Posts tagged ‘engineering education research’

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.

 

February 1, 2019 at 7:00 am Leave a comment

Embedding and Tailoring Engineering Learning: A Vision for the Future of Engineering Education

In the last couple of months, I have had the opportunity to speak to groups of Engineering Education Researchers. That doesn’t happen often to me, and I feel very fortunate to get that chance.

I was asked to speak about my vision for the future of Engineering Education, from my perspective as a Computing Education Researcher. What I said wasn’t wholly unique–there are Engineering Education Researchers who are already working on some of the items I described. The response suggested that it was at least an interesting vision, so I’m telling the story here in blog form.

For readers of this blog who may not be familiar with Engineering Education Research, the Wikipedia page on EER is pretty good.  The most useful paper I read is Borrego and and Bernhard’s “The Emergence of Engineering Education Research as an Internationally Connected Field of Inquiry.”  I also recommend looking around the Purdue Engineering Education department website, which is the oldest Eng Ed department in the US.

Engineering has had a long relationship with computing. Engineers made computing part of their practice earlier and more pervasively than scientists or mathematicians. I love how this is described in the motion picture Hidden Figures where Octavia Spencer’s character is part of the effort to use computing as soon as possible in the American space program. Engineering educators have made computing part of the learning goals for all of today’s engineering students, again more pervasively than what I can see in science or mathematics programs.

Much of my work and my students’ work is about embedding computing education (e.g., Media Computation which embeds computing in the digital media context that students value, or Brian Dorn’s work embedding computing in a graphic design context) and tailoring computing education (e.g., high school CS teachers need something different from software developers). Computing education can be embedded in Engineering classes and tailored for Engineering students, of course. My vision is about embedding and tailoring engineering education.

There are three parts to the story below:

  • Engineering Education for everyone K-16, especially for STEM learners.
  • Reaching a diverse audience for engineering education.
  • Recognizing the differences between Engineering Education research and teaching, and the need for more research on learning outside of the engineering classroom.

In January 2016, President Barack Obama launched the “CS for All” initiative. When he said that he wanted students to be “job-ready,” he wasn’t saying that everyone should be a software engineer. Rather, he was reflecting a modern reality. For every professional software developer, there are four-to-nine end-user-programmers (depending on the study and how you count). Most professionals will likely use some form of programming in the future. That’s an argument for “CS for All.”

We also need Engineering for All. Engineering skills like designing, planning, collaboration on diverse teams, and trouble-shooting are needed across STEM. When I look at bench science, I see the need for engineering — to design, plan, collaborate, debug, and test.

Engineering education researchers know a lot about how to teach those skills. I’d love to learn how to inculcate some engineering perspectives in my CS students. When I see Chemical Engineering students designing a plant, or Civil Engineering students designing a bridge, they predict that they made mistakes, and they look for those mistakes. There’s a humility about their process. CS students often run their program once and turn them in. If you write a hundred lines of code, odds are almost 100% that you made errors. How do we get CS students to think that way?

Engineering for All is different than what professional engineers do, in the same way that what a high school teacher needs is different than what a professional software developer needs. Both need a mental model of the notional machine. A high school teacher also needs to know how students get that wrong, and probably doesn’t need to know about Scrum or GitHub.

I believe that there is a tailored part of engineering education which should be embedded throughout K-16 STEM. The American Society of Engineering Education’s mission is focused on professional engineers, and my proposal does not diminish the importance of that goal. We need more professional engineers, and we need to educate them well. But engineering skills and practices are too important to teach only to the professionals.

Engineering should play a significant role in STEM education policy. Engineering education researchers should own that “E” in STEM. There are many research questions that we have to answer in order to achieve Engineering for All.

  • What is the tailored subset of engineering that should be taught to everyone? To STEM learners?
  • All technically literate US citizens should know far more about engineering than they do today. Here’s a hypothesis: If all US citizens understood what engineering is and what engineers do, we might have less crumbling infrastructure, because we citizens would know that infrastructure is critical and professional engineers design, build, and maintain infrastructure. How do we get there?
  • All K-12 students should have the opportunity to fall in love with engineering. How?
  • Are there limits to what we can teach about engineering in K-16? What learning and cognitive disabilities interfere with learning engineering, and what parts of engineering? I also wonder about the kinds of bias that prevent someone from succeeding in engineering, besides race and gender. For example, here in the South, there are a lot of students who don’t believe in evolution. I’m pretty sure that belief in evolution isn’t necessary for designing a bridge or a distillation column. But someone who believes in intelligent design is going to face a lot of barriers to getting through basic science to become an engineer. Is that how it should be?
  • Engineering should aim to influence K-12 STEM education nationally, in every state.

