest? We figured that there would be many different factors. To make it manageable, Miranda chose just four high schools to study as case studies where she did multiple interviews. All four of the schools were predicted by her best model to teach computer science, but none of the did.

Yes, as you’d expect, access to a teacher is the biggest factor, but it’s not as simple as just deciding to hire a CS teacher or train an existing teacher to teach CS. For example, one principal laid out for Miranda who could teach CS and who would take their class, and how to fill that gap in the schedule, and so on. In the end, he had a choice of offering choir or offering CS. There were students in choir. CS was a gamble. It wasn’t even a hard decision for that principal.

Here is the story that most surprised me. At two of the schools Miranda studied, they teach lots of cyber security classes, but no computer science. As you would expect, there was a good bit of CS content in the cybersecurity classes. They had the teachers. Why not then teach CS, too?

Because both of these schools were near Fort Gordon which has a huge cybersecurity district. Cybersecurity is a community value. It’s a sure thing when it comes to getting a job. What’s “computer science” in comparison?

In my opinion, there is nothing like Miranda’s study in the whole world. There are the terrific Roehampton reports that give us a quantitative picture about CS in all of England. There are great qualitative studies like Stuck in the Shallow End that tell us what’s going on in high schools. Miranda did both and connected them — the large scale quantitative analysis, and then used that to pick four interesting high schools to dig into for qualitative analysis. It’s a story specific to Georgia, and each US state is going to be a different story. But it’s a whole state, the right level of analysis in the US. It’s a fascinating story, and I’m proud that she pulled it off.

Keep an eye out for her publications about this work over the next couple years.

* By the way, Dr. Parker is currently on the academic job market.

December 16, 2019 at 8:00 am 6 comments

What’s generally good for you vs what meets a need: Balancing explicit instruction vs problem/project-based learning in computer science classes

Lauren Margulieux has posted another of her exceptionally interesting journal article summaries (see post here). Her post summarizes recent article asking which is more effective: Direct instruction or learning through problem-solving-first (like in project-based learning or problem-based learning — or just about any introductory computer science course in any school anywhere)? Direct instruction won by a wide margin.

Lauren points out that there are lots of conditions when problem-solving-first might make sense. In more advanced classes where students have lots of expertise, we should use a different teaching strategy than what we use in introductory classes. When the subject matter isn’t cognitively complex (e.g., memorizing vocabulary words), there is advantages to having the students try to figure it out themselves first. Neither of these conditions are true for introductory computer science.

This is an on-going discussion in computing education. Felienne Hermans had a keynote at the 2019 RStudio Conference where she made an argument for explicit direct instruction (see link here). I made an argument for direct instruction in Blog@CACM last November (see post here). Back in 2017, I recommended balancing direct instruction and projects (see post here), because projects are clearly more motivating and authentic for computer science students, while the literature suggest that direct instruction leads to better learning — even of problem-solving skills.

Lately, I’ve been thinking about this question with a health metaphor. Let me try it here:

Everybody should exercise, right? Exercise provides a wide variety of benefits (listed in a fascinating blog post from Freakonomics from this June), including cardiovascular improvements, better aging, better sleep, and less stress. But if you have a heart problem, you’re going to get treatment for that, right? If you’re having high cholesterol, you should continue to exercise (or even increase it), but you might also be prescribed a statin.  If you have a specific need (like a vitamin deficiency), you address that need.

Students in computing should work on projects. It’s authentic, it’s motivating, and there are likely a wide range of benefits. But if you want to gain specific skills, e.g., you want to achieve learning objectives, teach those directly. Don’t just assign a big project and hope that they learn the right things there. If you want to see specific improvement in specific areas, teach those. So sure, assign projects — but in balance. Meet the students’ needs AND give them opportunities to practice project skills.

And when you teach explicitly: Always, ALWAYS, ALWAYS use active learning techniques like peer instruction. It’s simply unethical to lecture without active learning.

September 16, 2019 at 7:00 am 6 comments

How the Cheesecake Factory is like Healthcare and CS Education

Stephen Dubner of the Freakonomics Podcast did an interview with Atul Gawande, author of the Checklist Manifesto. Atul is a proponent of a methodical process — from a behavioral economist perspective, not from an optimization perspective. People make mistakes, and if we’re methodical (like the use of checklists), we’re less likely to make those mistakes. If we can turn our process into a “recipe,” then we will make fewer mistakes and have more reliable results. Here’s a segment of the interview where he argues for that process in healthcare.

