Exploring Beliefs and Behaviours

Let's start with some background. Where did you grow up, and what were your primary interests?

I grew up in St. John's, Newfoundland. My mother was born here, and my father immigrated from Scotland. They met as grad students at Dalhousie University. I am very close to my younger siblings Trese (a nurse), Mare (a philosopher), and Kat (a professional musician). We grew up playing music and sports together. I’ve been inspired by them my whole life! 

I became very interested in psychology and political theory when I was in high school. I started my undergrad as a psychology major because I wanted to become a psychotherapist, but I developed a love for research and realized I was more interested in social, cultural, and political processes than in individual psychology. I eventually discovered sociology and never looked back. My core research interests have been stable for a long time, but the way I think about them has changed a lot, as you can imagine! Perhaps the biggest changes have come from branching out into network science and computational modelling, which I started doing around the time I moved to Waterloo in 2013 as a new Assistant Professor.

How did your broad range of interests evolve and how do you make sense of it all?

My core research interests developed early, and they’ve been evolving and branching out into other fields since I was a graduate student, due in part to energetic conversations with friends, colleagues in other fields, and my students. It helps that sociology is a very open and pluralistic field. And the things I am interested in have vibrant interdisciplinary communities of people (cognitive science, network science, and computational modelling) working on similar things.

But perhaps the most important factor was joining KI and the Faculty of Environment as an Assistant Professor in 2013, right after I finished my PhD at McMaster University. KI and ENV are very supportive of interdisciplinary and transdisciplinary scholarship, which has enabled me to take some intellectual risks that I might not have taken in a more disciplinary environment. During my first couple of years in KI, I developed relationships with philosophers, cognitive scientists, neuroscientists, network analysts, engineers, and climate modelers (to cite just a handful of examples) that guided me in exciting new directions. Being in KI let me follow new ideas, and to integrate knowledge from other fields with my sociological background.

It also helps that I’m a very model-based thinker. That includes some of the frameworks that feature prominently in KI, like design thinking, systems thinking, futures thinking, and probabilistic thinking. These different ways of thinking make it much easier to understand, assess, and integrate knowledge from different perspectives.

Your KI profile notes that you teach a course on the art and science of learning. Indeed, several of the students I interviewed particularly noted the value of this course to them. How do you present the content? 

I am a proponent of active learning, and I like to combine theory with practical knowledge and skills in my courses. I teach The Art and Science of Learning (INTEG 120) using a flipped classroom model, which means that students watch a pre-recorded lecture video and complete assigned readings before our class meetings. We then use our time together for discussion, debate, deliberate practice, and other learning activities. This helps students learn the material more effectively and durably while also becoming more self-aware and reflective. It also creates space for them to practice the skills they are learning, and to develop the skill of active listening and learning from people with different perspectives. This open-mindedness and iterative approach to learning is as important as the explicit skills that students gain in the course, such as metacognition, developing viable learning plans, and adopting “smart” learning strategies that work “in harmony” with our brains and bodies (since all cognition is embodied!) rather than against them.  

How does INTEG 120 set the stage for their subsequent courses?

There are a few ways I could answer that question, but I’d like to focus on courses in the KI core, since they are all designed to work together over time.

In their first year, students take INTEG 120 (which develops foundations in learning and systems thinking) and  INTEG 121,(which introduces design thinking and collaboration). In these courses, students are exposed to new ideas, skills, and mindsets that are simultaneously expanded and advanced in their later courses. The second-year core courses reinforce these foundations while also developing skills in critical thinking, creative thinking, and making collaboration work. My colleague Katie Plaisance, a philosopher of science, offers some incredible courses (INTEG 210, 220, and 221) that I wish I could have taken in my second year of undergrad! Then in their third and fourth year, students take courses that focus more on developing higher-level skills (inclusive of thinking/cognition, feeling/affect, and doing/psychomotor skills), most of which are related to collaborative design, futures thinking, and research methods and modelling. The degree culminates with an ambitious year-long capstone design or research project.

I taught many first-year basic design courses during a 38-year career. End of term course evaluations often seemed premature to me. Typically, the value of the ideas and the skills students gained became evident several years after the course ended, when they tackled increasingly difficult projects. Is that true for INTEG 120, as well? 

Yes. Many students are most comfortable with passive learning, and this course really pushes them out of their comfort zone. Often, those who either appear resistant or uninterested come back later to tell me of the positive impact the course has had on all their subsequent courses, both within KI and across the university.

One hazard is that the foundational skills we build in INTEG 120 may initially appear somewhat remedial. They are not. Students identify and practice the explicit skills I mentioned earlier, but they do so within a broader framework that emphasizes the importance of being vulnerable and open to learning from people with different life experiences, of recognizing uncertainty and change, and of cultivating curiosity and intellectual humility. My colleague Igor Grossman (in psychology) has shown that these are all foundational components of wisdom, and like metacognitive skills more generally, I see them as essential to long-term learning in any discipline.

