64th ISI World Statistics Congress - Ottawa, Canada

64th ISI World Statistics Congress - Ottawa, Canada

Statistical Literacy and Quality: two sides of the same coin?

Author

PC
Pedro Jose Campos

Co-author

Conference

64th ISI World Statistics Congress - Ottawa, Canada

Format: CPS Abstract

Session: CPS 53 - Teaching statistics III

Tuesday 18 July 4 p.m. - 5:25 p.m. (Canada/Eastern)

Abstract

Research in statistics education has focused on learning and literacy approaches, such as the SOLO taxonomy - Structure of the Observed Learning Outcome – that classifies student learning outcomes from any classroom activity, unit or programme (Biggs and Collis, 1982); the Learn by Doing in Statistics (Smith, 1998), who advocates that statistical reasoning should be developed by incorporating active-learning strategies that allow students to supplement what they have heard and read about statistics by actually doing statistics; the Profile of Statistical Understanding (Reading, 2002), which is aimed at providing a tool to assist educators to identify what 'can be' expected of students rather than what 'should be' (Reading, 2002); and the models of adult statistical literacy (Gal, 2002, 2003), who argues that statistically literate behavior is predicated on the joint activation of five interrelated knowledge bases (literacy, statistical, mathematical, context, and critical), together with a cluster of supporting dispositions and enabling beliefs. There are other approaches, such as Data Literacy (Gould, 2017), Statistical Reasoning (Sabbag, Garfield and Ziefller, 2018) but few or none take into consideration the link with quality aspects, especially when literacy is viewed from the perspective of official statistics.
Eurostat defines quality of statistics as the degree to which the characteristics of statistics fulfil the requirements of users of statistical information. The product quality dimensions defined by Eurostat in the European Statistics Code of Practice (Eurostat, 2011) principles covering statistical output include Relevance, Accuracy, Reliability, Timeliness, Punctuality, Coherence, Comparability, and Clarity. These principles, all or some of them, should be part of statistical literacy, as there is no point in thinking about literacy without thinking about quality. On the other hand, quality only makes sense if stakeholders are literate.
This paper aims to reflect on the importance of thinking about the promotion of statistical literacy also involving the aspects of quality. To this end, it is suggested to compare the principles of quality with the various classifications of literacy to try to find the common aspects and thus make a correspondence between these two sides of the same coin.