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Learning relationships in community-based service-learning: a social network analysis
BACKGROUND: Little is known about the social learning of students within community-based clinical placements and ways in which it can be supported. In an allied health service-learning program, we analysed students’ learning relationships to quantify what, and from whom students learnt. METHODS: We...
Autores principales: | , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2019
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6482529/ https://www.ncbi.nlm.nih.gov/pubmed/31023298 http://dx.doi.org/10.1186/s12909-019-1522-1 |
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author | Held, Fabian P. Roberts, Chris Daly, Michele Brunero, Claire |
author_facet | Held, Fabian P. Roberts, Chris Daly, Michele Brunero, Claire |
author_sort | Held, Fabian P. |
collection | PubMed |
description | BACKGROUND: Little is known about the social learning of students within community-based clinical placements and ways in which it can be supported. In an allied health service-learning program, we analysed students’ learning relationships to quantify what, and from whom students learnt. METHODS: We conducted a social learning network survey in four domains of learning (clinical knowledge, procedural skills, professional development, and complex determinants of health) to explore learning relationships (ties) with other people (alters) that students (egos) formed during their placement. We quantified how different roles (supervisors, health professionals, administrators, peers, schoolteachers, and clients) contributed to the students’ learning in each of the four domains. We used exponential random graph models (ERGMs) to test which relational processes contributed to the structure of the observed learning networks. RESULTS: Data was available from a complete cohort of 10 students on placement in a network of 69 members, thus providing information on 680 potential learning relations. Students engaged in similar ways in the domains of clinical knowledge, procedural skills, and professional development. Learning relations with academic supervisors were significantly more likely. Also students reported reciprocal learning relations with peers – i.e. they formed learning pairs. This effect was absent in learning networks about complex determinants of health (including socio-economic and cultural factors). Instead, local administrative staff were significantly more often the source of learning about the local contextual factors. CONCLUSIONS: Understanding the structure of student learning networks through social network analysis helps identify targeted strategies to enhance learning in community-based service-learning programs. Our findings suggest students recognised important learning from each other and from administrative personnel that is unrelated to the content of their placement. Based on this insight clinical educators could prepare students to become agentic learners, learning with each other and from sources outside their program. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (10.1186/s12909-019-1522-1) contains supplementary material, which is available to authorized users. |
format | Online Article Text |
id | pubmed-6482529 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2019 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-64825292019-05-02 Learning relationships in community-based service-learning: a social network analysis Held, Fabian P. Roberts, Chris Daly, Michele Brunero, Claire BMC Med Educ Research Article BACKGROUND: Little is known about the social learning of students within community-based clinical placements and ways in which it can be supported. In an allied health service-learning program, we analysed students’ learning relationships to quantify what, and from whom students learnt. METHODS: We conducted a social learning network survey in four domains of learning (clinical knowledge, procedural skills, professional development, and complex determinants of health) to explore learning relationships (ties) with other people (alters) that students (egos) formed during their placement. We quantified how different roles (supervisors, health professionals, administrators, peers, schoolteachers, and clients) contributed to the students’ learning in each of the four domains. We used exponential random graph models (ERGMs) to test which relational processes contributed to the structure of the observed learning networks. RESULTS: Data was available from a complete cohort of 10 students on placement in a network of 69 members, thus providing information on 680 potential learning relations. Students engaged in similar ways in the domains of clinical knowledge, procedural skills, and professional development. Learning relations with academic supervisors were significantly more likely. Also students reported reciprocal learning relations with peers – i.e. they formed learning pairs. This effect was absent in learning networks about complex determinants of health (including socio-economic and cultural factors). Instead, local administrative staff were significantly more often the source of learning about the local contextual factors. CONCLUSIONS: Understanding the structure of student learning networks through social network analysis helps identify targeted strategies to enhance learning in community-based service-learning programs. Our findings suggest students recognised important learning from each other and from administrative personnel that is unrelated to the content of their placement. Based on this insight clinical educators could prepare students to become agentic learners, learning with each other and from sources outside their program. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (10.1186/s12909-019-1522-1) contains supplementary material, which is available to authorized users. BioMed Central 2019-04-25 /pmc/articles/PMC6482529/ /pubmed/31023298 http://dx.doi.org/10.1186/s12909-019-1522-1 Text en © The Author(s). 2019 Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated. |
spellingShingle | Research Article Held, Fabian P. Roberts, Chris Daly, Michele Brunero, Claire Learning relationships in community-based service-learning: a social network analysis |
title | Learning relationships in community-based service-learning: a social network analysis |
title_full | Learning relationships in community-based service-learning: a social network analysis |
title_fullStr | Learning relationships in community-based service-learning: a social network analysis |
title_full_unstemmed | Learning relationships in community-based service-learning: a social network analysis |
title_short | Learning relationships in community-based service-learning: a social network analysis |
title_sort | learning relationships in community-based service-learning: a social network analysis |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6482529/ https://www.ncbi.nlm.nih.gov/pubmed/31023298 http://dx.doi.org/10.1186/s12909-019-1522-1 |
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