Scaffolding of a 'create-first' pedagogy with modeling and simulation at one of the UK's oldest universities

CLAIRE LUCAS: Well, hello, wherever you're watching this from. I'm Claire Lucas, and I'm here with my colleague, Francesco. We're from King's College in London, and we're going to talk today about how we developed and relaunched a new engineering department in the heart of the UK's oldest University, or one of the UK's oldest universities.

To give you some of that context, King's College London is in the center of London, so it's right in the city beside the Houses of Parliament, across the road from the London Eye, and about halfway between Buckingham Palace on one side and St. Paul's Cathedral on the other. And this location is really special, and it's a special part of our story, and it's what attracts students to us, being that close to the city, being that close to government. It's what attracts staff to us. But it also creates such a sense of tradition and a heritage of tradition that we have to contend with when trying to modernize what kind of teaching and learning we want to offer.

So the Department of Engineering at KCL was relaunched in 2019. It is simultaneously the oldest and newest engineering department in the UK, and that's because it had a period of hiatus when all the activity was paused before relaunch. And the vision for this relaunch was to put engineering at the heart of the city of London, but at the heart of the University.

So we were given two floors underneath the quad, the quadrangle if you can imagine a traditional quadrangle, we were given two floors underneath that to build a teaching and learning space. We were given the budget to hire lots of new staff and to purchase lots of new equipment. And the hope was that engineering would become the place where all of the research been fed in from other departments, so geography, war studies politics, law, all of that would come together and come to fruition through what it was that engineers were doing.

And we had the privilege, therefore, of designing our teaching and learning spaces and our research spaces. And as designers ourselves, we had the opportunity to take a design-led approach to these learning environments. So we did a lot of research looking, not only at teaching and learning spaces. We went on quite a few cool trips to different places, but also, we're right next to Google, we've got Facebook nearby, so we could look at what kind of spaces our students might go into, what kind of spaces are designed for creativity, for innovation and try and capture some of those features within the spaces that we were going to offer to our students.

So when we were thinking about how we echo this design-led teaching space, we really were talking about taking our engineering degree from the very traditional knowledge-based teaching, which King's College London was very, very good at is very, very good at, to a new type of teaching, a design-led teaching approach, and that's really what we're going to talk about over the rest of this talk.

We had to start, really, by deconstructing what engineering is all about. And when I use the word deconstructing there, I really do mean it in the sense of dismantling and examining, underlying assumptions, mental models, thinking about the systems and structures and processes that form engineering as a profession and as an institution. So we started by asking lots of questions in workshops with each other, with our partners, with our advisory board.

So examples of these questions-- who is engineering for? Who benefits from engineering at the moment? What kind of students do engineering? What kind of staff do we have?

And then this other side of that coin, who are we excluding then? So who doesn't get to benefit from what it is that we're doing? Who doesn't get to join in, and who doesn't get heard? And when we're designing the teaching space, when we're designing the curriculum, and when we're teaching our students to design, we're always thinking about how do we include diverse voices in that design from our community and our society around us.

We had to ask really challenging questions of ourselves about how engineering positively and negatively impacts the world. And if we were going to bring a new engineering department into this space, we wanted to make sure that it would have a positive impact on the local communities around us, the city of London, but also, those engineers would have a positive impact on the world. And that would be through increasing equitable outcomes for engineering, not only for our students-- we have one of the highest widening participation rates of students in London-- but also, for the people that they go on to work with.

We really were hopeful that we'd want to be able to create socially responsible professionals out of our engineers and those that would improve access to technology that we were producing around the world. And when we looked at what types of things that people would be doing, what we thought of innovators and entrepreneurs, we came across this concept again and again of wicked problems, those kinds of problems with no obvious or perfect solution, and this is such an antithesis to what students are really used to and sometimes what they expect.

What they're hoping for is some examples that look like some examples they might have tried before that we give them in a test so that they can remember what they've done before and reproduce it. And the world is not like that. The kind of problems that our students will go on to face don't even exist yet. We can't conceive of them. So we have to really help students think about the future, but also, how do we teach students to learn to think outside of the box.

And this all really came together in our catchphrase. It's potentially not a very catchy catchphrase, but really, what we're staking our claim on is that we want to be a department who teaches students to better make things, to make better things, and to make things better. So we want to examine the whole supply chain of what we're doing, looking at the source of our materials, who is mining those materials. Are there children involved in this supply chain, for instance? What are the environmental impacts of the things that we're making?

So we want to better make things, but we also want to make better things. We want the things that we produce to be better for society. We want them to be better for all sorts of people in the way that we do inclusive design. And by doing both of those things, we think that we will be able to make things better for everybody around us.

