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Conference Paper: A preference for deep over surface learning favors a more positive multi-source feedback assessment in clinical practicum
Title | A preference for deep over surface learning favors a more positive multi-source feedback assessment in clinical practicum |
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Authors | |
Issue Date | 2018 |
Publisher | Bau Institute of Medical and Health Sciences Education, Li Ka Shing Faculty of Medicine, The University of Hong Kong. |
Citation | Frontiers in Medical and Health Sciences Education 2018 Conference: Learning in Alliance: Inter-professional Health Education and Practice, Hong Kong, 18-19 December 2018 How to Cite? |
Abstract | Introduction: Multi-source feedback (MSF) has become an increasingly established tool to assess professionalism in medical settings. Educational research showed that a good learning environment and a preference for deep over surface learning approach are positively related to learning outcomes in traditional classroom settings. However, much less is known as to whether learning environment and students’ learning approaches also relate to performance in the clinical practicum as assessed by MSF. Thus, the present study examined the relationships between learning environment, learning approaches,
and MSF-assessed performance in medical education.
Method: A group of 198 Year 3 undergraduate students undertaking a nursing practicum course participated in the study. They completed a set of questionnaires which measured their perception of learning environment and their approaches to learning. Practicum performance was measured by MSF, a
questionnaire on students’ clinical practicum completed by the students themselves, two of their peers, and their clinical teachers. Statistical analyses were performed to examine features of the measured variables and their inter-relationships.
Findings: Each of the scales selected for analysis exhibited high internal consistency and one-factor structure. Findings suggested that a positively perceived learning environment was positively related to the use of deep learning approach and negatively related to surface learning approach. The use of deep learning approach was also related to better self- and peer-assessed performance, whereas surface learning approach was negatively related to teacher-assessed performance.
Conclusion: Findings implied that a positively perceived learning environment encouraged the use of deep over surface learning approach in the clinical practicum, and that a preference for deep over surface learning approach also favored a more positive evaluation of performance by self, peers, and clinical teachers. Implications for enhancing clinical practices as evaluated by MSF amongst medical
students are discussed. |
Description | Free Paper Presentation – Oral Presentation - Session D – Assessment and Quality Assurance - no. OPD26 |
Persistent Identifier | http://hdl.handle.net/10722/272105 |
DC Field | Value | Language |
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dc.contributor.author | Leung, HT | - |
dc.contributor.author | Zhao, Y | - |
dc.date.accessioned | 2019-07-20T10:35:47Z | - |
dc.date.available | 2019-07-20T10:35:47Z | - |
dc.date.issued | 2018 | - |
dc.identifier.citation | Frontiers in Medical and Health Sciences Education 2018 Conference: Learning in Alliance: Inter-professional Health Education and Practice, Hong Kong, 18-19 December 2018 | - |
dc.identifier.uri | http://hdl.handle.net/10722/272105 | - |
dc.description | Free Paper Presentation – Oral Presentation - Session D – Assessment and Quality Assurance - no. OPD26 | - |
dc.description.abstract | Introduction: Multi-source feedback (MSF) has become an increasingly established tool to assess professionalism in medical settings. Educational research showed that a good learning environment and a preference for deep over surface learning approach are positively related to learning outcomes in traditional classroom settings. However, much less is known as to whether learning environment and students’ learning approaches also relate to performance in the clinical practicum as assessed by MSF. Thus, the present study examined the relationships between learning environment, learning approaches, and MSF-assessed performance in medical education. Method: A group of 198 Year 3 undergraduate students undertaking a nursing practicum course participated in the study. They completed a set of questionnaires which measured their perception of learning environment and their approaches to learning. Practicum performance was measured by MSF, a questionnaire on students’ clinical practicum completed by the students themselves, two of their peers, and their clinical teachers. Statistical analyses were performed to examine features of the measured variables and their inter-relationships. Findings: Each of the scales selected for analysis exhibited high internal consistency and one-factor structure. Findings suggested that a positively perceived learning environment was positively related to the use of deep learning approach and negatively related to surface learning approach. The use of deep learning approach was also related to better self- and peer-assessed performance, whereas surface learning approach was negatively related to teacher-assessed performance. Conclusion: Findings implied that a positively perceived learning environment encouraged the use of deep over surface learning approach in the clinical practicum, and that a preference for deep over surface learning approach also favored a more positive evaluation of performance by self, peers, and clinical teachers. Implications for enhancing clinical practices as evaluated by MSF amongst medical students are discussed. | - |
dc.language | eng | - |
dc.publisher | Bau Institute of Medical and Health Sciences Education, Li Ka Shing Faculty of Medicine, The University of Hong Kong. | - |
dc.relation.ispartof | Frontiers in Medical and Health Sciences Education 2018 Conference | - |
dc.title | A preference for deep over surface learning favors a more positive multi-source feedback assessment in clinical practicum | - |
dc.type | Conference_Paper | - |
dc.identifier.email | Leung, HT: leung83@hku.hk | - |
dc.identifier.email | Zhao, Y: myzhao@hku.hk | - |
dc.identifier.authority | Zhao, Y=rp02230 | - |
dc.identifier.hkuros | 298792 | - |
dc.publisher.place | Hong Kong | - |