SIGCSE 2019 Papers from the Blogosphere

I’m gathering blog posts from others about their SIGCSE 2019 papers. Here’s what I’ve got:

From Katie Rich:

https://katiethecurious.com/2019/02/24/new-paper-debugging-lt/

Rich, K. M., Strickland, C., Binkowski, T. A., & Franklin, D. (2019). A K – 8 debugging learning trajectory derived from research literature. In Proceedings of the 2019 ACM SIGCSE Technical Symposium on Computer Science Education (pp. 745–751). New York: ACM.

From Shuchi Grover:

http://www.shuchigrover.com/countdown-to-the-50th-sigcse-in-minneapolis/

(Paper) Non-Programming Activities for Engagement with Foundational Concepts in Introductory Programming (Shuchi Grover, Nicholas Jackiw, & Patrik Lundh) | Mar 2, 12 – 12:30pm, Hyatt: Greenway B/C (2nd floor)

(Poster) Integrating Computational Thinking in Informal and Formal Science and Math Activities for Preschool Learners (Shuchi Grover, Ximena Dominguez, Danae Kamdar, Phil Vahey, Savitha Moorthy, Sara Gracely & Ken Rafanan) | Mar 1, 10am-noon, Hyatt Exhibit Hall

(Demo) Integrating Computational Modeling in K-12 STEM Classrooms (Gautam Biswas, Nicole Hutchins, Akos Ledeczi, Shuchi Grover & Satabdi Basu) | Feb 28, 10-10:45am, Hyatt Exhibit Hall

(Lightning Talk): Thinking about Computational Thinking: Lessons from Education Research (Shuchi Grover) | Feb 28, 4pm, Hyatt Lake Bemidji (4th Floor)

From Brett Becker

First Things First: Providing Metacognitive Scaffolding for Interpreting Problem Prompts. 

https://cszero.wordpress.com/2019/02/27/sigcse-2019-best-computer-science-education-research-paper/

50 Years of CS1 at SIGCSE: A Review of the Evolution of Introductory Programming Education Research

https://cszero.wordpress.com/2019/02/27/50-years-of-cs1-at-sigcse-a-review-of-the-evolution-of-introductory-programming-education-research/

From Austin Cory Bart

https://acbart.github.io/python-sneks/interventions.html

PythonSneks: An Open-Source, Instructionally-Designed Introductory Curriculum with Action-Design Research

Austin Cory Bart, University of Delaware, Newark, DE, USA

Allie Sarver, Virginia Tech, Blacksburg, VA, USA

Michael Friend, Virginia Tech, Blacksburg, VA, USA

Larry Cox II, Virginia Tech, Blacksburg, VA, USA

From Lauren Margulieux

https://laurenmarg.com/2019/01/13/article-summary-margulieux-et-al-2019-review-of-measurements-in-computing-education-research/

Lauren Margulieux, Tuba Ketenci, and Adrienne Decker.

Review of Measurements Used in Computing Education Research and Suggestions for Increasing Standardization

From Felienne Hermans

http://perl.liacs.nl/2019/01/31/when-i-grow-up-i-want-to-become-a-programmer-elli-11-how/

Early Programming Education and Career Orientation: the Effects of Gender, Self-Efficacy, Motivation and Stereotypes

Efthimia Aivaloglou and Felienne Hermans

 

 

Our work at SIGCSE 2019: Ebooks, jobs, privilege, what is research, and what is literacy

There was a time before each SIGCSE Symposium or ICER Conference that I would write a blog post about all the cool things being presented from Georgia Tech (see for example SIGCSE 2018 and SIGCSE 2017 posts).  But now, the list of things at SIGCSE 2019 from Georgia Tech and University of Michigan (my new home) is enormous.

I’m going to take a different strategy — the selfish and easier strategy.  Let me just tell you about the things that I know about because I work with the authors. All the proceedings are available here.

