StatTree: Progressing a Mobile Application to Support Statistical Decision Making

Peter ALLEN
Curtin University, Australia
p.allen@curtin.edu.au

Lynne ROBERTS
Curtin University, Australia
lynne.roberts@curtin.edu.au

Abstract

Quantitative research methods play a critical role in the development of professional competence across the health, behavioural and social sciences. Despite this, they are an area of weakness for many students. Students are known to particularly struggle when required to select appropriate statistical tests and procedures for different types of data, research questions and hypotheses. Furthermore, research suggests that this is a skill not often practiced in class. Decision trees (or graphic organisers) are known to support such statistical decision making, but extant trees carry a range of limitations that constrain their efficacy. Recent developments in mobile learning technologies offer the potential for many of these limitations to be overcome. In this poster presentation we will report on the theoretical and empirical rationale behind, and our progress towards "StatTree", an Australian Government Office for Learning and Teaching funded project to develop a cross-platform mobile application designed to support students' statistical decision making. The application guides users through a series of simple, annotated questions to ultimately offer them the guidance necessary to conduct, interpret and report a statistical test or procedure suitable for their circumstances. We will also use the poster presentation as an opportunity to invite delegates to offer critical feedback on our work to date, and/or participate in pilot testing of the application and its supporting resources, either independently, or within a classroom context.

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