Getting feedback on Teaspoon Languages from CS educators and researchers at the Raspberry Pi Foundation seminar series

In May, I had the wonderful opportunity to speak at the Raspberry Pi Foundation Seminar series. I’ve attended some of these seminars before. I highly recommend them (see past seminars here). It’s a terrific format. The speaker presents for up to a half hour, then everyone gets put into a breakout room for small group discussions. The participants and speaker come back for 30-35 minutes of intensive Q&A — at least, it feels “intensive” from the speaker’s perspective. The questions you get have been vetted through the breakout room process. They’re insightful, and sometimes critical, but always in a constructive way. I was excited about this opportunity because I wanted to make it a hands-on session where the CS teachers and researchers who attended might actually use some Teaspoon Languages and give me feedback on them. I have rarely had the opportunity to work with CS teachers, so I was excited for the opportunity.

Sue Sentance wrote up a very nice blog post describing my talk (thank you!) — see here. The video of the talk and discussion is available. You can watch the whole thing, or, you can read the blog post then skip ahead to where the conversation takes place (around 26:00 in the video). If you have been wondering, “Why isn’t Mark just using Logo, Scratch, Snap, or NetLogo? We already have great tools! Why invent new languages that are clearly less powerful than what we already have?”, then you should jump to 34:38 and see Ken Kahn (inventor of ToonTalk) push me on this point.

The whole experience was terrific for me, and I hope that it’s valuable for the viewer and attendees as well. The questions and comments indicated understanding and appreciation for what I’m trying to do, and the concerns and criticisms are valuable input for me and my team. Thanks to Sue, Diana Kirby, the Raspberry Pi Foundation, and all the attendees!

Learning the Craft of CS Education: Recommending the CS-Ed Podcast

I’ve just finished listening to the first three episodes of the new podcast on CS Education from Dr. Kristin Stephens-Martinez (click here for the podcast homepage). If you teach computer science, I highly recommend it to you. It’s not about CS education per se, except in the sense that research often informs the education topics being discussed. Rather, it’s a nuts-and-bolts discussion of issues relevant to the craft of being a CS educator.

Kristin is terrific as the interviewer on the podcast. She plays all of us — teaching CS, looking for tips, trying to get what she can from these experts.

• The first episode was with David Malan of CS50 at Harvard. It was an in-depth discussion of the tools they’re creating for CS50. I didn’t hear any that I was particularly interested in using, but I did hear about tools that I wanted to recommend to colleagues who teach those topics.
• Dan Garcia of BJC fame at Berkeley was absolutely delightful. He didn’t talk about Snap! or Beauty and Joy in Computing. Rather, he gave a concrete checklist of how to develop good exams in CS. I’m a fan of checklists, and his were great. I’ll definitely use these tips in the future.
• Amy Ko of U.Washington talked about her research, but in really concrete, practitioner-oriented terms. The first part was about how to help students debug. She definitely gave me insights on how to help students develop debugging skills. The second part was about how Donald Knuth was really a qualitative researcher — fascinating stuff.

I’m going to show up later in the series. I don’t know remember what I said! I hope that Kristin is kind to me in the post-production phase, because I don’t think I’m typically as grounded and offering concrete advise as these first three were. I’ll find out in the next few weeks.

TL;DR: If you teach CS, go listen to the CS-Ed podcast. You’ll get something useful out of it that’s worth your time.

What’s unique about CS education compared to other DBERs?

I was recently asked by an NSF program officer to answer the questions, “What makes CS education different than other discipline-based education research (DBER, like math ed, physics ed, or engineering ed)? What research questions might we ask (that we might not currently be asking) to improve practice in CS education?” If I’m going to write a long-form email reply, I might as well make it a blog post. I’m using the specific term, computer science education, not my preferred and more general computing education because the question was framed specifically about CS programs, not necessarily about information technology, information systems, cybersecurity, or other computing programs.

Computer science education research has a quadruple-whammy right now that isn’t facing any other DBER that I know:

• ONE: We know less about how to do CS education well than we know about math, physics, science, or engineering education. A point I made in my SIGCSE keynote is that ASEE is 126 years old, NCTM started in 1920, and AAPT in 1950. CSTA started in 2004. With Ben duBoulay, I wrote the history chapter for the new Handbook of Computing Education Research. The field only dates back to 1967. Because CS is so new, there are few mechanisms to track progress at a systemic level. Most US states don’t gather data on CS like they do reading, science, mathematics, and other school subjects. We have less knowledge of how to teach and what’s going on because we’ve been at it for a shorter time.
• TWO: Below are two slides that I built but decided to edit out of my SIGCSE keynote talk. These are about the relative sizes of CS Ed and other DBER conferences. CS departments are desperately seeking more faculty (see the latest job ads analysis here). We have fewer practitioners and researchers than these other fields.