DUBNER: Okay, what’s the difference between a typical healthcare system and say, a restaurant chain like the Cheesecake Factory?

GAWANDE: You’re referring to the article I wrote about the Cheesecake Factory…Basically what I was talking about was the idea that, here’s this restaurant chain. And yes, it’s highly caloric, but the Cheesecake Factorys here have as much business as a medium-sized hospital — $100 million in business a year. And they would cook to order every meal people had. And in order to make that happen, they have to run a whole process that they have real cooks, but then they have managers.

I was talking to one of the managers there about how he would make healthcare work. And his answer was, “Here’s what I would do, but of course you guys do this. I would look to see what the best people are doing. I would find a way to turn that into a recipe, make sure everybody else is doing it, and then see how far we improve and try learning again from that.” He said, “You do that, right?” And we don’t. We don’t do that.

Here’s where Gawande’s approach ties to education. Later in the interview:

DUBNER: And do you ever in the middle of, let’s say, a surgery think about, “Oh, here’s what I will be writing about this day?”

GAWANDE: You know, I don’t really; I’m in the flow. One of the things that I love about surgery is: it is, I have to confess, the least stressful thing I do, because at this point I’ve done thousands of the operations I do. Ninety-seven to 98 percent go pretty much as expected, and the 2 percent that don’t, I know the 10 different ways that are most common that they’ll go wrong and I have approaches to it. So it’s kind of freeing in a certain way.

I think about teaching like this. I have been teaching computing since 1980. I actively seek out new teaching methods. Teaching CS is fun for me — because I know lots of ways to do it, I have choices which keeps it interesting. I have mentioned the fascinating work on measuring teacher PCK (Pedagogical Content Knowledge) by checking how accurately teachers can predict how students will get exam questions wrong. I know lots of ways students can get computer science wrong. I still get surprises, but because I’m familiar with how students can get things wrong, I have a starting place for supporting students in constructing stronger conceptions.

We can teach this. The model of expertise that Gawande describes is achievable for CS teachers. We can teach new CS teachers methods that they can choose from. We can teach them common student mental models of programming, how to diagnose weaker understandings, and ways to help them improve their mental models. We can make a checklist of what a CS teacher needs to know and be able to do.

September 2, 2019 at 7:00 am 8 comments

Why high school teachers might avoid teaching CS: The role of industry

Fascinating blog post from Laura Larke that helps to answer the question: Why isn’t high school computing growing in England?  The Roehampton Report (pre-release of the 2019 data available here) has tracked the state of computing education in England, which the authors describe as a “steep decline.” Laura starts her blog post with the provocative question “How does industry’s participation in the creation of education policy impact upon what happens in the classroom?” She describes teachers who aim to protect their students’ interests — giving them what they really need, and making judgments about where to allocate scarce classroom time.

What I found were teachers acting as gatekeepers to their respective classrooms, modifying or rejecting outright a curriculum that clashed with local, professional knowledge (Foucault, 1980) of what was best for their young students. Instead, they were teaching digital skills that they believed to be more relevant (such as e-safety, touch typing, word processing and search skills) than the computer-science-centric content of the national curriculum, as well as prioritising other subjects (such as English and maths, science, art, religious education) that they considered equally important and which competed for limited class time.

Do we see similar issues in US classrooms?  It is certainly the case that the tech industry is painted in the press as driving the effort to provide CS for All.  Adam Michlin shared this remarkable article on Facebook, “(Florida) Gov. DeSantis okay with substituting computer science over traditional math and science classes required for graduation.” Florida is promoting CS as a replacement for physics or pre-calculus in the high school curriculum.

“I took classes that I enjoyed…like physics. Other than trying to keep my kids from falling down the stairs in the Governor’s mansion I don’t know how much I deal with physics daily,” the governor said.

The article highlights the role of the tech industry in supporting this bill.

Several top state lawmakers attended as well as a representative from Code.org, a Seattle-based nonprofit that works to expand computer science in schools. Lobbyists representing Code.org in Tallahassee advocated for HB 7071, which includes computer science initiatives and other efforts. That’s the bill DeSantis is reviewing.

A Microsoft Corporation representative also attended the DeSantis event. Microsoft also had lobbyists in Tallahassee during the session, advocating for computer science and other issues.

The US and England have different cultures. Laura’s findings do not automatically map to the US. I’m particularly curious if US teachers are similarly more dubious about the value of CS curricula if it’s perceived as a tech industry ploy.

 

July 29, 2019 at 7:00 am 3 comments

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

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