Statistics Education Research Journal

Systematic review of statistical ability measures

2025-06-12T18:48:38+00:00

This systematic review investigates measures of statistical ability in published literature to understand how statistical ability has been conceptualised and assessed. The review examines the components, reliability, validity, and correlations of these measures with cognitive (e.g., intelligence) and non-cognitive (e.g., attitude towards statistics) factors. From 51 papers, 25 unique measures were identified, with 60% assessing knowledge-based competencies. The validity evidence suggests that these measures assess their intended learning outcomes. Correlations between the measures and cognitive factors were stronger when closely aligned with the assessed ability. Research reporting correlations between statistical ability measures and non-cognitive factors is relatively limited. The review aims to inform educators and provide direction for future measurement development to address the identified gaps in the literature.

Investigative questions with secondary data: Characterizing high school students’ questions and the role of data visualization in refinement

2025-08-22T07:53:17+00:00

We investigated how high school students formulate and refine investigative questions when conducting a statistical investigation with secondary data. The data consisted of students’ written activity reports and email-based, post-interview responses collected after a seven-session instructional sequence in which CODAP served as the primary tool for multivariate data analysis. We distinguished initiating investigative questions (IIQs) from analysis-phase investigative questions (AIQs) implied in students’ analysis plans and characterized both sets across five analytical components: variables, clarity of population, intent, feasibility of drawing conclusions from the data, and global view of data. We then used thematic analysis to examine how data visualization appeared to be involved at points where IIQ-to-AIQ refinement was evident. Compared with IIQs, AIQs more often included a greater number of clearer variables and took forms that were more feasible for drawing conclusions from the given dataset. Across the three episodes analyzed, the representational and exploratory functions of data visualizations appeared to support refinement by helping students operationalize everyday terms, narrow populations, anticipate interpretable relationships, and set aside uninformative variables. This study offers classroom-based empirical insights into investigative questions in the context of secondary data and into the potential role of data visualization in their refinement.

Toward a taxonomy of research on statistical knowledge for teaching

2025-12-29T14:44:33+00:00

The knowledge needed to teach statistics overlaps with, but is not limited to, the knowledge needed to do statistics. Hence, research on statistical knowledge for teaching should not be limited to the study of teachers’ subject matter knowledge. This article outlines a taxonomy describing multiple foci for research on statistical knowledge for teaching. The theoretical structure for the taxonomy is sketched and then stress-tested using a collection of articles from the Statistics Education Research Journal. Challenges of using the taxonomy to categorize research are made explicit, and ideas for navigating them are provided. It is shown how the taxonomy can serve as a framework to track the prevalence of various research foci in the field and plan future studies. Directions for future scholarship to refine the taxonomy itself are also proposed.

Undergraduate students' inconsistent routines when engaging in statistical reasoning concerning mode

2024-11-19T14:59:44+00:00

Using the commognitive construct of routine—repetitive rules or patterns observed in statistical discourse—we aimed to investigate how students use inconsistent routines when engaging in statistical reasoning about mode in the context of comparing modes across several data groups. The study data was collected by distributing mode-related questions to students through a Google Form, followed by interviews. Four mode-related questions were given to 43 undergraduate students participating in the study. The results showed that routine plays a significant role in statistical reasoning. The study identified two factors that contributed to the occurrence of inconsistent routines among students: (a) the way students described the data display and (b) the disconnection between routine and endorsed narrative. The results of this research highlight the importance of providing students with opportunities to work with diverse forms and conditions of data associated with mode.