---

---

---

• THREE: Perhaps a natural consequence of the first two: CS teachers know less of what we do know about evidence-based methods than STEM teachers in other fields. Charles Henderson showed that the vast majority of physics teachers in the US know about evidence-based teaching methods (over 80%) and try to use them (over 60%). Christopher Hovey presented evidence that it’s a small percentage for CS teachers (closer to 10%, see paper here). This might be expected given that we’re new (e.g., haven’t had the time to develop dissemination mechanisms that actually reach teachers) and there are relatively few teachers (compared to other disciplines) so it’s a smaller target to reach.
• FOUR: We are facing enormous economic demand for computer science. Undergraduate University CS enrollments are skyrocketing in the US. There’s a great story and infographic from UNC this last week on their enrollment demands.
  

The result is that we’re providing CS education to many students with few resources (teachers) and without a whole lot of data or use of evidence-based methods. From a research perspective, it’s also interesting that lots of students are resisting CS education — which is pretty common across STEM education. Students complain about algebra, calculus, physics, chemistry, and so on. The interesting twist is that students resisting CS ed are also then resisting the economic benefits, which makes it a bit more intriguing to study. The incentives are there, but many students still find the costs greater than the benefits.

Some of the research questions that I find interesting which are unique to CS education research:

• Why isn’t the enrollment boom extending to high schools?. Undergraduate education is exploding, but over 90% of US high school students are avoiding computer science, even when it’s being offered (which Miranda Parker explored in her dissertation). These are much lower numbers than in other STEM fields. (See blog post here about the low CS numbers in high schools, and this blog post comparing CS to other STEM fields.) We need ethnographic work and design work, to understand what’s going on and to document what might influence students to find CS more attractive.
• What would computing education look like for the other 90%? If we wanted to invent computing education that would reach the rest of US high school students, what would it look like? I suspect that the answer is going to be mostly about integrating CS into other-than-CS classes (like Bootstrap, STEM-CT, and Project GUTS). It’s an issue both of engaging students and getting teachers to adopt. I’m working on task-specific programming with teachers informing the design (see post here), to create programming that they’ll actually adopt and integrate into their non-CS classes. Katie Cunningham is working on inventing CS education that is focused on user needs rather than programming language demands. This is an area where we need a lot of design studies to explore a wide range of possibilities.
• What’s going on in community college CS? I know of studies of CS education at the high school level, the four year college, and the university level. I know of few studies at the community college level. How do they manage the economic imperative of CS education with preparing the students to go on to university? How do they motivate students to complete degrees if students just want to get a good job?
• What’s going on in undergraduate CS classes, especially during the enrollment boom? One of Lecia Barker’s greatest hits was her definition of the “defensive climate,” how students in CS are more about competing than collaborating, and even questions in class are more about showing-off than gaining knowledge. We published a paper that drew on defensive climate research at ITICSE last year (see blog post) — and that was one of the few papers published on the subject since Lecia’s ground-breaking work in 2002-2004. As I search in Google Scholar, I see a couple papers from Colleen Lewis (2011 and 2013), but other than those, there are very few papers testing or extending these notions over the last 15 years. Is “defensive climate” still an issue? I bet it is. How do we test for it? How do we address it? Is there a difference in climate between liberal arts and engineering based CS? How does the climate impact diversity? We have few studies of what’s going on in CS classes under these extreme conditions these days.
• How do we improve teaching quality in CS education? CS education has an issue like Engineering, but unlike science and math. I bet few calculus teachers are seriously swayed by, “How do professional mathematicians use calculus?” But in CS Ed, we’re always swayed by that economic benefit — many CS teachers worry about preparing students for current jobs, for current tools and languages. That focus on industry may inhibit a focus on pedagogy, but that’s a hypothesis to be explored. How do we teach CS teachers to know and use better teaching methods? What influences adoption of new teaching methods? This is particularly an important question in post-secondary where we have such extreme enrollment pressure. When I talk to CS teachers about new methods, the most common response is, “Sure, but when could I learn to do that?!?”
• What influences access to CS education?. When I teach my class on CS education research, I ask my students to identify open research questions. Last semester (see blog post here), a lot of their questions were about access to CS classes, which is complicated by the unique issues of CS education: How do parents’ education level/career influence student choices in CS, e.g. ,to take a CS class, to get a CS degree, to seek a CS job, etc.? Do students with learning disabilities (e.g., dyslexia) view code differently, and does that influence their participation in CS? Could we use fMRI or eye tracking to measure this? Why don’t more lower-income students go into CS, especially since it has such a large economic benefit? What percentage of current CS students are lower-income? How many lower-income students have the opportunity to learn CS and don’t take it?

