JOURNAL ARTICLE

Unveiling Gender: The Teacher's Role in Shaping Gender Identities through Hidden Curriculum and Pedagogy.

  • Published In: African Journal of Gender, Society & Development, 2025, v. 14, n. 4. P. 31 1 of 3

  • Database: Sociology Source Ultimate 2 of 3

  • Authored By: Wadesango, Newman 3 of 3

Abstract

This article examines the pivotal role teachers play in shaping gender identities within educational settings through the hidden curriculum—unwritten, implicit lessons conveyed via classroom interactions, teacher attitudes, and institutional practices. It highlights how teachers, often unconsciously, reinforce traditional gender norms by differentially encouraging behaviors and academic interests aligned with societal stereotypes, thereby influencing students' self-perceptions and future aspirations. Employing a qualitative desktop study grounded in Gender Schema Theory, the article synthesizes global policy frameworks such as the Convention on the Elimination of All Forms of Discrimination Against Women (CEDAW) and Sustainable Development Goals (SDG 4 and SDG 5), emphasizing the need for gender-responsive pedagogy and ongoing professional development. The study advocates for inclusive teaching strategies that critically address implicit biases and promote equity, urging educational policies to support reflective practices that enable teachers to challenge and transform entrenched gender norms in classrooms.

Additional Information

  • Source:African Journal of Gender, Society & Development. 2025/12, Vol. 14, Issue 4, p31
  • Document Type:Article
  • Subject Area:Education
  • Publication Date:2025
  • ISSN:2634-3614
  • DOI:10.31920/2634-3622/2025/v14n4a2
  • Accession Number:192190497
  • Copyright Statement:Copyright of African Journal of Gender, Society & Development is the property of Adonis & Abbey Publishers Ltd. and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

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