Leveraging Artificial Intelligence for Rural Education: ASystematic Review of Transforming Learning Opportunities and Bridging the Urban-Rural Divide
AI has immense potential in transforming rural education -bringing solutions to long-standing problems under resource constraints, insufficient teachingorother forms of educational inequality. Delivering AI-based technologies to limited frameworks in educational systems can be particularly effective in providing tailored learning experiences, virtual classrooms with access to quality educationandusing Natural Language Processing (NLP)to break language barriers. This integration could greatly contribute to an equitable educational environment in which rural students have opportunities similar to those in the cities for their peers. Despite these benefits,there are a number of challenges to the widespread implementation of artificial intelligence in rural education: poor infrastructure, higher cost of implementationandlack of instructor training. Besides, the ethical implication on privacy, information securityandprejudices issues in artificial intelligence needs to be handled sensibly to promote equity and inclusivity. Overcoming these is mostly the collaborative effort between governmental institutions, academic institutionsanddevelopers of the technology coupled with financial input towards infrastructure and educating the educators. The present paper discusses the role that artificial intelligence can play in bridging the gap between urban and rural education, highlights its potential applicabilityanddiscusses the challenges that should be overcome to implement it efficiently. Finally, recommendations are made for further policy development and the enhancement of AI projects in rural education to make the education of all learners more equal and effective.
Authors
- Astha Tripathi
- Vandana Yadav (ORCID: https://orcid.org/0000-0002-7628-894X)
- Sandeep Kumar
Publication Details
- Published
- 2025-01-01
- DOI
- https://doi.org/10.56147/aaiet.1.2.11
- Citations
- 1
- Primary Topic
- Engineering Education and Technology
- Type
- article
- Field-Weighted Citation Impact
- 3.25