So when we were putting together our program, we, again, had to go through this period of deconstruction. So we looked to curricula around the world, and we see a very siloed way of doing curricula. So the UK has the opportunity of having something called a general engineering degree, which is not that common around the world. This is a degree that students can take where there are no specialisms at the end, but often, students are choosing electronic engineering or choosing mechanical engineering.

So we really wanted to reimagine what would a generalist engineering degree look like. And of course, it won't surprise those of you who are here because you're designing people, that has design at the heart of it. So design is about 25% of the contact time of what students do here, and this is not super typical for a traditional research-led university. And these design modules run concurrently with the engineering science modules, with the maths and programming modules, and students work together in those teams on multiple projects throughout their time at King's.

When we were thinking about how to deliver design-based teaching then, we were able to draw on some of this great heritage of various revolutions that have taken place in engineering education. So we started out by looking at McMaster University and their problem-based learning approach. So this really came out of health and medicine, and we continue to draw on lots of other disciplines in the way that they reinvent teaching and learning. And this problem-based learning was all about setting students a contextual problem where they would be then motivated in a self-directed way to look for solutions and to acquire knowledge that would help them to solve that problem.

And this was very quickly taken on by engineers. And you have, in Europe, Aalborg University, who turned that problem-based learning into project-based learning. And what that transition was, was students would have to produce an artifact or a solution in order to solve that problem. So it takes all of the benefits of problem-based learning and scenario-based learning and actually involves students creating and designing as part of it.

We then move on to a new phase of problem-based learning and project-based learning from Stanford, which starts to include more P's, so not just problems, but also people and planet and processes and thinking about all of the ways that you can widen the context of what it is that students are trying to do. And then finally, we can't miss the emergence of CDIO from MIT, and that's spread globally around the world. And this is where students don't only conceive and design something, but also have to go through cycles of implementation and operation in order to test their designs and check that they are going to work in the way they say they are. So we look backwards at these various revolutions in engineering education, and what we're going to talk about next is that we think the next revolution is in a skills-based approach, so what skills do students need to be engineers and how can we do skills based pedagogy for engineering education.

So before we do that, let's just talk about what traditional pedagogy is, and anybody who's ever done a teaching and learning course, if you're an academic or if you've done anything in education, you will have heard of this Bloom's taxonomy triangle. And this is very well established. It is the model by which students go through stages of learning. So they start off learning to remember, learning to understand. They may then, once they've acquired some knowledge, be able to apply that knowledge, be able to analyze that knowledge. And only towards the end, really, do you get the opportunity to do creation.

And what's more is that that creation is not just at the end of the cycle, but the time devoted to it is really represented in this triangle. It's really the tip. It's the smallest part of what people get to do. So students are really, really well trained, again and again, in applying mathematical procedures to find solutions to questions, but in many cases, they're just remembering a previously similar question. And even in practical pedagogy and engineering labs, students can end up being quite procedural in the way that they follow through.

And we also see this echoed in the way that departments are structured and the way that courses are structured. Everything is broken down into a core set of knowledge, and we, the faculty, really stand as gatekeepers for students saying, you cannot progress to creativity before you've mastered all of these other things. So you can tell by the way I'm talking that we reject this as the model for how we want to train our engineers, and what we're proposing, instead, is a new way of doing this triangle.

So we have a create first pedagogy. We want to turn that tip of the triangle to be the biggest part of the curriculum, 25% of the curriculum that students do. And so all of our courses start with students having something they know they'll need to create something for. And students then go through these phases horizontally. So it's not a year-on-year progression through the stages, but within each design module, students go through this whole cycle before iterating through to the next year.

So just briefly to go through these stages, you start off with creativity, which means that you're going to have to do some evaluation. You have to evaluate the scenario. You have to evaluate the needs. You have to analyze yourself and understand your current gaps, what are you good at, what are you not good at, what do you need to learn to do. But you also have to do lots of analysis of different options, and we deliberately create these scenarios with lots of options available so that students have to go through that dealing with uncertainty.

And we get students to be applying. The reason we run these modules concurrently with other things is that they're applying techniques that they're learning about in other modules. So they may be learning some modeling in a module, or they may be learning some fluid dynamics, and they're going to apply that within these design problems.

And we think that through trying things out that the students will gain technical understanding, and that understanding will go beyond knowledge-based understanding, and they'll understand why some things work some of the time and don't work all of the time, and they will be able to consolidate that understanding.

And finally, we have quite an extensive lessons-learned process at the end of each project, and through that we want students to remember the lessons. So we want them to remember that technical knowledge through quite an impactful experience, but also to remember what worked and what didn't work, what they tried and how they felt about it to really help them with their self-development as well.

So in order for students to go about this kind of pedagogy, where we're starting with creativity and going through all of these problem-solving stages, we really revisit the question, the long-asked question about soft skills. And we're still using that title quite loosely because we are still looking for a better way of describing these enabling, non-technical skills, which help students to become, not only better engineers in the future, but better learners and facilitate their learning in this problem-based environment.