• Wednesday is the RESPECT conference (see program here). At the 9:30 session, Katie Cunningham will be one of the presenters of a paper “Job Placement Experience and Perceptions of Alumni from a Three-year Computer Science Program” with Miguel Lara and Bude Su about the job placement experience of students who graduate from the CSin3 program that won a best paper award at last year’s SIGCSE Symposium.
• On Thursday afternoon, I’m going to be on a panel with Lauren Margulieux, Leo Porter, Greg Nelson, and our organizer and moderator, Colleen Lewis.  The topic of the panel is “Negotiating Varied Research Goals in Computing Education Research.”  Greg and Amy Ko published a paper at this last year’s ICER, which won one of the best paper awards, that I and others strongly disagreed with.  Amy’s blog post captures the discussion and arguments well. This panel continues that discussion.
• Friday morning: I will be giving a keynote “Computing Education as a Foundation for 21st Century Literacy.”  I’ve practiced it every seminar and event I could find for the last couple months, so I’m ready.
• At Friday’s 10 am poster session, ECEP will be presenting a poster (Jeff Xavier as lead) on “Fostering State-level Change In CS Education: The Expanding Computing Education Pathways Alliance.”
• At a Friday morning 10:45 am special session, Miranda Parker will join Helen Hu, Jason Black, and Colleen Lewis to explore the role of privilege in CS education — an issue near and dear to Miranda’s heart (see, for example, this post).
• At Friday afternoon’s 3 pm poster session, Katie Cunningham will have a poster with Miguel Lara and Bude Su echoing their RESPECT paper.
• Friday afternoon at 3:45, Barb Ericson will be on a panel with Alison Derbenwick Miller, Lecia Barker, and Owen Astrachan on broadening participation in computing.  “You don’t have to be a white male that was learning how to program since he was five:” Computer Use and Interest From Childhood to a Computing Degree. I know that Barb is working hard on analyzing all the AP CS 2018 data, so this may be the unveiling of her annual analysis (see 2017 and 2016 posts here).
• Saturday afternoon, Barb Ericson (with Brad Miller and Jackie Cohen of U-M) will present a workshop on how to use the Runestone ebook platform that we use in our work (see, for example, this post).

I highly encourage everyone to check out the SIGCSE 2019 Best Paper award-winning presentations (see list here).  I’m particularly excited that Andreas Stefik’s (with Richard Ladner, William Allee, and Sean Mealin) project on developing CS Principles materials for blind and visually-impaired students is being recognized. We need to take more seriously making computing accessible to a broader range of students.

 

The Cambridge University Press Handbook of Computing Education Research: Now Available

After a long haul, it’s finally available. The snazzy promotion flyer is here (with discount code). You can order the book from the Publisher here. Or get it from Amazon here.

I was an author of one chapter (on computing in other disciplines) and co-author with Ben du Boulay on the history chapter. While the overall process was hard work, it was enormous fun to work with Ben. I’ve read his work for many years (he invented the concept of a notional machine), but we still haven’t met face-to-face. Ben knows all of this literature on the European side of CER that I’m not well versed in, and he’s a delight to work with. I learned a lot and so enjoyed the process.

The Cambridge Handbook of Computing Education Research

This Handbook describes the extent and shape of Computing Education
research today. Over fifty leading researchers from academia and industry
(including Google and Microsoft) have contributed chapters that together
define and expand the evidence base. The foundational chapters set the
field in context, articulate expertise from key disciplines, and form a
practical guide for new researchers. They address what can be learned
empirically, methodologically and theoretically from each area. The topic
chapters explore issues that are of current interest, why they matter, and
what is already known. They include discussion of motivational context,
implications for practice, and open questions which might suggest future
research. The authors provide an authoritative introduction to the field and
is essential reading for policy makers, as well as both new and established
researchers.

The biggest concerns for institutionalized CS education in the United States: Standards, limited models, and undergraduate enrollment caps

I was interviewed for the SIGCSE Bulletin by my long-time collaborator, Leo Porter (see https://sigcse.org/sigcse/files/bulletin/bulletin.51.1.pdf).  I talk about this blog, how I started teaching in 1980, about Media Computation, and about what inspires me.

One of the questions relates to the recent discussion about standards and frameworks (see post here).

LP: You have worked with education public policymakers in “Georgia Computes!” and Expanding Computing Education Pathways (ECEP) over the last dozen years. What’s your biggest worry as US states start institutionalizing CS education?

