teaching

I am passionate about research methods teaching. I have designed, developed, and led quantitative methods courses at both undergraduate and postgraduate research level. My approach emphasises not just technical competence but the capacity to interrogate statistics critically—equipping students to engage with quantitative claims as informed sceptics, not passive consumers.

Taught Modules

Research Methods Training

Level: Year 2 Undergraduate

An introduction to applied quantitative analysis in the social sciences, with a strong emphasis on critical engagement with statistics. Rather than treating numbers as authoritative, this module equips students to interrogate quantitative claims, understand their limitations, and provide grounded critique. Students develop confidence to both conduct and critically assess quantitative research in their further studies and careers.

The module covers the use of quantitative methods in education research, basic statistical methods, reproduction of published analyses, and formulation of substantive research questions.

Introduction to Quantitative Research in Education

Level: Research Students (PhD)

A foundational course for beginners in quantitative research, providing grounding in quantitative analysis including epistemology, research design, survey-based data collection, and descriptive methods for summarising data and assessing relationships. The course prioritises accessible software solutions with low learning curves, removing unnecessary barriers to engagement with quantitative methods. Examples are drawn from social research and policy applications. Delivered through eight two-hour in-person workshops combining concept introduction with discussions and practicals.

Intermediate Topics in Quantitative Education Research

Level: Research Students (PhD)

An advanced workshop series for those seeking to develop their quantitative research skills further. The series covers effective measurement, survey validation, p-values and effect sizes, regression modelling, structural equation modelling, and drawing conclusions from quantitative research. Workshops apply taught methods to real-world data analysis.

The five standalone workshops cover: surveys (samples and validation); p-values, effect sizes, hypothesis testing and meta-analysis; designing and interpreting regression models; structural equation modelling; and causal inference through random assignment and difference-in-differences.

Standalone Workshops

Doing Regression Analysis

A workshop introducing multiple linear regression for researchers working with complex, multi-layered phenomena. Covers issues of causality in quantitative research, simple linear regression and line-of-best-fit estimation, and multiple regression. Combines brief lecture segments with hands-on exercises using widely used survey data. Delivered across statistical software platforms including Stata or R (through RStudio).

Supervision and Other Teaching

Dissertation Supervision: Postgraduate and undergraduate dissertation supervisor across Education Studies programmes.

Guest Lecturing: Contributions to modules including Higher Education and Universities in Global Context and Understanding Higher Education: Trends and Issues.

Seminar Leadership: Seminar leader for modules including Youth in a Globalising World.