What does data science mean for statistics education?
Presented at: 9 March 2022; 22:00 UTC
Webinar duration: 90 minutes
Presenter(s): Rob Gould (USA) and Helen MacGillivray (Australia)
Data Science Education and Statistics Education: Why the distinction is needed
Rob Gould - Dept. of Statistics, University of California, Los Angeles
For decades now, statistics educators have worked to achieve wide-spread statistical literacy. And now, well before that task is accomplished, along comes Data Science Education and data literacy. I’ll explain why these terms are more than just a new label for old things and, based on my experiences on a team that designed and implemented a fairly large-scale secondary level data science program, describe challenges towards achieving wide-spread data literacy.
What’s different, what’s not, and what to do with the holes in the data science and statistics educational road
Helen MacGillivray - School of Mathematical Science, Queensland University of Technology
The science, and its practice, of data, variation and uncertainty has always developed and grown in response to real problems and in tandem with the conceptual, technological and mathematical tools which help solve them. However, the progress of awareness and education in the statistical and data sciences has a propensity to be bumpy, fraught and often fragmented. This tends to be more so than in other disciplines because of the very human craving for certainty and ‘answers’, and the inextricable linkages to and across increasing endeavours and fields – Rodriguez’s (2013) ‘big tent’ is now even bigger and more complex. Analysis of holes, traps and bumps in the statistical education road can offer valuable lessons for data science education. This presentation aims to provide a brief overview, touching on leadership and advocacy, teacher education, resourcing and assessment, and including some ideas for how the statistical community can have the influence and impact vitally needed in the data science hurly-burly.
Rodriguez, R. (2013). Building the big tent for statistics. J . Amer. Statist. Assoc, 108, 1-6.