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Pedagogy of teaching with large datasets: Designing and implementing effective data-based activities

Research output: Contribution to journalArticlepeer-review

Abstract

Integrating the use of large datasets into our teaching provides critical and unique opportunities to build students' skills and conceptual knowledge. Here, we discuss the core components needed to develop effective activities based on large datasets, which align with the 5E learning cycle. Data-based activities should be structured around a relevant question, use authentic publicly accessible data, be scaffolded to include choice, and involve discussion of the results. It is important that the software that is used to manipulate, analyze and/or visualize the data is accessible for students. There are a range of strategies to reduce the barriers of working with large datasets through pre-organizing and pre-scripting code for analyses, using online cloud-based versions of software, and reducing opportunities for error in syntax. Resources exist for learning open-source software (e.g., Data Carpentry) as well as for support and professional development in teaching with large datasets (Project EDDIE).

Original languageEnglish (US)
Pages (from-to)466-472
Number of pages7
JournalBiochemistry and Molecular Biology Education
Volume50
Issue number5
DOIs
StatePublished - Sep 1 2022
Externally publishedYes

Bibliographical note

Publisher Copyright:
© 2022 The Authors. Biochemistry and Molecular Biology Education published by Wiley Periodicals LLC on behalf of International Union of Biochemistry and Molecular Biology.

UN SDGs

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

  1. SDG 4 - Quality Education
    SDG 4 Quality Education

Keywords

  • RStudio
  • big data
  • professional development

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