Barbara McKenzie
Exploring a problem-based learning approach in pharmaceutics.
McKenzie, Barbara; Brown, Alyson
Authors
Alyson Brown
Abstract
Objective. The basis of this study was to explore the impact of the initiation of a Problem-Base Learning (PBL) approach within a second-year pharmaceutics degree on a Master of Pharmacy programme, introduced as a way of improving deep learning and to foster independent learning. Design. A semi-structured interview was used to seek feedback from the students, and feedback from staff was secured though a focus group. A thematic approach was used for the analysis, once data saturation had been reached. Exam pass-rate statistics were also analysed. Assessment. Five parent themes were identified from the student interviews: Module structure, Promoting lifelong learning, Integration and future practice, Outcomes and Student experience. The third year exam pass rate improved by 12% in the year following the introduction of PBL in second year. Conclusions. Various recommendations were proposed to further improve the module, based on the findings of this study. These include improving feedback and support through tutorials, reducing the volume of directed study, as well as highlighting the relevance of pharmaceutics to the pharmacy degree. A long-term review would be needed to assess the full implications of PBL teaching within this course.
Citation
MCKENZIE, B. and BROWN, A. 2017. Exploring a problem-based learning approach in pharmaceutics. Pharmacy [online], 5(3), article number 53. Available from: https://doi.org/10.3390/pharmacy5030053
Journal Article Type | Article |
---|---|
Acceptance Date | Sep 13, 2017 |
Online Publication Date | Sep 20, 2017 |
Publication Date | Sep 30, 2017 |
Deposit Date | Oct 31, 2017 |
Publicly Available Date | Oct 31, 2017 |
Journal | Pharmacy |
Electronic ISSN | 2226-4787 |
Publisher | MDPI |
Peer Reviewed | Peer Reviewed |
Volume | 5 |
Issue | 3 |
Article Number | 53 |
DOI | https://doi.org/10.3390/pharmacy5030053 |
Keywords | Problem based learning; Deep learning; Pharmacy; Pharmaceutics |
Public URL | http://hdl.handle.net/10059/2563 |
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Publisher Licence URL
https://creativecommons.org/licenses/by/4.0/
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