---

With this post, I’m taking a break from the blog, both for the holidays and to deal with some intense proposal writing. It’s been an exciting year. I’m going to end with a picture from the recent Georgia Tech PhD graduation ceremony. Not only did I get to hood Dr. Miranda Parker, but Barbara and I watched our son, Dr. Matthew Guzdial, get his doctoral hood. It’s a nice bright spot to close out the year. I wish you a happy holiday season and a successful 2020.

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.

 

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.

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.

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.

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.

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.

 

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

High School CS Teacher’s Experience like University CS Teacher’s: “Code Shock”

Jeff Yearout has been teaching for over 25 years, and is just in his second year of teaching CS.  His concerns in his blog echo many of the same ones that I hear from higher-education CS teachers, e.g., dealing with the wide variance of students, and getting all students to engage around code (pseudo or otherwise).

I think one of the hardest things to manage in designing a curriculum is how to dial the difficulty up at a proper pace for the “center mass” of the class skill level. And in this new curriculum from PLTW this particular unit starts out manageable, but suddenly shoots up rapidly, thus the “code shock” mentioned above. I also have the challenge of having a lot of kids in class who simply don’t want to interact in class when, for instance, I’m working through pseudocode on the board.

From “Teaching CS is Hard“

Require CS at University in order to Get CS into K-12 (Revisited)

I wrote a blog post in Blog@CACM in 2011: If You Want High School CS, Require Undergraduate CS.  Everything we’ve seen since then makes me more convinced this is a viable path to providing high-quality CS education for every student.

There is a growing body of evidence that every student at University will need computing. The recent report from Burning Glass and Oracle Academy shows how much in demand CS skills are, far beyond just those who will be professional software developers. Teaching everyone about computing would help in addressing Cathy O’Neill’s calls for more people to be investigating the algorithms controlling our lives. The argument for why University involvement is necessary for K12 CS Ed is based on an observation made recently by Code.org: We are not producing enough CS teachers in University. If everyone took CS at University, that would also reach pre-service teachers. That would make it easier for those teachers to teach CS in the future.

Requiring CS at University may help with the bigger cultural and perception problem.  In England, we see that schools aren’t offering CS even if it’s part of the required curriculum, and students (especially females) aren’t taking it (see the Royal Society report from last month).  The problem is that we’re trying to shoehorn CS into a culture that isn’t asking for it, or rather, the students (and schools) don’t perceive a need for CS. This is a form of the same problem that came up when we were talking about getting more formal methods into software development practice. All professionals should understand the role of computing in our society and how to use computing as a literacy: To express ideas, to share ideas, and to use in developing ideas.

Schools follow society. Society is rarely (if ever) changed by schooling. If you want a computationally literate society, convince the adults. If most professionals use computing, the same professionals that students want to be like, then there is a social reason to learn computing. Social demand to prepare K-12 students in that literacy makes it more likely for that literacy to succeed in K-12 education.  Trying to teach all students something that society doesn’t value for everyone is counter to situated learning theory.  Students (even K-12 students) are engaged in legitimate peripheral participation — their “job” is to figure out what is expected of them in society. If they don’t see computational literacy broadly in society, students don’t get the message that it’s important for everyone to learn.

When I make this suggestion to University faculty, I often hear the argument, “Anything you require of students, they will hate.” Then they tell me an anecdote of some student who hated a requirement, or of some personal experience of a class they hated. I know of no empirical evidence that says that this is generally true. We do have empirical evidence that says it’s false. Mike Hewner’s work found that US students take required classes in order to discover what they like, and they make curricular choices based on what they like.

We are already seeing students from all over campus flooding into our classes (see the Generation CS report and the National Academies report). We are already learning how to manage the load. It’s already happening in some Universities that most or all students at University are taking CS. Why not require it so that we get the Education students who we may not be seeing yet in CS classes?

Instead of using Universities to make CS education work, we are pouring money into CS Ed via in-service professional development — a tenfold increase in England, and $1.5B in the next five years in the US.  In general, more money in education alone doesn’t change things. We have to think about systems, policies, and our educational ecosystem. Universities are part of that educational ecosystem.

Universities play a role in K-12 education in all other subjects. We have to involve them in order to create sustainable K-12 Computer Science education.

Universities aren’t preparing enough computer science teachers, and we have no path to get there

Not really a surprising claim, but I still think that we’re not talking enough about this. No K-12 subject is taught nationwide without producing teachers from universities. We simply cannot create sustainable K-12 CS education without universities producing CS teachers (called “pre-service teacher professional development”). Currently, we produce new CS teachers by recruiting existing teachers from other subjects (called “in-service teacher professional development”). None of our models for growing CS nationwide currently have a plan to replace in-service with pre-service (as described in this blog post).

