Civic Statistics and iNZight: Illustrations of Some Design Principles for Educational Software

Chris J. Wild () and Jim Ridgway ()
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Chris J. Wild: The University of Auckland
Jim Ridgway: The University of Durham

Chapter Chapter 10 in Statistics for Empowerment and Social Engagement, 2022, pp 237-266 from Springer

Abstract: Abstract The PCS project has made good use of iNZight in exploring topics such as migration, gender inequality, childhood malnutrition, and natural disasters. Further examples of Civic Statistics topics that have been addressed using iNZight are provided here, along with a range of examples of creative ways to display data. The chapter outlines the advantages of technology enhanced statistics education and software requirements; maps some analyses which are central to Civic Statistics and shows how these can be conducted using iNZight. Examples include working with multivariate data, exploring subgroups within data, using multiple representations, analysing and reanalysing, and telling stories grounded in evidence. Often with complex social/civic datasets it is necessary to explore changes over time, and to explore spatial patterns. Here, we describe software features that facilitate data exploration for naïve users that include both direct guidance and hooks to encourage engagement and further learning, and also features for advanced users, such as the automatic generation of R code for documentation and software reuse. Software for analysing data is evolving rapidly to accommodate new sorts of data, new techniques for analysis, and new methods to present data. Therefore, the chapter concludes by describing developments to iNZight that are in progress.

Keywords: Software designSoftware design; Multivariate data; Multiple representations; Disaggregation; Complexity reductionComplexity reduction; Complex survey designsComplex survey designs (search for similar items in EconPapers)
Date: 2022
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DOI: 10.1007/978-3-031-20748-8_10

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