So Francesco and I have a PhD student that we jointly supervise, who has reviewed about 20 years worth of literature, looking for these mentions of skills, which are either needed to become better engineers in the future or that help them to do their learning and enable their learning whilst they're in their degree. He's done things like look at the process by which those skills are defined, figured out who are the main stakeholders and gatekeepers of these skills definitions, and try to develop a framework of soft skill aspects. And for now, we've posed the concept of non-functional requirements, and I'll talk about those.

So if you're a systems or a software engineer, this idea of non-functional requirements might be quite familiar to you, but for everybody else, when you're designing something, you will often think about what the thing should do, so in various scenarios, what is it that things should be able to do, and we call those the functional requirements. And these are very similar across the UK. If you're signed up to the Washington accord, these are very similar around the world, sets of expectations by year that a student is in of what a student should be able to do.

So they move in year one from being able to apply methods and solve quite broadly-defined problems to by the time they're in their master's year, so year four, we have four-year master's degrees, to be able to select from state-of-the-art knowledge to frame, analyze, and solve complex problems. But what can be quite unique and what you can have quite a DNA in is thinking about the non-functional requirements, how should students be.

So if education is a transformation of students, what do they become through the experiences that they have and the learning that they have? So by the end of the first year, we really focus a lot on trying to help students become more self-aware. We do these reflections and analysis of skills gaps. We help them become culturally competent, as they learn with each other in multicultural teams, but also, think about the things that they're designing and how they impact wider society. And we want them to become creative design thinkers.

And we scaffold this throughout the degree. So in the second year, we're trying to help them become quite innovative and resourceful in the way they solve problems whilst also being socially and environmentally aware and ethically aware of what they're creating. And then in the third and fourth years, the bachelor's and the master's parts of their degree, they're really looking at becoming technology innovators and becoming systems thinkers through more commercial and professional awareness, through more global and social responsibility.

So this is really how we present our course to students and to academics that join us that not only are we looking at these functional things, what students should be able to do, but we're really thinking about becoming and what students will leave us and how they will be at the end of their degree.

And just drawing back to the work that the PhD student is doing, we're hoping at the end of all of this to be able to generate a behavioral marketing system for engineering. So this, again, draws on aspects from medicine and from other industries, and it's all about identifying skills through behavior. So what behavior does a student demonstrate, and how does that indicate a skill that they might possess, and we're looking at both positive and negative behavior.

So the question that we're really asking then, through our observation of students and through longitudinal assessment of what students are doing is, what types of behavior can we observe early on that result in students who make good design decisions later on? So what can we observe that a student does in their first one, two, or three weeks that leads to them becoming great designers, and therefore, how can we scaffold that in and make sure that students get the chance to develop that behavior in those skills?

And this is where we are at the moment. We've been running the degree. We've got our first set of graduates who graduated last year. And we've really been thinking about the industrial processes. We liken this iterative process that we do to agile problem solving in industry. We've drawn on design-thinking, problem-solving processes and others, because we're really trying to understand how we can map the journey that students go on in their learning to industrial problem-solving processes, and not just one type of process, but multiple types of processes that we could give.

So Francesco is going to talk now about a deep dive into the example of the way that we actually do this and deliver this in our curriculum.

FRANCESCO CIRIELLO: Thank you, Claire. Claire's question has prompted us to delve into extensive research, understand how professional teamwork maps to learning. And this paradigm is what forms the foundation of our pedagogy at King's and marks a shift from learning-based knowledge transfer approach to learning by process-oriented design.

In shaping our learning experiences, we do acknowledge that the ideal setting for professional skill development is one that closely resembles that of professional practice, but we also know that design cultures can vary significantly across organizations. So to this end, we built up different phases to our framework with which we deliver the design modules, and we'll start with students conceiving ideas through personalized product design.

They will then move on to integrating systems, and they will apply model-based methods to deliver safety critical solutions. And was leveraged into year two, they'll have built sufficient design intuition to continuously iterate and improve their products so that they can start tackling those intractable problems that don't have any analytical solutions. And by the end of their second year, they become innovative thinkers that can tackle the future, and they can address global needs and examine the connections that extend beyond that of themselves as a designer into different types of spaces and see connections between social, problem, solution, natural, and commercial spaces. We really strive to be explicit about these themes as we design the activities, and within each way of thinking, we try and create a learning journey that exemplifies the value of each of these design lenses.

One way we articulating this pedagogy is by mapping design culture to establish taxonomies of learning. And we try and conceive it in a way that students would use broadly-defined modules in years 1 and 2 to acquire foundational knowledge, but then they can apply it within the design modules so that it consolidates different dimensions of learning, from being able to critique the human dimensions of products, to being able to integrate learning across disciplinary domains, to reflecting on process improvement and quality management up to caring about service and about society.

