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Updated: Dec 29, 2025

Using Learning Outcome Measures to assess Doctoral Nursing Education
Published on: June 21, 2010
Micro-feedback skills workshop impacts perceptions and practices of doctoral faculty
Najma Baseer1, James Degnan2, Mandy Moffat3
1Institute of Basic Medical Sciences (IBMS), Khyber Medical University, Peshawar, Khyber Pakhtunkhwa, Pakistan.
Doctoral supervisors trained in micro-feedback workshops showed improved feedback skills and aligned perceptions with their supervisees. This faculty development enhances the supervisory relationship and learning outcomes in doctoral education.
Area of Science:
- Medical Education
- Supervisory Training
- Health Sciences
Background:
- Doctoral supervision requires effective feedback delivery for supervisee improvement.
- Health sciences supervisors often lack formal training, leading to trial-and-error feedback practices.
- Microteaching offers a standardized approach to developing essential supervisory feedback skills.
Purpose of the Study:
- To develop doctoral supervisors' feedback skills using a micro-feedback workshop.
- To assess the effectiveness of the micro-feedback training using the Kirkpatrick evaluation framework.
- To evaluate changes in supervisor and supervisee perceptions of feedback.
Main Methods:
- Quasi-experimental, repeated measures, pre-post test design with separate samples.
- A micro-feedback skills workshop utilizing microteaching techniques.
- Kirkpatrick levels 1 and 2 evaluation, including Objective Structured Teaching Exercises (OSTE) and questionnaires.
Main Results:
- High supervisor satisfaction and willingness (71%) for faculty development.
- Significant learning gain (56%) observed in OSTE scores post-workshop.
- Post-workshop, perceptions of feedback delivery became congruent between supervisors and supervisees.
Conclusions:
- Structured micro-feedback workshops effectively enhance doctoral supervisors' feedback skills.
- Training aligns supervisor and supervisee perceptions of feedback, improving the supervisory relationship.
- This approach offers a scalable solution for improving doctoral education quality.
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