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Does a deep learning inventory predict knowledge transfer? Linking student perceptions to transfer outcomes.

Andrew B LoGiudice1,2, Geoffrey R Norman3,4, Saba Manzoor3

  • 1Department of Evaluative Clinical Sciences, Sunnybrook Research Institute, Sunnybrook Health Sciences Centre, 2075 Bayview Ave, Toronto, ON, M4N 3M5, Canada. andrew.logiudice@sri.utoronto.ca.

Advances in Health Sciences Education : Theory and Practice
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PubMed
Summary
This summary is machine-generated.

Deep learning inventories, like the Revised Two-Factor Study Process Questionnaire, may not accurately predict students' knowledge transfer abilities. This study found these tools have questionable validity for assessing deep learning outcomes in health sciences education.

Keywords:
Deep learningInstructional designKnowledge transferLearning approachesQuestionnaireStudy process

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Area of Science:

  • Medical Education
  • Educational Psychology

Background:

  • Students are encouraged towards deep learning, focusing on general principles over memorization.
  • Deep learning is frequently assessed using Likert-style inventories.
  • The predictive validity of these inventories is debated due to limited evidence and unclear outcome measures.

Purpose of the Study:

  • To test the predictive validity of the Revised Two-Factor Study Process Questionnaire.
  • To examine the relationship between deep learning inventory scores and knowledge transfer in undergraduate health sciences students.

Main Methods:

  • Administered the Revised Two-Factor Study Process Questionnaire to health sciences students.
  • Assessed student perceptions of final exam items related to knowledge transfer demands (application, integration, novelty).
  • Analyzed exam performance on items identified as requiring knowledge transfer.

Main Results:

  • The deep learning inventory demonstrated good reliability.
  • Inventory scores did not substantially predict knowledge transfer outcomes.
  • Findings question the validity of the inventory for assessing deep learning.

Conclusions:

  • The Revised Two-Factor Study Process Questionnaire and similar tools may not be valid predictors of knowledge transfer.
  • Further research is needed to develop and validate tools for assessing deep learning and knowledge transfer in medical education.