Federated Education Platform: Harmonizing Competencies

This group has been sunsetted As of December 31, 2019

Objective: To assist those working with training programs to identify relevant core competencies and intensity of training for specific research roles.

Question:  How are training programs using existing CTSA core competencies to create a “personalized pathway” for trainees across the translational spectrum?

  • Currently 97 competencies across 14 Core Thematic Areas listed
  • Additional 9 sets of role-based competencies
  • Trainees with different levels of prior preparation and unique career goals

Goal: To assist those working with training programs to identify relevant core competencies and level of mastery recommended for specific research roles (“phenotypes”).

  • Increase efficiency of training (“overtraining” or “undertraining”)
  • Manage learner/mentor expectations
  • Assist with preparation of Individual Development Plans


  • A cross-sectional REDCap survey requested input from CTSA educators on what level of training mastery is recommended in each of the 97 competencies based on an individual’s desired career phenotype
  • Survey distributed to members of Workforce DTF and Methods/Processes DTF – Snowball sampling to reach individuals who advise trainees
  • Focused on KL2 Scholars

Moving Forward:

  • Manuscript submission
  • Upload data for all phenotypes to CLIC workspace
  • Consider different workforce/team roles
  • Explore whether information is useful for: – development of the IDP; – identifying gaps in hub programs

Rebecca Jackson, Ohio State University Medical Center
Susan Pusek, University of North Carolina at Chapel Hill
David Ingbar, University of Minnesota

Related Group
Workforce Development Enterprise Committee
2nd Wed., Bi-Monthly, 4-5 pm ET


Using Google drive to collaborate.

Publications, Reports & Posters

  • Data for all Phenotypes
  • Personalized Training Pathways for Translational Science Trainees: Building On a Framework of Knowledge, Skills and Abilities across the Translational Science Spectrum