A collection of SERJ papers by new researchers - 2025

Anne Patel

An inferentialism-based framework for capturing statistical concept formation over time

Statistics education researchers have been challenged to consider the theory of inferentialism in understanding concept formation in students. A critique of inferentialism is that no comprehensive method has been formulated to use the theory in practice. In this paper an inferentialism-based framework is presented that appears to be capable of explicating the development of statistical concepts during learning. By following six 11-year-olds’ learning over several statistical modelling cycles using TinkerPlots, the framework was used to capture their interrogative cycles of noticing and wondering, giving and asking for reasons, and sanctioning and censuring, as well as oscillations between concretising language about actions and conceptualising language towards concept formation. Five teaching episodes occurring near the beginning of a 12-week learning sequence are used to illustrate how the framework might be able to capture student concept formation over time.

Chelsey Legacy

Vampires and star-crossed lovers: Secondary teachers’ reasoning about the connections between multivariate data and visualization

As ideas from data science become more prevalent in secondary curricula, it is important to understand secondary teachers’ content knowledge and reasoning about complex data structures and modern visualizations. The purpose of this case study is to explore how secondary teachers make sense of mappings between data and visualizations, especially depictions of multivariate relationships. The participants were 14 in-service secondary teachers who were video recorded as they worked through three sets of activities. In these activities, participants created a visualization (network graph) from multivariate data, encoded raw data for several attributes from visualizations depicting multivariate relationships, and structured data into a tidy format. With minimal instruction, participants were able to create visualizations when given data representing multivariate relationships. They were also able to structure non-tidy data into a tidy format with some scaffolding and discussion. Notably, creating data tables from visualizations, especially relational tables, seemed more challenging for them. These results provide insight into secondary teachers’ reasoning about connections between multivariate data and visualization.

Karin Landtblom

Which measure of central tendency is most useful? Grade 6 students’ expressed statistical literacy

Recently, the importance of statistical literacy has been stressed, and three central concepts in statistical literacy are the measures of central tendency: mean, median, and mode. This study explores aspects of statistical literacy expressed by 12–13-year-old students, focusing on mean, median, and mode. Their responses were analysed using a framework of statistical literacy that includes knowledge and dispositional elements. The results showed that students’ descriptions of the measures were mainly based on mathematical and vocabulary knowledge. When discussing what measure was easiest or hardest to explain, a variety of conceptions were expressed. Some explanations about the usefulness of the measures were related to context knowledge. Here, the median was an exception as students gave neither examples of contexts nor found the median useful outside the classroom.