I have two. The first is that the efforts to standardize CS education are making the bar too low. When the K-12 CS Ed Framework was being developed, decisions were being made based on how current teachers might respond. “Teachers don’t like binary, so let’s not include that” is one argument I heard. I realize now that that’s exactly the wrong idea. Standards should drive progress and set goals. Defining standards in terms of what’s currently attainable is going to limit what we teach for years. Computing education research is all about making it possible to teach more, more easily and more effectively. I worry about setting standards based on our limited research base, not on what we hope to achieve.

The second is that most of our decisions are being made around the assumption of standalone CS classes and having teachers with a lot of CS education. I just don’t see that happening at scale in the US. Even in the states with lots of CS teachers in lots of schools, a small percentage of students take those classes. This limits who sees computer science. To make CS education accessible for all, we have to be able to explore alternative models, like integrating computing education in other subjects without CS-specific teachers. If we only count success in CS education as having standalone CS classes, we are incentivizing only one model. I worry about building our policy to disadvantage schools that want to explore integrated models, or have to integrate because of the cost of standalone CS classes.

Since this interview, I have a third concern, that may be more immediate than the other two.  This is what I wrote my CACM Blog on this month. The NYTimes just published an article “The Hard Part of Computer Science? Getting Into Class” about the growing CS undergraduate enrollment and about the efforts by departments to manage the load.  Departments used to talk about building capacity, but increasingly, the discussion is about capping or limiting enrollments.  The reason why this is concerning is because we’ve been down this road before — see Eric Roberts’ history of CS capacity challenges. Our efforts to limit enrollment send a message about computer science being only for elites and being unwelcoming to non-CS majors. This is exactly opposed to the message that Code.org, CS for All, and the AP CS Principles exam is trying to send. We’re creating a real tension between higher education and the efforts to grow CS, and it may (as Eric suggests) send enrollments into the next dive.

How to organize a state (summit): From ECEP and NCWIT

Soon after we started the Expanding Computing Education Pathways (ECEP) Alliance, we were asked: What should a state do first?  If they want to improve CS Education, what are the steps?

We developed a four step model — you can see a three minute video on ECEP that includes the four step model here. It was evidence-based in the sense that, yup, we really saw states doing this.  We had no causal evidence. I’m not sure that that’s possible in any kind of education public policy research.

One of those steps is “Organize.” Gather your allies. Have meetings where you CS Ed people rub elbows with the state public policymakers, like legislators and staffers in the Department of Education (or Department of Public Instruction, or whatever it’s called in your state).

A lot of states have had summits since then (see a list of some here).  Now, working with the fabulous NCWIT team of communicators, graphic designers, and social scientists, ECEP has released a state summit toolkit.  We can’t yet tell you how to organize a state. We can tell you how to organize a state summit.

From finding change agents to building a steering committee of diverse stakeholders, convenings play an important role in broadening participation in computing at the state level. ECEP and NCWIT have developed the State Summit Toolkit to assist leadership teams as they organize meetings, events, and summits focused on advancing K-16 computer science education.

From https://ecepalliance.org/summit-toolkit 

Need for Reviewers for US Department of Education CS Education Grants – Guest Post from Pat Yongpradit

Pat Yongpradit of Code.org asked me to share this with everyone.

The US Department of Education has announced the EIR grant competition for FY 2019. This year EIR incorporates an exclusive priority for computer science with a focus on increasing diversity and equity in access, as compared to last year where the highlight was that CS was merged with STEM as a combined priority. See more detail in our blog.

There are many moving parts to the federal grant review and award process, including a merit-based review process. In order to adequately score grants featuring computer science, the US Department of Education must have enough reviewers with K-12 computer science education experience. There is more information on the merit-review process and the Department’s mechanism for selecting reviewers in this blog.

Code.org has been asked to put interested folks in touch with leaders of the EIR grant program. If interested, please send your CV to EIRpeerreview@ed.gov.

Having CS knowledgeable reviewers participating in the federal grant review process is crucial to maximizing the opportunity these grants present the field and our collective goal of expanding access to K-12 computer science.

Best,

Pat

Hadi Partovi’s keynote at CrossRoads 2018: CS Ed Research needs to up its game

I was scheduled to be on a panel at last year’s InfoSys Crossroads 2018 conference, but my father passed the week before, so I couldn’t make it.  Several people told me that I had to see the video of Hadi Partovi’s talk, because “he talks about CS Education Research.”  The facial expression suggested I should feel warned.

