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Open-source Tools for Training Resources - OTTR.

Candace Savonen1,2, Carrie Wright1,2, Ava M Hoffman1,2

  • 1Johns Hopkins Bloomberg School of Public Health, Baltimore, MD.

Journal of Statistics and Data Science Education : an Official Journal of the of the American Statistical Association
|May 19, 2023
PubMed
Summary
This summary is machine-generated.

Open-source Tools for Training Resources (OTTR) streamlines the creation and maintenance of data science training materials. This system reduces workload and enhances flexibility for educational content delivery.

Keywords:
data scienceeducationinformaticsopen-sourcetools

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Area of Science:

  • Data Science and Informatics
  • Educational Technology

Background:

  • Rapid advancement of data science tools outpaces user training and resource availability.
  • Existing training materials often become outdated due to insufficient maintenance prioritization and funding.
  • Lack of accessible, up-to-date resources hinders efficient application of data science methods in research.

Purpose of the Study:

  • To introduce Open-source Tools for Training Resources (OTTR) as a solution for creating and maintaining data science training materials.
  • To enhance the efficiency, flexibility, and longevity of educational content for data science and informatics.
  • To provide a platform that simplifies the publication of training resources across multiple online learning communities.

Main Methods:

  • Development of the OTTR framework, a system designed for flexible content creation and maintenance.
  • Implementation of a simplified workflow for publishing training materials to various platforms.
  • Integration of pedagogical features, including automatically graded formative and summative assessments (multiple choice, fill-in-the-blank).
  • No local software installation required for content creators.

Main Results:

  • Successfully created 15 training courses using the OTTR repository template.
  • Demonstrated a significant reduction in the workload required for updating training courses across multiple platforms.
  • Validated the system's ability to support diverse pedagogical approaches and publishing needs.

Conclusions:

  • OTTR provides an efficient and flexible solution for developing and maintaining up-to-date data science training resources.
  • The system empowers educators to create customized, engaging learning experiences with reduced maintenance overhead.
  • OTTR facilitates the dissemination of crucial data science skills through accessible online learning communities.