Introducing StatHand: A cross-platform mobile application to support students’ statistical decision making

Peter Allen, Lynne D Roberts, Frank D Baughman, Natalie J Loxton, Dirk van Rooy, Adam J Rock, James Finlay

Research output: Contribution to journalArticle (Academic Journal)peer-review

3 Citations (Scopus)
296 Downloads (Pure)

Abstract

Although essential to professional competence in psychology, quantitative research methods are a known area of weakness for many undergraduate psychology students. Students find selecting appropriate statistical tests and procedures for different types of research questions, hypotheses and data types particularly challenging, and these skills are not often practiced in class. Decision trees (a type of graphic organizer) are known to facilitate this decision making process, but extant trees have a number of limitations. Furthermore, emerging research suggests that mobile technologies offer many possibilities for facilitating learning. It is within this context that we have developed StatHand, a free cross-platform application designed to support students’ statistical decision making. Developed with the support of the Australian Government Office for Learning and Teaching, StatHand guides users through a series of simple, annotated questions to help them identify a statistical test or procedure appropriate to their circumstances. It further offers the guidance necessary to run these tests and procedures, then interpret and report their results. In this Technology Report we will overview the rationale behind StatHand, before describing the feature set of the application. We will then provide guidelines for integrating StatHand into the research methods curriculum, before concluding by outlining our road map for the ongoing development and evaluation of StatHand.
Original languageEnglish
Article number288
Number of pages10
JournalFrontiers in Psychology
Volume7
DOIs
Publication statusPublished - 29 Feb 2016

Keywords

  • statistics
  • research methods
  • selection skills
  • decision tree
  • teaching and learning
  • mobile learning
  • iOS
  • web application

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