6,728
Views
29
CrossRef citations to date
0
Altmetric
Articles

Gender stereotypes: the impact upon perceived roles and practice of in-service teachers in physical education

ORCID Icon & ORCID Icon
Pages 259-271 | Received 19 May 2020, Accepted 04 Nov 2020, Published online: 20 Nov 2020
 

ABSTRACT

This study aimed to explore gender stereotypes and their impact upon perceived roles and practice of in-service physical education teachers. Twenty-one qualified PE teachers completed an online story completion method and results were analysed using reflexive thematic analysis. Comparisons were generated between the two-story stems: between male and female participants and between the hypothetical stories and direct question answers. Results showed that teachers’ perceptions largely conformed to typical gender stereotypes, including stereotypical views on gender roles, gendered sports and story character assumptions. Participants did not attribute stereotype reproduction to themselves as teachers and negative external pressures arose as a common reasoning for stereotypical practice. However, only female participants highlighted parents and peers as significant contributors, whereas both genders highlighted governmental pressures such as curriculum design. This study displayed that gender segregation, masculine and feminine discourses and gendered habitus are still prominent within PE.

Disclosure statement

No potential conflict of interest was reported by the author(s).

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 398.00 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.