Learning analytics, education data mining, and personalization in health professions education

Janet Corral, Stathis Th Konstantinidis, Panagiotis D. Bamidis

Research output: Chapter in Book/Report/Conference proceedingChapter

4 Scopus citations

Abstract

Personalization of student evaluation data and learning application usage has the potential to provide targeted feedback to support self-directed learning and expertise development among learners in health professions education. To provide personalization, health professions programs need to leverage both: (1) the technical infrastructure and analysis for existing student data, and (2) understand the interrelated contexts of learning, teaching, and expertise development within the clinical context. Personalization is more than feeding back results to learners; it also moves into intelligent tutors. Tips for successful adoption of personalization in health professions education, including security, legal, and administrative concerns, are discussed.

Original languageEnglish (US)
Title of host publicationDigital Innovations in Healthcare Education and Training
PublisherElsevier
Pages137-150
Number of pages14
ISBN (Electronic)9780128131442
ISBN (Print)9780128131459
DOIs
StatePublished - Jan 1 2020

Keywords

  • education data mining
  • health professions education
  • learning analytics
  • personalization

ASJC Scopus subject areas

  • General Medicine

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