Angel Gurria, in the introduction to the 2014 OECD Yearbook, wrote ‘Building an inclusive, resilient world relies mostly on the input of all citizens’. In many countries, citizens are encouraged to participate in public policy decision processes. However, there are barriers to be overcome before this idea can become a reality. Sound evidence-based decision-making in private as well as public life requires quantitative reasoning skills, and (at least as important) positive attitudes to hard evidence i.e. a willingness to engage with statistical data.
ProCivicStat promotes the empowerment of young people by developing their ability to understand evidence about key social phenomena that permeate civic life – such as racism, migration, demographic changes, equality, and unemployment among different subgroups.
Development of such abilities can contribute to the Europe2020 goals whose realization requires responsible involvement and action from individual citizens and NGOs, as partners to governments’ actions. Global initiatives such as the United Nations Sustainable Development Goals reflect nations’ desires for a world that is fairer, and supports sustainable development. We believe that there has never been a more auspicious time for informed citizens globally to push their own governments to achieve the goals they have set themselves about social justice and the environment. But what is an ‘informed citizen’?
We begin with a bald (but we believe self evident) assertion: every interesting social phenomenon is multivariate, has non-linear relationships, and has confounding variables.
So ‘informed citizens’ need to be able to understand complex phenomena. However, there are serious problems with the ways that statistics is taught in most countries in high school and at the introductory undergraduate level (for a review, see Batanero, Burrill, Reading, 2011; for recommendations, see GAISE 2016 and this website). In essence, most curricula focus on single (or perhaps two) variable problems; they focus on technical mastery of mathematical techniques developed over 100 years ago; they use artificial data; and they make little use of data visualisation techniques. (We acknowledge that this characterisation does not apply universally, and that islands of excellence can be found). Statistical techniques taught and data sets used in current curricula (at the high-school and introductory university levels) are misaligned with the needs of citizenship, and are not geared to enable learners to transfer any skills they acquire to their duties as engaged citizens (see Cobb, 2015; Engel, 2016; and Ridgway, 2016).
It is unreasonable to exhort teachers to change curriculum practices without support. ProCivicStat set out to provide support to teachers in high schools and universities by creating resources that engage students with multivariate data on a range of interesting topics relevant to their future roles as active citizens. We show how digital technology can be integrated into teaching and learning of statistics by using simple, powerful, tools for data visualization and analysis. Addressing socially meaningful issues into teaching is expected to increase motivation, enable students to experience how statistical analyses play a role in understanding the pressing social and political issues of our time, and develop positive student attitudes towards quantitative information used in the governance of society.
ProCivicStat also aims to strengthen Europe’s innovation capacity through the creation of a common framework for higher education institutions that foster the modernisation of education.
Batanero, C., Burrill, G., and Reading, C. (Eds.). (2011). Teaching Statistics in School Mathematics-Challenges for Teaching and Teacher Education: A Joint ICMI/IASE Study. Springer: Dordrecht.
Cobb, G. W. (2015). Mere renovation is too little too late: we need to rethink our undergraduate curriculum from the ground up. The American Statistician, 69(4), 266–282.
Engel, J. (Ed.). (2016). Promoting understanding of statistics about society. Proceedings of the IASE Roundtable Conference. www.iase-web.org/Conference_Proceedings.php.
GAISE. (2016). Guidelines for assessment and instruction in statistical education: College report 2016. Alexandria, VA: American Statistical Association.
OECD. (2014). OECD Yearbook 2014, OECD Publishing: Paris. https://doi.org/10.1787/observer-v2013-5-en.
Ridgway, J. (2016). Implications of the Data Revolution for Statistics Education. International Statistical Review. doi:10.1111/insr.12110.