1,703
Views
0
CrossRef citations to date
0
Altmetric
Articles

Digital flesh: a feminist approach to the body in cyberspace

ORCID Icon
Pages 578-593 | Received 13 Jul 2019, Accepted 13 Jul 2020, Published online: 02 Aug 2020
 

ABSTRACT

Despite the rapid growth of digital learning, the relationship between the body and new information technologies has been underexamined in education research literature. This study presents a feminist conceptual framework in order to situate the body as an issue central to the academic discussion of online education. This paper extends feminist technoscience scholars’ notion of co-constructing gender-technology by critiquing the disembodied approach to emerging education technologies. By integrating the philosophical approaches to the body of Butler and several phenomenologists, the author suggests alternative ways of understanding online learning environments based on a literature review. This new feminist phenomenological concept, digital flesh, prompts a greater awareness of the gendered materiality of cyberspace that challenges the dominant discourse of learning technology, as evidenced by recent artificial intelligence experiments.

Disclosure statement

No potential conflict of interest was reported by the author.

Additional information

Notes on contributors

Hyungjoo Yoon

Hyungjoo Yoon is a doctoral candidate at the University of Georgia. His research interests include online education, feminist and critical theories, and social network analysis. He is currently pursuing two graduate certificates in Women's Studies and in Interdisciplinary Qualitative Studies at UGA.

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 712.00 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.