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Diagnosing Statistical Education Needs of Health Science Learners

  • Amy S. Nowacki
  • , Ann M. Brearley
  • , Robert A. Oster
  • , Emily Slade
  • , Katrina L. Devick
  • , Matthew J. Hayat
  • , Sally W. Thurston

Research output: Contribution to journalArticlepeer-review

Abstract

Many types of health science learners, including clinical and translational scientists, students, researchers, and clinicians, seek to increase their knowledge of biostatistics. These learners are heterogeneous in their field, career stage and career focus. Based on the collective experience of an expert panel with over 115 years teaching statistics to health science learners, we propose a framework for considering the needs of health science learners motivated by their career goals. This framework defines four types of health science learners seeking statistical training: (a) consumers, (b) “milestone makers”, (c) biomedical researchers with statistical support, and (d) biomedical researchers without statistical support. Each type of learner has different levels at which they need to understand statistical topics for their careers, such as when to use a particular statistical method or why a given method works; these differing levels of understanding are detailed in our proposed framework. Further, this framework identifies the expectations that each of these types of learners should have for gaining statistical knowledge in a single seminar, multiple seminars, a seminar series, an accredited course, or a certificate/degree program. Advantages and disadvantages of widely used educational formats for these learners are also described. From this work, health science learners seeking biostatistical training or those who are planning a training program for others can gain insight into identifying appropriate statistical training goals for the type of learner with which they identify. Statistical educators may also use these guidelines to help health science learners align expectations for various types of training.

Original languageEnglish (US)
Pages (from-to)199-209
Number of pages11
JournalJournal of Statistics and Data Science Education
Volume33
Issue number2
DOIs
StatePublished - 2025

Bibliographical note

Publisher Copyright:
© 2024 The Author(s). Published with license by Taylor & Francis Group, LLC.

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

  1. SDG 4 - Quality Education
    SDG 4 Quality Education

Keywords

  • Biostatistics
  • Health science learner
  • Research training
  • Statistical competency

PubMed: MeSH publication types

  • Journal Article

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