This is a session of Topic 5: Statistics education in the workplace, government and across disciplines

Session 5H (Friday 13th, 11:00-12:30,   Level 2 - Seminar Room 2)

Statistics Education Across Disciplines: pedagogy and assessment for statistical literacy, critical thinking, and evidence-based practice

Organizer

• Rossi Hassad (United States) : Session chair

Abstract

Statistical literacy and statistical competence are now universally recognized as essential skills for most academic majors and disciplines. The underlying rationale encompasses the need for data-driven decision-making and policy development, as well as evidence-based practice, which are applicable to all disciplines, especially with the increasing availability of data, not to mention, the “big data” revolution. Adding to this, is the expanding role of non-statisticians as data analysts. Indeed, the emphasis on these skill sets has been the focus of the statistics education reform movement for more than two decades. Nonetheless, there is a consensus among educators that these skills continue to be lacking among graduates entering the workforce, and this is generally attributed to the persistence of the mathematical approach to teaching introductory statistics, rather than emphasizing conceptual understanding and statistical literacy. As Hogg (1991) noted, “good statistics is not equated with mathematical rigor or purity, but is more closely associated with careful thinking”. This session will address strategies for teaching statistics to diverse disciplines, using non-technical language and problem-based learning methods to promote understanding, appreciation, and engagement in the analysis, appraisal, and use of data. Selected statistical techniques which can be impactful across disciplines in helping to understand complex patterns within populations, will be included. As well, assessment approaches will be explored, specifically the effectiveness of the multiple-choice question format for assessing critical thinking about data as the core element of statistical literacy.

Papers