Joint Doctoral Program in the Learning Sciences - interviews

On the occasion of the call for applications to join the second cohort starting in the autumn semester, the Center for Learning Sciences (LEARN) and ETH Zürich's Professorship for Learning Sciences and Higher Education met with four of their PhD students who shared their perspectives on what led them to the Learning Sciences.

Julia Chatain is a researcher doing a doctoral degree between the Game Technology Center and the Professorship for Learning Sciences and Higher Education at ETH Zürich.

Her research focuses on how to teach abstraction in the context of mathematics through games that make abstract concepts more concrete by allowing students to interact with mathematical objects such as vectors, graphs, and functions.

Q: What led you to the Learning Sciences?

"For as long as I can remember, I’ve always been fascinated by how the brain works and how we can help people learn. Is there a good way of teaching people? Does it depend on the person, does it depend on the topic?

I’ve been teaching math for a very long time, and I find it intriguing how some people are drawn to abstraction right away –and you can take them there directly –but some people need to connect it to something, to their own experiences. I was very curious about how we could actually do that."

Q: What drives you?

If you provide them [women] a safe space where they can explore this, they’re excellent. And once they are empowered and think “yeah, I can do this”, then they get very creative very fast. I find that very important.

"Once you learn about how you learn, how other people learn, it helps you understand yourself and other people, much, much better.

When I try to teach or explain something to someone and I see that they are struggling, now I understand what’s happening, why they are struggling, and I understand how to help them.

Learning is something that everybody does, it’s such a connective tissue. I think it’s a fascinating field, education is how we help the next generation grow.

It’s a field where you learn forever because with new technologies there are many new ways we can use to teach people concepts.

On the side, I also participate in a lot of events where I teach mathematics or computer science to girls and women.

As you know, there are very few women in these fields. But when I participate in those events, I notice that they have absolutely no problem with abstraction.

As soon as I explain it, they don’t struggle with it. What they struggle with, is the confidence and trust in themselves.

If you provide them a safe space where they can explore this, they’re excellent. And once they are empowered and think “yeah, I can do this”, then they get very creative very fast. I find that very important.

I would be happy if more girls and women see that they can actually do that. I don’t mind if they don’t decide to make a career out of it, but I want them to know they can do it, that it's an option, and we are here to support them as well.

Part of my research is also about trying to see how we can integrate this into pedagogical practice and have an educational system that supports young girls and gives them confidence directly in the classroom."

Lucas Ramirez is a Doctoral student in Computer Science from the ML4ED Lab at the Center for Learning Sciences (LEARN) at EPFL. Currently, his research focuses on delivering educational content through video games.

Q: What led you to the Learning Sciences?

I’ve been intrigued by education for a long time. Because I’ve always taught, I had been thinking about the use of video games from a standpoint of education for many years in terms of the innovative and unique ways to learn that they offer.

For the little anecdote, I have always enjoyed talking about things that I understand. And even as a child, in my first report card already, my teacher at the time commented that I spent most of my time helping my classmates.

So, you could truly say that this is something that goes way back for me.

Q: What in particular sets the Learning Sciences apart?

I wanted to do something that was at the intersection of several fields

It all came together for me when I learned that it was possible to do research at the intersection of computer science --to incorporate data mining and machine learning-- and education at EPFL.

I wanted to do something that was at the intersection of several fields because to me, interdisciplinarity is a fantastic thing.

By bringing people around the table to work on the same topic, who have different interests, different expertise, and who have a different view of things, you get to generate ideas that couldn't have been generated by any one particular field of research alone.

And that comes from the interaction of the different perspectives and the co-construction towards a common goal.

Looking into how we process information --how we learn-- naturally invites one to engage in self-reflection. It makes you question the way each of us interprets information.

There are many issues around fairness in machine learning. And I’ve realized that if we aren’t extremely careful and don’t take measures to adjust equity, it is very likely that we could end up with an algorithm that is biased because the data itself is biased.

Christian Fässler is a biomedical engineer pursuing his research in medical education at the Professorship for Learning Sciences and Higher Education at ETH Zürich.

His work focuses on a platform that enables medical students to run differential diagnostics using simulations.

Q: How did you become interested in the Learning Sciences?

My educational background is in biomedical engineering. I completed my studies at ETH before joining this lab to try and help medical students handle the difficult mental task of running differential diagnostics.

Medical students typically lack clinical practice, and especially with the pandemic, there was an urgent need to provide them with the knowledge they required in a more efficient manner. We try to provide them with the conceptual and deep understanding they require.

Q: What motivates you?

We must look for new ways to solve problems

There are so many different ways of learning. Changing the learning and instructional approaches to make them more efficient and long-lasting is what it really is about for me.

There is so much potential to improve learning and teaching at universities. We must look for new ways to solve problems, which is both challenging and exciting.

Laila El-Hamamsy is a PhD student at the Center for Learning Sciences (LEARN) at EPFL. With a background in robotics, her research focuses on the digital transition currently underway across the entire canton de Vaud school system.

Q: What led you to the Learning Sciences?

I gradually moved towards the Learning Sciences. I started with MicroEngineering with the idea of then moving towards robotics.

By end of my master's degree, I realized that I was most interested in programming and data analysis.

Gradually, it was the type of application that tended to guide my choices more and more until it became quite clear that education was at the center of it all.

That's when I discovered that I could work in educational engineering. Couple that with my experience as a teaching assistant and the robotics classes I would teach on the weekends, and it was an alignment of little things that ultimately pointed me in this direction.

Moreover, at the same time as my thesis was starting, the digital education project of the canton Vaud led by the Center LEARN was also starting. I was lucky to be brought in to do my thesis on that project.

Q: What about this field motivates you?

Ultimately, it is a collaboration, what we do needs to bring something to the teachers and practitioners

I was interested in co-constructing the research with the field. I did a case study on the value of maintaining close interactions with teachers as part of the process because ultimately, it is a collaboration, what we do needs to bring something to the teachers and practitioners.

The digital education project is important and has real impact. It’s an application of translational research which looks to directly use the results to influence the decisions at the level of the project itself.

Applying research results to practice is what attracted me. We work together towards a goal that is useful for everyone and that is the real value of what we do.