Designing a sequence of activities to build reasoning about data and visualization

Abstract

Our complex world requires multivariate reasoning to make sense of reality. Within this paper, we offer a sequence of activities designed to develop multivariate reasoning by explicitly connecting data and visualization. The activities were designed based on a hypothetical learning trajectory we conjectured for students with limited experience with multivariate visualizations. Drawing from evidence collected using these activities in a series of professional development sessions with in-service teachers, we find that the activities functioned as intended, and thus we promote these activities for developing students' multivariate reasoning at the secondary and post-secondary level. We detail specific challenges the teachers faced, and based on these results, offer our reflections and recommendations for curricula and teaching.

Visualizing statistical edutainment: What you see is what you get

“…What is a catchy headline that captures "what's going on this graph"? Leveraging this activity, a teacher might then utilize a recent paper [56] that provides a rich class of activities that build multivariable reasoning both in the interpretation of graphs and in the building of visualizations.…”

Introduction to rethinking learners' reasoning with nontraditional data

“…Rao et al's work [17] focuses on developing secondary teachers' multivariate reasoning through activities designed to support teachers' understanding of the principles of tidy data and data visualization. They carefully designed a sequence of activities-beginning with moving from data to visualization (using network graphs), followed by moving from visualization to data, and finally introducing principles of tidy data to support teachers' learning of visualization and the structure of data.…”

“…The articles in this issue focus on new approaches to the teaching and learning of data practices related to messy, complex, or nontraditional data from the youngest learners [8,19] to secondary learners [14,17], undergraduate students [15,16], graduate students, teachers, and researchers [2,5,9,17]. There are two overarching themes in the articles in this special issue: new ways to consider data visualizations in the classroom [2,5,14,17,19] and new approaches or elements that need to be considered in the teaching and learning of data science practices [8,9,15,16].…”