Teaching
Teaching roles, philosophy, and materials.
Teaching Philosophy
The thing students most need from a quantitative psychology course is not a procedure to follow — it's a feeling for why the procedure works, and a sense of what breaks when the assumptions don't hold. That intuition is hard to transmit through lecture alone. My approach is to put students in contact with data as quickly as possible, so they can develop that intuition by doing rather than watching.
In cognitive psychology and research-methods labs, students took part in perception and memory experiments and analysed pooled class data. This gives us a shared example to discuss: what did the experiment measure, which explanation fits, and what would distinguish it from an alternative?
I'm particularly interested in making the mathematics of cognitive science accessible to students who don't come in with a strong quantitative background. Bayesian reasoning, evidence accumulation, signal detection — these ideas are genuinely comprehensible if you encounter them through concrete examples first and formalism second. I hold Associate-level teaching accreditation through CIRTL (Center for the Integration of Research, Teaching and Learning), completed in 2024.
I mentor undergraduate and graduate students in experimental design, programming, and data analysis — and I'm particularly attentive to the moment when someone hits a wall with quantitative material. Getting students past that wall, with their confidence intact, is one of the more satisfying things about this job.
Guest Lecturer
Lecture and student-led presentations on k-means clustering as an introduction to unsupervised machine learning in a psychology context.
Course Instructor
Sole instructor for a large introductory course with a diverse cohort including students with varied educational backgrounds. Course covered attention, perception, memory, reasoning, learning, personality, development, and social behaviour. Teaching emphasised active participation through in-class polls, low-stakes knowledge checks, and structured reflection prompts, with the goal of making psychological science feel applicable and worth engaging with consistently.
Lab Demonstrator & Grader
Honours-level course covering advanced statistical techniques, analytic strategy, design planning, data handling, and Bayesian analysis. My role was to guide students through practical analyses and questions about research design.
Lab demonstrator for a course covering attention, memory, word recognition, reasoning, and problem solving through hands-on experiments. Also adapted materials for online delivery during the pandemic.
Assessed methodology, data analysis, and scientific writing of honours-level cognitive psychology research projects.
Courses I'm Prepared to Teach
I can contribute to curricula across the following areas, from introductory to advanced level:
- Cognitive psychology (perception, attention, memory, reasoning, decision making)
- Research methods and experimental design
- Frequentist and Bayesian statistics
- Mathematical psychology and cognitive modelling
- Machine learning methods and applications in psychology
- Human-AI interaction and collaboration
- Introduction to programming for psychological research (Python, MATLAB)
I'm particularly interested in developing courses that build a bridge between classical cognitive psychology and the computational methods that are reshaping the field — accessible to students without a strong mathematics background, but rigorous enough to be genuinely useful.