Looking for answers, we examined the state-by-state data on the number of graduates prepared to teach various subjects. We found that in 2016, only 75 teachers graduated from universities equipped to teach computer science. Compare that to the number of graduating teachers prepared in mathematics (12,528) and the sciences (11,917 across general science, biology, chemistry, physics, and earth science).

Source: Universities aren’t preparing enough computer science teachers

More Teachers, Fewer 3D Printers: How to Improve K–12 Computer Science Education

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.”

Source: More Teachers, Fewer 3D Printers: How to Improve K–12 Computer Science Education – IEEE Spectrum

Preparing Tomorrow’s Faculty to Address Challenges in Teaching Computer Science

I’ve blogged here when we have opened registration for the New Computing Faculty workshops (e.g., here), but I haven’t really explained why we’re doing them.  We took a lot of grief on Twitter for the workshops in the Spring, and 120 characters just isn’t enough to explain the whole story. We (Leo Porter, Cynthia Lee, Beth Simon, and me) wrote an article that appeared in the May CACM explaining the rationale.  If you don’t have ACM Digital Library access, you can grab the paper from my Guzdial Papers page here in the blog.

The new challenges compound existing teaching-related challenges for the field. We still need to broaden participation in our field, with the lowest percentage of women majors in all of STEM. The economic rewards of a computing career make it even more important to bridge the digital divide. If there are more students than faculty can teach effectively, they may be inclined to lean on a pessimistic belief that success is dependent on “brilliance” and innate ability where only a subset of students can succeed. If CS faculty feel there is little they can do to change students’ outcomes in their individual classrooms, it will be true. Research shows that more CS faculty hold this mistaken and unproductive view of students than faculty in other STEM disciplines.

Source: Preparing Tomorrow’s Faculty to Address Challenges in Teaching Computer Science | May 2017 | Communications of the ACM

Registration open for New Computing Faculty Workshops in Summer 2017

Beth, Cynthia, Leo, and I are running our workshop for new CS faculty again this summer.  Registration is open. Please do pass on word!

The third New Computing Faculty Workshop will be held August 6-8, 2017 in San Diego. The goal of the workshop is to help computing faculty at research intensive universities to be better and more efficient teachers.  By learning a little about teaching, we will help new faculty (a) make their teaching more efficient and effective (e.g., students learn more with less input time from faculty) and (b) make their teaching more enjoyable. The workshops were described in Communications of the ACM in the May 2017 issue (see article here). The workshop will be run by Beth Simon (UCSD), Cynthia Bailey Lee (Stanford), Leo Porter (UCSD), and Mark Guzdial (Georgia Tech).

Source: New Computing Faculty Workshops in Summer 2017 – CRA

We need a greater variety of CS teaching methods: The Way We Teach Math Is Holding Women Back

As I often do, I was trying to convince my colleagues that there is no “Geek Gene.”  One of them agreed that there is no Geek Gene.  But still…some people can’t learn CS, he insisted.  He pointed out that some people take a class “6-8 times to pass it.”

That got me thinking about the evidence he offered.  If someone takes the same course six times and can’t pass, does that mean that the student can’t learn CS?

Or maybe it proves that we’re insane, if Einstein’s famous quote is right (“Insanity: doing the same thing over and over again and expecting different results.”)  If the problem is our teaching and learning methods, simply repeating the exact same methods six times is not going to work.  Think about in terms of teaching reading.  We recognize that we need a variety of methods for teaching reading.  Having a dyslexic person take the exact same mainstream class six times will simply not work.

Why we are so resistant (as in the mathematics story linked below) to consider alternative teaching methods in CS?

The irony of the widespread emphasis on speed in math classrooms, with damaging timed tests given to students from an early age, is that some of the world’s most successful mathematicians describe themselves as slow thinkers. In his autobiography, Laurent Schwartz, winner of the world’s highest award in mathematics, described feeling “stupid” in school because he was a slow thinker. “I was always deeply uncertain about my own intellectual capacity; I thought I was unintelligent,” he wrote. “And it is true that I was, and still am, rather slow. I need time to seize things because I always need to understand them fully.”

When students struggle in speed-driven math classes, they often believe the problem lies within themselves, not realizing that fast-paced lecturing is a faulty teaching method. The students most likely to internalize the problem are women and students of color. This is one of the main reasons that these students choose not to go forward in mathematics and other STEM subjects, and likely why a study found that in 2011, 74% of the STEM workforce was male and 71% was white.

Source: Jo Boaler on Women in STEM, Ivanka Trump and Betsy DeVos – Motto