Mine Çetinkaya-Rundel

Aditya Rudrapatna has written the following article as part of our series of Academic Interviews; featuring Mine Çetinkaya-Rundel !

Student Aditya Rudrapatna had the opportunity to speak with Dr. Çetinkaya-Rundel and gain an insight into her life, her work, and what a statistician and data scientist in the 21st century looks like. Here is his conversation with her.

What was it like growing up in Istanbul and how did it influence your life and work?

I was born in Istanbul and finished high school there. I went to the United States for college and stayed for a while, but all of my family is back in Turkey. What I can say is that Istanbul today is different to Istanbul then, and a lot has changed in the country, but it’s still a gorgeous city.

I enjoyed maths at school, and I’m happy to be sticking around in that quantitative area, but I would never have guessed that I would wind up doing what I am today. I never took a single statistics course in high school, so yes, I liked working with numbers, but I don’t think I understood what mathematics really was as a student. I don’t think that I could have envisioned that I’d be doing the things that I’m doing now, because I didn’t know about them.

What’s your standout memory from university?

I'll tell you a story I’ve told a few students of mine. I went to university in New York, and in the winter it can get pretty cold. I had an 8am lecture and one of the hardest things was to be there in the dead of winter so early. I remember every morning picking up hot chocolate and a muffin, eating those in class and then falling asleep, to the point where I would just hide under my coat to get warm.

I ended up not doing very well on this one exam - I used to do well in my classes, but I didn’t understand what we were doing in this one - so I thought I should talk to the professor and try to understand why I was missing things. As I walked in to his office - and this isn’t a small class, but a large one in a large lecture auditorium - the professor says, “Oh the girl under the coat is here, you’re awake today!” I said to myself, “How does he know who I am?! There are hundreds of students in this class!” I would never have guessed that in that dark auditorium I was visible to the professor. If I had known that I was, I wouldn’t have fallen asleep! So that was impactful in the sense that it really made me realise that you are not anonymous in a class.

What are you working on right now with your research?

There are a couple of aspects to my work right now. One of them is pedagogical development in assessments. I teach data science and computing courses and there’s lots of good literature around how students learn certain things, especially in computer science education literature. The literature on how people learn statistical programming languages, like R, is a little thinner. I’m interested in how people learn and stick with R, and programming, depending on what syntax they’re learning with. So I’m working on both position and opinion pieces on this topic as well as thinking about how to study it.

What do you think the future of pedagogy looks like?

 I think it will have better structures for active and collaborative learning. We need tools, classroom spaces and pedagogical training to support this. It's clear that students don't want to learn alone, they like learning with each other. That doesn't mean students love doing team projects, but I think it does mean that if you can provide collaborative learning experiences where people can learn from each other, with some guidance, it has a positive impact on learning and satisfaction.

About my own discipline, there’s been a lot more working with data than what used to be included in the introductory statistics course over the last few decades. All these data science courses popping up, I don’t think this is a fad, I think that this move will reshape how we introduce students to working with data. It will have to come with better consideration around how we teach computing, but I think we're moving in that direction.

Looking forward, what would you like your legacy to be?

I would like it to be something along the lines of what I'm working on right now. I work with a lot of people who have moved on to saying, “Yes, we should be teaching students about data, working with data and computing with data”, but that isn’t accepted by all members of the statistics community and all decision makers at learning institutions. I hope that I can make some contribution to getting closer to that goal. There are a lot of variables at play there; it's not just about what's good for science. There's other considerations as well, for example around equity, but I hope that we can at least get closer to that point.