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Bridging Over Troubled Waters: Educa...
~
Oyewole, Kemi Anike,
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Bridging Over Troubled Waters: Educator Resource Sharing in Professional Learning Networks /
紀錄類型:
書目-電子資源 : Monograph/item
正題名/作者:
Bridging Over Troubled Waters: Educator Resource Sharing in Professional Learning Networks // Kemi Anike Oyewole.
作者:
Oyewole, Kemi Anike,
面頁冊數:
1 electronic resource (229 pages)
附註:
Source: Dissertations Abstracts International, Volume: 86-05, Section: A.
Contained By:
Dissertations Abstracts International86-05A.
標題:
Social network analysis. -
電子資源:
https://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=31643284
ISBN:
9798346389910
Bridging Over Troubled Waters: Educator Resource Sharing in Professional Learning Networks /
Oyewole, Kemi Anike,
Bridging Over Troubled Waters: Educator Resource Sharing in Professional Learning Networks /
Kemi Anike Oyewole. - 1 electronic resource (229 pages)
Source: Dissertations Abstracts International, Volume: 86-05, Section: A.
Collaboration is increasingly used to support learning in complex educational environments. Professional learning networks are a collaborative approach that builds human capital by connecting professionals working in different contexts to address similar needs. In my three-paper dissertation, I take a conceptual and empirical approach to increasing our understanding of professional learning networks. In my first paper, I sharpen our characterization of professional learning networks by contrasting them with two other collaborative learning approaches: professional learning communities and networked improvement communities. I differentiate these approaches' histories, sociological bases, and use. I show that distinguishing these approaches' goals is necessary to maximize collaborative outcomes with scarce time. Further, the limits of each approach suggest how they can be combined in service of educational justice. In my second and third dissertation papers, I use four waves of survey data and 29 coach interviews to characterize a 45-member instructional coach professional learning network. I employ exponential random graph models and a SIENA model for cross-sectional and longitudinal social network analysis. My inferential models show that coaches share advice with peers who have similar professional needs. These trusting connections grow increasingly close over time. However, coaches are less engaged after many years in the network or when the network meets online. I also make a methodological contribution by introducing member checking in social networks research, inviting practitioners to use their insights to direct network analysis. My dissertation illustrates the potential-and challenges-of professional learning networks bridging across contexts so educators can access the resources that help them navigate the troubled waters of contemporary schools.
English
ISBN: 9798346389910Subjects--Topical Terms:
3564656
Social network analysis.
Bridging Over Troubled Waters: Educator Resource Sharing in Professional Learning Networks /
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Collaboration is increasingly used to support learning in complex educational environments. Professional learning networks are a collaborative approach that builds human capital by connecting professionals working in different contexts to address similar needs. In my three-paper dissertation, I take a conceptual and empirical approach to increasing our understanding of professional learning networks. In my first paper, I sharpen our characterization of professional learning networks by contrasting them with two other collaborative learning approaches: professional learning communities and networked improvement communities. I differentiate these approaches' histories, sociological bases, and use. I show that distinguishing these approaches' goals is necessary to maximize collaborative outcomes with scarce time. Further, the limits of each approach suggest how they can be combined in service of educational justice. In my second and third dissertation papers, I use four waves of survey data and 29 coach interviews to characterize a 45-member instructional coach professional learning network. I employ exponential random graph models and a SIENA model for cross-sectional and longitudinal social network analysis. My inferential models show that coaches share advice with peers who have similar professional needs. These trusting connections grow increasingly close over time. However, coaches are less engaged after many years in the network or when the network meets online. I also make a methodological contribution by introducing member checking in social networks research, inviting practitioners to use their insights to direct network analysis. My dissertation illustrates the potential-and challenges-of professional learning networks bridging across contexts so educators can access the resources that help them navigate the troubled waters of contemporary schools.
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