meet the SIG Leads

Alyssa has been an Assistant Professor in Psychology at Toronto Metropolitan University since 2018. She is the director of the Psychology and Statistics Education Research (PASER) lab, where her research group examines topics such as statistics attitudes, statistics anxiety, and methods for improving statistics education in psychology. She is especially interested in understanding how students learn and engage with statistical software. Alyssa has taught basic and advanced undergraduate statistics, but most of her teaching is at the MA/PhD level with courses such as regression, multilevel modeling, structural equation modeling, or multivariate methods. She is also an Associate Editor for the Statistics Education Research Journal and Chair of the Canadian Psychological Association's Teaching of Psychology section. Alyssa is 'mom' to a toddler and corgi and a huge fan of women's basketball.

Anna is a lecturer in the Department of Statistics at the University of Auckland.  Her research within data science and statistics education focuses on technology-based and technology-informed pedagogy, including but not limited to: large-scale teaching and assessment practices and tools; introduction of computer programming for data science and associated design principles for tool and task design; tool-mediated development of statistical concepts and reasoning, such as graphical and visual inference;  and frameworks for observable integrated statistical and computational thinking practices.

Nicola is currently a teaching-focused Lecturer in Health Data Science based in the medical school at Lancaster University (UK).  Her research interests include teaching statistics to medical and health sciences students, with a particular focus on programming and statistical software. She is also interested in the relationship between how we teach statistics and how we communicate statistics to the general public. Nicola has previously taught programming and statistics to a range of audiences in both industry and academic settings.

Letetia holds a Ph.D. in Mathematics and an M.Phil. in Statistics from the University of the West Indies, St. Augustine Campus (UWI-STA). Currently, she is a Project Officer, providing Statistical Consulting on institutional data and has over a decade of experience lecturing Mathematics, Probability, and Statistics at the tertiary level. She previously coordinated the Mathematics Help Centre, assisting students with difficulties in quantitative courses and regularly engages in research and outreach. 

Letetia is a part of a Social Statistics Research Cluster at the Department of Behavioral Sciences, exploring research on Statistics Anxiety in students. She also lectures various courses including a Graduate Course in Advanced Statistics in Psychology and conducts workshops on statistical software using IBM SPSS and R. Her research interests encompass data-driven models for Higher Education, multidisciplinary applications of mathematical and statistical models for sustainability, and Statistics Education pedagogy. 

Letetia is also affiliated with the Royal Statistical Society (RSS) and the American Statistical Association (ASA). As the first Women in Data Science (WiDS) Trinidad and Tobago Ambassador, she is closely involved in WiDS Worldwide through Stanford University, which highlights exceptional women in Data Science. Letetia is passionate about teaching, mentoring, and outreach and is dedicated to emphasising the importance of Mathematics and Statistics across various fields.

Click here to view Letetia's LinkedIn profile.

Fareena is currently an Instructor in Sociology at the University of the West Indies, St. Augustine Campus. She teaches courses in introductory statistics, quantitative and qualitative research methods and health sociology. Fareena is also a PhD candidate in Sociology; her research focuses on food consumption patterns among adults in Trinidad and Tobago during the COVID-19 pandemic. Her interests include statistics education, health and illness, and nutritional sociology. 

Lazaros Gonidis has been involved with teaching methods and statistics in Higher Education for more than 10 years and is currently a Psychology Lecturer at the University of Sussex, lecturing psychological methods and statistics. He always had a keen interest in experimenting with gamification and other novel teaching methods, and is excited to see how Higher Education will respond to the expansion of AI. He has also researched how AI can affect people’s compliance and judgement, and is looking forward to building a network of scholars that will research the use of AI in teaching statistics and methods.

Hilary Watt (expert medical statistics teaching fellow) develops innovative statistics teaching methods. Her passion is language and images that foster conceptual understanding, especially of p-values and of confidence intervals. She leads discussions (at conferences and beyond) on how best to interpret confidence intervals and p-values. She pays attention to common major misconceptions and poor standards in published statistical interpretations (“replicability crisis”), with resulting publications. She develops and trials teaching strategies designed to overcome poor standards/ fundamental misconceptions. She has publications in progress on the research collaboration that she leads, with data from medical statistics educators. She is author of Data Wrangling RECIPES in R online resource. She is medical researcher co-supervising fellowship/ students and awarded statistician NIHR funding to undertake randomised controlled trials.