The American University (particularly the Land Grant University, developed in the late 1800’s) was supposed to blend the German University focus on research and the British focus on undergraduate education. My favorite history of that story is Larry Cuban’s How Scholars Trumped Teachers, but Michael Crow also tells the story well in his book Designing the New American University. We believed that there were synergies between research and teaching. It’s not clear that that’s true.

Research and teaching have different measures of success and don’t feed directly into one another.

Teaching should be measured in terms of student success and at what cost. Cost is always a factor in education. We know from Bloom’s two-sigma 1984 study (and all the follow-ups and replications) that the best education is an individual human tutor for each subject who works with a student to mastery. But we as a society can’t afford that. Everything else we do is a trade-off — we are trying to optimize learning for the cost that we are willing to bear.

Research should be measured in terms of impact — on outcomes, on the research community, on society.

It’s quite likely that the education research on a given campus doesn’t influence teaching practice on the same campus.

I see that in my own work.

We can see the transition for education research idea to impact in teaching practice as an adoption curve. Boyer’s “Scholarship Reconsidered” helps to explain what’s going on and how to support the adoption. There is traditional Scholarship of Discovery, the research that figures out something new. There is Scholarship of Teaching that studies the practice of teaching and learning.

Then there’s Scholarship of Application, which takes results from Discovery into something that teachers can use. We can’t expect research to influence teaching without scholars of application. Someone has to take the good ideas and carry them into practice. Someone has to figure out what practitioners want and need and match it to existing research insights. Done well, scholarship of application should also inform researchers about the open research questions, the challenges yet to be faced.

High-quality teaching for engineering education should use the most effective evidence-based teaching methods.

Good teachers balance teaching for relevance and motivation with teaching for understanding. This is hard to do well. Students want authenticity. They want project-based learning and design. I was at the University of Michigan as project-based learning for science education was first being developed, and we knew that it very often didn’t work. It’s often too complex and leads to failure, in both the project and the learning. Direct instruction is much more efficient for learning, but misses out on the components that inspire, motivate, and engage students. We have to balance these out.

We have to teach for a diverse population of students, which means teaching differently to attract women and members of under-represented groups. In our ICER 2012 paper, we found that encouragement and self-perception of ability are equally important for white and Asian males in terms of intention to persist in computing, but for women and under-represented group students, encouragement matters more than ability in terms of how satisfied they are with computing and intention to persist. This result has been replicated by others. Encouragement of individual students is critical to reach a diverse audience.

An important goal for a first year Engineering program is to explain the relevance of the classes that they’re taking. Larry Cuban tells us that a piece of the British system that got lost by the early 1920’s in the American University was having faculty advisors who would explain how all the classes fit together for a goal. The research on common first year Engineering courses (e.g., merging Physics, Calculus, Engineering in a big 12 credit hour course) shows that they worked because they explained the relevance of courses like Calculus to Engineering students. I know from my work that relevance is critical for retention and transfer.

Do students see relevance of first year Engineering programs? Most first year programs emphasize design and team problem-solving. First year Engineering students don’t know what engineers do. When they’re told “This is Engineering” in their first year, do they believe it? Do they cognitively index it as “real Engineering”? Do they remember those experiences and that learning in their 3rd and 4th years when they are in the relevant classes? I hope so, but I don’t know of evidence that shows us that they do.

Engineering education research, like most discipline-based education research (DBER), is focused on education. I see the study of “education” as being about implementation in a formal system. Education is a design discipline, one of Simon’s Sciences of the Artificial. Robert Glaser referred to education as psychology engineering.

We need more research on Engineering Learning. How do students learn engineering skills and practices, even outside of Engineering classes? How do those practices develop, even if it’s STEM learners and teachers using them and not professional engineers? How should we best teach engineering even if it’s not currently feasible?

That last part is much of what drives my work these days. We’re learning a lot about how great Parsons Problems are for learning CS. Very few CS classes use them. There are reasons why they don’t (e.g., they’re emphasizing the project side of the education spectrum). I’m figuring out how to teach CS well, even if it’s not feasible in current practice. CS teaching practice will eventually hit a paradigm shift, and I’ll have evidence-based practices to offer.

To focus on engineering learning requires work outside the classroom, like Multi-Institutional, Multi-National (MIMN) studies that we use in computing education research, or even laboratory studies. A focus on Engineering Learning creates new opportunities for funding, for audience, and for impact. For example, I could imagine engineering education researchers seeking science education funding to figure out how to teach high school science teachers the engineering that they ought to teach their students — not to introduce engineering, but to make their students better in science.

