Anna Fergusson (University of Auckland | Waipapa Taumata Rau)
Abstract
I migrated into the world of statistics and data science education research after already establishing a successful career as an educator: first as a high school teacher for 12 years, and then as an introductory-level statistics lecturer for eight years. For the last three years, I have been trying to find “my place in the world” of research, and have found at times that the models I once relied on for informing my career decisions have not always been that useful for my new journey. As a researcher who actually loves spending time on developing teaching materials and engaging with students, I often find myself balancing competing priorities, making it difficult to get everything ticked off my “must see” list of research tasks! In this talk, I will share some of my initial experiences of navigating the sea of statistics and data science education research, using examples from my work to illustrate the opportunities and challenges of starting my journey in Aotearoa New Zealand. I will discuss how my experiences with teaching at the high school and university levels, as well as my background in data technologies, have shaped my evolving perspectives and research priorities. I will also consider what could be useful models for embarking on, and supporting, early career research paths within statistics and data science education, and reflect on the importance of collaboration, inclusivity, and adaptability.
Bio Sketch:
Anna Fergusson is a Lecturer in Data Science and Statistics at the University of Auckland (Waipapa Taumata Rau). She has led several large-scale statistics and data science curriculum design projects and has worked with the New Zealand Ministry of Education and the New Zealand Qualifications Authority on the development of national curriculum frameworks, assessment standards, examination papers, project-based tasks, and teaching resources for statistics. Her research focuses on technology-based and technology-informed pedagogy and assessment systems, and frameworks for task design and integrated statistical and computational thinking practices. She supports and advances her teaching, research, and data science practice by designing and creating new software tools and educational technologies.