With INTEG 120, I am not trying to teach a bunch of isolated tips and tricks that will just help students raise their GPAs a bit. I want students to master those skills, of course, but my goals are more wholistic and developmental. I want to create space for students to assess their mindsets, appreciate their strengths, and develop their learning skills in a way that will help them develop knowledge, skills, and even wisdom, over a lifetime.

Of course, these changes don’t happen in a single semester. I can’t tell you how motivating it is to hear about the impact of INTEG 120 from some of our graduates who are now years into their professional careers.

What do you find most rewarding about teaching?

I love to see significant transformation, such as seeing students develop higher-level cognitive capacities like creative and critical thinking. But what truly inspires me is seeing students transform their own self-concepts, embrace uncertainty and diversity, and approach the world with a sense of curiosity, openness, and confidence. 

All the KI professors are highly skilled educators, but they are also identified on the website as "researchers." Can you briefly describe one aspect of your current research?

Like most other professors on campus, KI professors spend roughly 40% of their work time conducting research and sharing the results of that work to their peers and various other groups of people (including students and community members). My PhD is in Sociology, but I also work in a variety of interdisciplinary research fields, including network science, computational social science, and cognitive social science. Most of the social and political problems that interest me transcend any discipline, which means I am continuing developing the same foundational skill set that INTEG 120 is designed around. In fact, I try to run my research lab (Netlab) in a way that supports me and my students as we continue to develop and refine those foundational skills and mindsets.

Among other things, I am currently leading a 5-year research project focused on understanding whether and how coordinated information operations – such as disinformation campaigns and censorship – influence political polarization and the evolution of public opinion and belief systems more generally. This requires statistical analyses of change within and across countries over time on the one hand, and a micro-level focus on how individual people think, feel, and behave within the contexts of their own social relationships and networks on the other. My team and I are especially interested in the role that social media and new technologies play in all of this. Like many of the projects I work on, this one requires carefully integrating knowledge – usually in the form of theory, methods, and models – from many different fields.

I know you said “briefly,” but if you’ll allow it, I’d like to make one more connection here. I know my students will go on to do many different things, most of which will look very different from the specifics of my work. But we are on the same journey; we are trying to develop the same foundational skillset regardless of the specifics of our work. Fully embracing the reality that my students and I need the same foundational learning skills and mindsets to thrive helps me reduce the distance between my role as a teacher and my role as a researcher.

One of the ways I’ve grown as both a teacher and a researcher is by struggling to make implicit habits of mind explicit enough to teach to another person. For example, I’m a very model-based thinker, and I have been for as long as I can remember. Regardless of what problem I am working on, I try to construct multiple mental models that force me to adopt different perspectives, if only temporarily. Training your mind to think like this enables you to see the same thing in different ways and to interrogate the implications of each. This provides more depth, helps generates novel insights, and encourages more intellectual humility and a collaborative mindset.

Well-intended "interdisciplinary programs" have become developed with mixed success by many universities in the USA. What distinguishes Knowledge Integration from most other interdisciplinary programs?

This could be a lengthy list! Let's focus on four related things.

First, the course progression is very deliberate and intentional. Any well-designed curriculum places foundational coursework at the beginning and grows both deeper and broader over time. In KI, the connections are more explicit and intentional. Most of us have been teaching our courses for many years and we all know and rely on the content in other KI courses to help us build the most resilient and robust education possible for KI students.

Second, we view the curriculum as an iterative design project that can be improved constantly. We take a day or two each year to share our latest insights as educators and update our courses. Crucially, we factor student feedback and perspectives into this process, at the level of individual courses and the program overall. We iteratively improve KI using the same frameworks – design and futures thinking in particular – we teach our students!

Third, we aim to go beyond the traditional “arts and sciences” menu of courses that comprise the core of many other interdisciplinary programs. This broader vision stems from the early influence of engineering, design thinking, and maker culture in KI. I am personally very grateful to folks like Ed Jernigan, Paul McKone, Kim Boucher, and Linda Carson for envisioning what undergraduate education could be if it was embedded in a more inclusive and diverse learning environment that embraces the relationship between “knowing” and “doing.”

Fourth, the foundational thinking frameworks we emphasize in KI – such as design thinking, systems thinking, and futures thinking – are powerful and flexible; they can help you and your collaborators make progress on just about any problem you might work on.

During my ten-week visit to KI in 2022, I was also impressed by the collaborative mindset each professor brought to the department and honestly, the understanding and respect with which each views each other.  

Good observation! We are a deeply collaborative department, and as I mentioned earlier, we practice the same skills and mindsets we teach our students. Among other things, KI is what it is because we all appreciate the importance of diversity, intellectual humility, open-mindedness, and genuine deliberation. I feel most fortunate to have landed in such a lively and dynamic department!

This interview is part of a project conducted by Dr. Mary Stewart during her two-month fellowship at the University of Waterloo in the fall of 2022. Thank you to Dr. Stewart for her work in highlighting the transdisciplinary nature of the KI program and its community members, and to Fulbright Canada for making this opportunity possible.