I enjoyed the talk. Hadi made some critical and completely fair statements about CS Ed Research today. I recommend watching.

 

The really research-y stuff is around 30 minutes into the talk.  He talks about CS competing with other fields (a point that Joan Ferrini-Mundy also made to ECEP), and that CS has to make the argument for itself. I most appreciated the point (around 31:50) that no CS Ed research meets the “What Works Clearinghouse” standards for “works without reservations.” He’s right, and it’s a fair criticism.  Maybe it’s too early, but at some point, we have to be able to compete at the evaluation standards applied to all other subjects.  Code.org is stepping up their game, with the first evaluation demonstrating that their CSP curriculum significantly increases the rate at which students take and pass the AP CSP exam (see paper here).

I learned a lot from his talk, especially his points about how to scale. I love the advice to “Execute first, raise funding after.”  Since I’m trying to re-start my research program at Michigan, I am thinking about that advice a lot. I hear Hadi saying that I need to be executing on something interesting to fund first, before trying to sell the something interesting I want to do. Writing proposals about things I’m not executing on will probably not be convincing, and delays me making progress on the things I’m passionate about.

Of course, I vehemently agree with his argument that the future of CS Ed is to integrate CS into other subjects.

 

Higher Ed and the Role of a Computing Culture: Interview on No Such Thing Podcast

When I visited the To Code and Beyond workshop last month (as mentioned in this podcast), I was interviewed by Marc Lesser for the No Such Thing podcast, which he just released.  (My keynote is also in his podcast series here.) It’s a wide ranging interview, from woodworking to the work I’ve started with History professors Bob Bain and Tamara Shreiner, from how I began teaching computing in 1980 to how I’ve been inspired by (to name a few) Alan Kay, Yasmin Kafai, E. Paul Goldenberg, Brian Harvey, and Bob Kozma.  Marc’s framing for the podcast is interesting (pasted below): How do we “bottle” me? In other words: How do we create more computing educators who care about CS for All, especially at the higher education level? The episode can be found here.

At the top of the last episode you learned about Mark Guzdial. Mark is a Professor in the College of Engineering at the University of Michigan. After his talk at Cornell Tech’s “To Code and Beyond” I had a chance to sit down with Mark and ask what questions had bubbled up while I listened to his talk live. Probably my most pressing question: what you’re saying is great, but we’ve all seen professors like you on youtube – Mark is a brilliant, animated, ukulele playing Computer Science professor, who, from my time with him, seems as passionate about you learning about his passion topic, as he is about the topic itself. He’s a rare mix, and what I’m sure many in the audience wondered – what the country is wondering right now – is how do we bottle some of that, and help thousands of teachers in every state offer young people the experience that surely the students in Mark’s class have each semester. For what it’s worth, out-of-state tuition at his school is $43,476 with a 26% acceptance rate. A wicked problem, indeed.

Inverse Live Coding: A practice for learning web development

I finished my first semester teaching at the University of Michigan. I taught EECS 493 User Interface Development all on the Web. It was a tough class for me since I had never before this class used JavaScript, jQuery, or CSS. I learned a lot, but I also had to teach it.

As readers of this blog now, I am a fan of live coding (see blog post here) where a teacher writes code live in front of the class. The positive aspects of live coding include that the teacher will likely make mistakes, so students see that (a) mistakes are common and expected, (b) mistakes can be corrected, and (c) there is a process to recover from mistakes.

I could not live code in this class. I didn’t know the material well enough. It took me too long to code, and I couldn’t recover from mistakes in front of the class.

It was also so hard in the context of a Web-based user interface course. I had the advantage that I could watch videos of Mark Ackerman and Walter Lasecki teach the course before me. Both of them know JavaScript and Web technologies well enough that they could live code in front of the class. I couldn’t understand what they were doing. Part of it was the low-resolution of the video — I couldn’t read the screens well. But a bigger part of it was the cognitive load of remembering the HTML and the CSS while writing the jQuery code. I couldn’t figure out the code while also remembering the names of the divs and how they were nested, and what CSS formats were being applied to which divs and classes. Maybe the younger kids fare better than me in my mid-50’s.

