A Qualitative Textual Analysis of Feedback Comments in ePortfolios: Quality and Alignment with the CanMEDS Roles.

Introduction: Competency-based education requires high-quality feedback to guide students' acquisition of competencies. Sound assessment and feedback systems, such as ePortfolios, are needed to facilitate seeking and giving feedback during clinical placements. However, it is unclear whether the written feedback comments in ePortfolios are of high quality and aligned with the current competency focus.

Automating the Identification of Feedback Quality Criteria and the CanMEDS Roles in Written Feedback Comments Using Natural Language Processing.

Introduction: Manually analysing the quality of large amounts of written feedback comments is time-consuming and demands extensive resources and human effort. Therefore, this study aimed to explore whether a state-of-the-art large language model (LLM) could be fine-tuned to identify the presence of four literature-derived feedback quality criteria ( and ) and the seven CanMEDS roles ( and ) in written feedback comments.

Methods: A set of 2,349 labelled feedback comments of five healthcare educational programs in Flanders (Belgium) (specialistic medicine, general practice, midwifery, speech therapy and occupational therapy) was split into 12,452 sentences to create two datasets for the machine learning analysis.

Training to Support ePortfolio Users During Clinical Placements: a Scoping Review.

Unlabelled: ePortfolios are frequently used to support students' competency development, and teachers' and clinical mentors' supervision during clinical placements. User training is considered a critical success factor for the implementation of these ePortfolios. However, there is ambiguity about the design and outcomes of ePortfolio user training.