This coordinated approach prevents us from dissociating ways of thinking about design from the technical implementations of a project. So that's what I'm going to focus on next, and thankfully, Autodesk tools help us connect technical skills to ways of thinking, and they help us transverse across disciplinary boundaries.

So what we'll do is, we'll take one of our first-year integrated design modules as an example case study, and we'll look at how students design a ship to collect floating waste. And by using this project-based example, we run through several of the learning activities that show how the approach can connect technical design skills to systems thinking.

The project itself runs over 10 weeks and motivates learning across many different disciplines, from system design and management, to control analysis. Students have to learn about embedded programming with microcontrollers and communication systems, as well as the underpinning mechanics, such as the fluid and structural mechanics that will make their ship perform adequately.

So let me show you a few of the modeling and design techniques that we use to exemplify systems skills. For example, we'll set the module by sharing the CAD components of what is available in the maker space. And what we really like about virtualizing the components at the get-go of the model is that learners develop a sense of inquiry, which makes them reflect on the purpose of components. And they start questioning what to do with bearings, with mounts, with couplings, and different types of fasteners. And in doing so, we can support students with a variety of virtual examples that they can then go on and discuss and analyze.

Tracking components allows us to build and present design variants, which we can then on extend and inspect using comparative analysis. So for example, at this stage, we might discuss strategies for waterproofing a motor and the ensuing trade offs that are cross-domain on shaft misalignment, to torque transmission, motor placement, and so on.

Duplicating components also allows us to scaffold how learners design parts for fabrication. We run through tutorials on top-down modeling, for example, to create 3D printed motor housings, and we show how learners, how system design tools can also shape the geometrical form of art. Where possible, we also encourage learners to adopt automated modeling to rapidly explore solution spaces so that fabricated items such as the hull of the ship or the propellers are modeled parametrically. Here, for example, we're using Chris Drake's airfoil tools, which is an excellent design automation tool, to streamline the hull of a ship, and this really enables quicker development, so a better exploration of the solution space.

And this simple, but effective product lifecycle management approach allows us to track components to quickly assemble diverse conceptual prototypes and also, to have students present assembly diagrams to a technical standard and share their bills of materials with us so that they can access physical components as they move from the design to the manufacturing stage of their prototyping. And we keep maintaining this digital thread even beyond the Autodesk ecosystem, and we are keen to exemplify the role of design tool interoperability in support of system design.

In this module, again, with an example, we integrate the CAD assemblies within other simulation environments, such as Simulink, which help us create reduced order dynamical models and design control algorithms that we can then deploy onto hardware. In this way, we interface with CAD models, and we can create multi-domain physical simulations, for example, here showing an electrical mechanical component model for a voltage controlled DC motor.

And we even integrate with testing and measurement activities, where some of the modeling gets complemented with simple experimental campaigns so that we can provide model closure for those ambiguous moments in which we need to reduce order of models.

And some of the tools within Fusion 360 really help us merge these transitions. For example, we use inspection tools that allow us by tracking all of these components to deduce properties such as the center of mass, the moment of inertia, the distance between propellers. And we can feed these into template system models that allow us to analyze the performance at the system level of the design. And this digital thread that merges CAD and simulation also allows learners to see the connection between the technical and the system thinking skills.

And in being able to interact with these system-level models, learners can build an intuition about the emerging behavior of components of an assembly, and the techniques help us better understand the engineering parameters, acknowledge the diversity of physical domains-- for example, interfacing mechanical, fluid, and electrical disciplines-- and also, improve our system design through intuition and explorative tuning. But this transition goes even further when the students are asked to make and operate a ship, as we create a powerful feedback loop with integrated design and analysis.

So now, students need to think about nesting for fabrication, how to create joints for assembly, and also, how to start thinking about how to integrate the components within a physical prototype. And we're becoming increasingly interested in enriching some of these experience, going into data-driven, decision-making tools just to support systems thinking even with visualization of properties at the mesoscale of the hierarchy of an assembly.

So for example, we've been exploring new ways of introducing the new Maker site plugin within our module and its learning experience so that students can also investigate sustainability parameters within their overall performance metrics. And also, these tools are really helping us making technical skills, transversals, so that we move simply from techniques to ways of thinking because these are really embedded within the design tools. So we see a lot of value in using it.

And it's really helping us shape the future of education and how we're pushing its boundaries by creating these learning journeys across multiple years, where we're transforming education to be design led and transversal, and thankfully, Autodesk tools like Fusion 360 are really enabling this transformation. So if you liked this class, please click on Recommend. And if you'd like to engage with our general engineering department, drop us an email using the addresses on the screen.