My vision for engineering education has three parts:

  1. K-16 STEM learners need Engineering for All. Engineering education has more to contribute than just for producing more professional Engineers. Engineering education ought to own the “E” in STEM education policy. Engineering skills and practices can be tailored to different audiences and embedded in STEM education.
  2. Reaching a diverse audience is critical for both research and teaching. For me, that diversity includes the people who need engineering education who aren’t going to become professional engineers, but also people who look different or even have different beliefs.
  3. Finally, research and teaching are different activities, with different measures of success. Teaching should be informed by evidence and be as efficient and effective as possible for a given cost. We need evidence for what we’re doing, and we should gather evidence if we don’t know if what we’re doing is working. Research should focus on what’s possible and on having impact, even if that impact isn’t in the on-campus classrooms. We shouldn’t expect research to impact teaching without explicit investment in adaptation to support adoption.

(Thanks to Barb Ericson, Beth Simon, Leo Porter, and Wendy Newstetter for advice on drafts of this piece.)

March 15, 2017 at 6:00 am 5 comments

What Computing Education Research does that Engineering Ed and Physics Ed Research doesn’t

In my most recent recent Blog@CACM post on last month’s ACM Ed Council meeting, I mentioned that I gave a talk about the differences between computing education research and engineering education research (EER) and physics education research (PER). Let me spell these out a bit here.

The context was a panel on how to grow computing education research (CER). We were asked to consider the issue of getting more respect for computing education research (an issue I’ve written on before). I decided to explore the characteristics of CER that are important and that are not present in EER or PER. Engineering Education Research (EER) and Physics Education Research (PER) are better established and more well-respected in the United States.  But I’ve come to realize that CER has characteristics that are different from what’s in EER and PER.

Engineering Education Research

I came to a new understanding of EER because of a cross-campus STEM Education Research seminar that we’re holding at Georgia Tech this semester. It’s given me the opportunity to spend a couple hours each week with people who publish in Journal of Engineering Education (see here), review for them, and edit for them. JEE is generally considered to top EER journal.

If you’re not familiar, engineering education research is a big deal in the United States. There are well-funded engineering education research centers. There are three academic departments of EER. It’s well-established.

In one of the early sessions, we talked about the McCracken Study (Mike McCracken has been coming to the sessions, which has been great), where an experimental assignment was used in five classes in four countries. Are there similar studies in EER? Our EER colleagues looked at one another and shrugged their shoulders. For the most part, EER studies occur in individual classes at individual institutions. Laboratory studies are rare. International collaborations are really rare.

I started digging into JEE. The last issue of JEE only had papers by American authors from American institutions. I’m digging further back. My colleagues are right — international authors and collaborations are unusual in JEE.

In contrast, I don’t think that the ACM Transactions on Computing Education has ever had an only-American issue. Our ICER conference is not even American-dominated. The ICER 2014 best paper award went to a paper by Leo Porter (American) who worked with Raymond Lister (Australian) using data collected from Daniel Zingaro’s classroom (at U. Toronto in Canada) to address a theory by Anthony Robins (New Zealand).  We use classroom studies, laboratories studies, and frequently use multi-institutional, multi-national (MIMN) collaborative studies (and study how to conduct them well).

Physics Education Research

At the January workshop on CER that Steve Cooper organized (paper to appear in CACM next month — it’s where Eric Roberts gave a keynote that I wrote about here), Carl Wieman was the opening keynote speaker. He talked about the hot issues in physics education research.

After his talk, he was asked about how physics education researchers were dealing with the gender skew in physics and about improving access in K-12 to quality educational opportunities. If you look at Brian Danielak’s visualization of AP CS test data, you’ll see that CS is the most gender-skewed, but Physics follows closely after.  (Click on the picture to get a bigger version, and look at the lower left-hand corner.)

 

ap-exam-data

Carl said that gender diversity just wasn’t a priority in PER. I dug into the PER groups around the US. From what I could find, he’s right. Eric Mazur’s group has one paper on this issue, from 2006 (see here). I couldn’t find any at U. Washington or at Boulder. There probably is work on gender diversity in physics education research, but it certainly doesn’t stand out like the broadening participation in computing effort in the United States (see papers listing from Google Scholar).  The January workshop really brought home for me that a key characteristic of CER, particularly in comparison with PER, is an emphasis on broadening participation, on social justice, on improving the diversity of the field, and guaranteeing access to quality educational opportunities for all.

I don’t have a deep bottom-line here. It was only a few minute talk. My exploration of EER and PER gave me a new appreciation that CER has something special. It’s not as big or established as EER or PER, but we’re collaborative, international, working on hard and important problems, and using a wide variety of methods, from in-classroom to laboratory studies. That’s pretty cool.

October 12, 2014 at 12:19 pm 9 comments


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