My objective as an educator of quantitative social science is not only to provide my students with the knowledge of statistical techniques but also to teach them what policy, social, and personal implications sociological research can have on their everyday lives.
I want my students to excel at quantitative methods while mastering programming in R and Python. I plan to achieve this by trying out novel ways to teach. In 2015, Dr Silvia Bartolic (PI) and I worked on a flipped-classroom project called “Quantitative Arts: Scientist by Nurture”. The idea was born in a sociology research methods class, where we realised that universities need to improve current curricula on how research design was taught to social science students. Aiming to make quantitative research methods more accessible, with the support of the UBC Teaching and Learning Enhancement Fund and the American Sociological Association’s Carla B. Howery Teaching Enhancement Fund, we developed online tutorials and a new flipped-classroom course for research methods classes. With teaching research projects like these, I hope to help students explore new ways to learn.
In my future academic career, I want to experiment with various teaching strategies. I will combine traditional teaching methods with new experimental ones because innovation is essential to figuring out the teaching style that best suits a particular class/cohort of students. It is the experimental and practical side of the challenge that I find interesting about teaching. With that said, my own preference in style of teaching would be the flipped-classroom technique, where students learn concepts outside of the classroom (using, for instance, instructor-created video tutorials) while the analysis of the material (programming labs, problems, quizzes, and discussions) happens in class. This is the style I implemented at the American University of Central Asia, where I worked in 2017.
On top of regular teaching, I mentored students from research methods classes to publish their work in undergraduate research journals. One of my students published his work in the Sojourners, an undergraduate sociology journal, and was awarded the Undergraduate Sociology Award for his work. I supervised a Master’s student at the OECD Academy and an MSc student at Oxford. I also worked as a college advisor for six Master’s students at St Antony’s College, Oxford. Moreover, I was a mentor for the PhD Connections Initiative at UBC, where senior PhD candidates mentored first-year PhD students to navigate graduate school. I led a teaching assistants’ training session for sociology graduate students to grade undergraduate papers and organised professional development seminars in 2013-2014.
In my classroom, I teach my students that data can reveal a lot of information even when we know very little about its origin. In teaching statistical methods classes, I introduce the Titanic mortality data to students without explaining the data. Instead, I ask the class to guess what these observations represent by analysing them. Usually, students accept the challenge and start exploring the data independently. In their explorations, students often notice that the mortality rates are unusual compared to the general population. They find that mortality rates are unusually high among men than women and in the lower class than in a higher class. Even if they do not always guess the correct answer, students’ conjectures are often quite close to the actual. For instance, they can conclude that these data represent casualty numbers from an armed conflict. This exercise teachers them to critically evaluate data and develop skills in explorative analysis and learn about how to interpret data.
Overall, I want my students to leave my courses having mastered the skills to apply theoretical and statistical knowledge to their everyday lives. I prepare my students for future careers by training them to apply scientific knowledge to everyday life and analyse and quantify real situations using sociological theories and statistical methods.