Journal article : Review
Barriers to AI adoption for women in higher education: a systematic review of the Asian context
- Abstract:
- Artificial Intelligence (AI) is transforming higher education rapidly by enabling personalized learning, enhancing administrative processes, and improving access to educational resources. However, disparities in AI adoption, particularly among women in the Asian context, raise concerns about equity, inclusivity, and access. This disparity could lead to a deficit in AI skills among women, affecting their ability to contribute as effectively as men in the future. Therefore, it is necessary to understand the current state of women's adoption of AI and the barriers they face in Asian higher education. The systematic review has been conducted using PRISMA guidelines. This review paper synthesizes the findings from the studies conducted in various contexts of Asia to present an overall picture of the state of AI adoption among women in Asia. A total of 17 studies were selected for this review, highlighting socio-cultural barriers, lack of trust, technological unawareness, biases in AI algorithms, and inadequate representation of women in AI policy formulation. Besides highlighting these barriers, the results also shed light on recommendations given by earlier studies that facilitate and encourage women to adopt AI in higher education. Based on the Asian perspective, the conclusion proposes specific recommendations for policymakers and practitioners to promote inclusive AI that empowers women in Asia to contribute more effectively to higher education.
- Publication status:
- Published
- Peer review status:
- Peer reviewed
Actions
Access Document
- Files:
-
-
(Preview, Version of record, pdf, 1.7MB, Terms of use)
-
- Publisher copy:
- 10.1186/s40561-025-00390-5
Authors
- Publisher:
- SpringerOpen
- Journal:
- Smart Learning Environments More from this journal
- Volume:
- 12
- Issue:
- 1
- Article number:
- 38
- Publication date:
- 2025-06-05
- Acceptance date:
- 2025-05-12
- DOI:
- EISSN:
-
2196-7091
- Language:
-
English
- Keywords:
- Subtype:
-
Review
- Source identifiers:
-
3003163
- Deposit date:
-
2025-06-05
This ORA record was generated from metadata provided by an external service. It has not been edited by the ORA Team.
If you are the owner of this record, you can report an update to it here: Report update to this record