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IPS115 Reija H.

Table 1. Six key recommendations by ProCivicStat
#1 Statistics education activities should promote engagement with
social issues and develop leaner’s critical understanding.
#2 Use relevant data and texts, and highlight the multivariate,
dynamic and aggregated nature of social phenomena.
#3 Embrace technologies that enable rich visualizations and
interactions with data about relevant social phenomena.
#4 Teaching methods should develop skills of critical interpretation
of a wide variety of data and text sources.
#5 Assessments should examine the ability to investigate and
critically understand data, statistics findings and messages about
key social phenomena.
#6 Promoting the understanding of civic statistics requires a
systemic change and collaboration by relevant stakeholders.
Source: (ProCivicStat, 2018)

Media sources should be evaluated based on valid knowledge – not
feelings or beliefs. This is where statistics form an integral part. Sashi Sharma
outlines a few examples of where statistical literacy helps to make sense of the
news media: for example, sensational news headlines (“Kids who watch
‘Sesame Street’ do better in school” (Sharma, S. [2017]) that are often based
on singular studies, with small sample sizes, confounding variables and
sampling error. Sharma puts it well: “Indeed, citizens without statistical literacy
may not be able to discriminate between credible and incredible information
and will have difficulty in interpreting, critically evaluating and communicating
reactions to such messages” (Sharma, S. [2017]).
There are several formal definitions of statistical literacy available (See Gal,
I. [2002]; Schield, M. [2010]; Wallman, K. [1993]). On a general level, the
“traditional” view to literacy (‘literacy leads to development’) differs greatly
from the new concept, which argues that literacy is rooted in social customs
and has a social meaning. Social literacy implies training those who want to
communicate something (UNESCO Institute for Lifelong Learning. [2013]). In
recent years, ISLP has been concerned with responding to this more modern,
and broad, concept of literacy. The definition of the term ‘statistical literacy’
by Gould, R. (2017) reveals the demands of a modern society, such as
understanding issues of data privacy and ownership and the provenance of
data and understanding how data are stored and how representations in
computers can vary and why data must sometimes be altered before analysis.
Finally, statistical literacy leads us to the term data literacy. According to
the Oceans of Data Institute (2015): “The data literate individual understands,
explains and documents the utility and limitations of data by becoming a

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