3,431
Views
152
CrossRef citations to date
0
Altmetric
Articles

Developmental networks and learning: toward an interdisciplinary perspective on identity development during doctoral study

&
Pages 807-827 | Published online: 15 Sep 2010
 

Abstract

The authors draw on two families of theories – developmental networks and sociocultural perspectives on learning – to develop an interdisciplinary approach to the study of doctoral education as a path to the professoriate. This approach seeks to elucidate the connection between doctoral students’ developmental networks, what they learn during their graduate experience (including their learning about the faculty role) and how they develop a professional identity. The authors first discuss the key tenets of the developmental networks and sociocultural perspectives, before exploring their alignments and explaining how the combination might remedy the limitations inherent in each approach. Finally, they offer some research propositions and directions for further study of the preparation of doctoral students for academic careers.

Acknowledgements

We want to gratefully acknowledge the advice received from Chris Golde and two anonymous reviewers during the writing of this manuscript. A previous version of this article was presented at the Association for the Study of Higher Education annual conference in Jacksonville, FL in November 2008. This research was supported by a grant from the Hewlett‐Mellon Fund for Faculty Development at Albion College in Albion, Michigan.

Log in via your institution

Log in to Taylor & Francis Online

PDF download + Online access

  • 48 hours access to article PDF & online version
  • Article PDF can be downloaded
  • Article PDF can be printed
USD 53.00 Add to cart

Issue Purchase

  • 30 days online access to complete issue
  • Article PDFs can be downloaded
  • Article PDFs can be printed
USD 678.00 Add to cart

* Local tax will be added as applicable

Related Research

People also read lists articles that other readers of this article have read.

Recommended articles lists articles that we recommend and is powered by our AI driven recommendation engine.

Cited by lists all citing articles based on Crossref citations.
Articles with the Crossref icon will open in a new tab.