So, I tried a different practice. Maybe call it Inverse Live Coding.

• I wrote programs (HTML, CSS, plus JavaScript with jQuery) before class.
• I demoed and lectured on those programs (briefly — maybe 10-15 minutes).
• Critical: I gave the students the code and all the associated files (HTML, CSS, and JavaScript).
• Then, live in-class, I had students pair up to make small changes to the code.

This is like in-class coding or a lab session, but short — like 8-10 minutes of coding. We can do three of these in a lecture period. It’s more like a Peer Instruction (PI) session than a traditional laboratory coding activity.  I typically put 2-3 of these in a 90 minute class, as part of a lecture. I have students use iClickers to “click in” when they’re successfully done with the change, so we’re using PI practices to make clear what kind of activity this is. That ritual (clicking in then re-joining the class session) helps with bringing people back to the whole-class context after the pair-programming activity.

Here’s an example: I wrote a small JavaScript/HTML/CSS project that had a balloon slowly float upward, and could be steered left or right with arrow keys. (Why yes, that is a Smalltalk balloon in the example.)

I explained the code, introducing ideas like closures and the ready() method in jQuery.

Then I gave them a challenge. In this case, make the balloon also drift to the left, or drift in different directions based on the time or a random variable.

Different kinds of questions: I was pleased by how well this worked. First, it didn’t take much time. 80% of the teams solved at least one of the challenges in less than 8 minutes. Second, the teaching assistants and I got tons of questions. Many of the questions were fundamental ones — things I never would have even thought to talk about in class if I was live-coding. These are (paraphrased) actual questions that I got during the inverse live-coding sessions.

• “Okay, I made the changes in the JavaScript. Now, how do I compile it?”
• “I made the changes using the debugger in Chrome. How do I make this work in the CSS, HTML, or JavaScript files?”
• “So, the jQuery is changing the HTML or the CSS, right? How come my file isn’t changing?”

These were pretty easy questions to handle in class, but one could imagine that those could stymie a student working alone. When I got one of these questions 1:1 or 2:1 during the pair-programming/live-coding, I made sure I answered the question for the whole class, too. These were questions about the fundamental nature of how Web technologies work (e.g., that the interpreter/compiler is the browser itself, and that jQuery says it’s changing CSS/HTML, but it’s really changing the DOM tree, etc.). It was much better to push the students to do the programming, and thus face these questions, than for the teacher to do the programming. The teacher would have an expert blind spot and may not even think to explain those parts that are invisible and confusing.

Miranda Parker suggested a variation of this practice. I could invite students to come up to the front of class to solve the problem, or to explain their solution after the session. That could be helpful in making sure that everyone sees something that works.

I would still use live coding in an intro course, when there aren’t invisible other files involved in the task and increasing cognitive load. In classes like Web Design, I will use inverse live coding more in the future.

Come to my workshop on CS Education at ASEE June 16!

I am attending my first American Society for Engineering Education (ASEE) Conference this year — see the website here: https://www.asee.org/conferences-and-events/conferences/annual-conference/2019.

I’m still figuring out Engineering Education Research, so I’ll be offering a workshop based on our work at Georgia Tech: Techniques for Improved Engagement and Learning of Programming. The workshop is Sunday, June 16, 2019 from 9:00 am to noon. Please come, and please pass this on to others you know who are attending ASEE and might be interested.

Computing education research at Georgia Tech over the last 15 years has led to techniques for teaching programming which improve student learning. Learning is enhanced through greater engagement and reduced cognitive load.

These techniques are:

• Media computation: Teaching programming through manipulation of digital media which improves students’ sense of utility and relevance leading to greater engagement;
• Worked examples: Using worked examples in peer instruction and for prompting for predictions that improve learning;
• Subgoal labeling: Structuring and labeling worked examples to improve immediate learning, retention over time, and transfer to new problems.

The learning objectives for this workshop are for participants to experience these techniques so that they might be able to judge which are most useful for their own practice. Participants will:

• Manipulate digital media with programs that they write during the workshop (laptops required).
• Participate in peer instruction questions using worked examples.
• Compare worked examples with and without subgoal labeling.