| dc.contributor.author | Kahenya, N. P. | |
| dc.date.accessioned | 2026-10-16T11:16:15Z | |
| dc.date.available | 2026-10-16T11:16:15Z | |
| dc.date.issued | 2025 | |
| dc.identifier.isbn | 9798337387956 | |
| dc.identifier.uri | 10.4018/979-8-3373-8795-6.ch010 | |
| dc.identifier.uri | http://repository.anu.ac.ke/handle/123456789/1236 | |
| dc.description | This book chapter is published by IGI Global Scientific Publishing. In book: Advancing Access to Digital Learning (pp.311-348). | en_US |
| dc.description.abstract | The advancement of generative artificial intelligence (GenAI) presents a transformative opportunity to address educational inequalities in sub-Saharan Africa (SSA). The educational landscape is at the crossroads where strategic adoption of free and open GenAI could fundamentally transform learning equity. This chapter builds a case on how emerging openly accessible models are creating unprecedented opportunities that, if well utilized, can bridge educational gaps that plague this region. Unlike the proprietary systems, these openly accessible models may significantly lower deployment costs and offer adaptable architectures for low-resource environments that are synonymous with sub-Saharan Africa. The chapter outlines practical and actionable strategies, including policy reviews and formulation where none exist to including hybrid deployment systems combining offline AI capabilities. Teacher trainings that focus on prompt engineering with open-source tools and public-private partnerships to ensure sustainable implementation.. Kahenya, Paul. (2026). The Future of Learning: Openly Accessible Generative AI Models as a Catalyst for Educational Equity in Sub-Saharan African Countries. 10.4018/979-8-3373-8795-6.ch010. The advancement of generative artificial intelligence (GenAI) presents a transformative opportunity to address educational inequalities in sub-Saharan Africa (SSA). The educational landscape is at the crossroads where strategic adoption of free and open GenAI could fundamentally transform learning equity. This chapter builds a case on how emerging openly accessible models are creating unprecedented opportunities that, if well utilized, can bridge educational gaps that plague this region. Unlike the proprietary systems, these openly accessible models may significantly lower deployment costs and offer adaptable architectures for low-resource environments that are synonymous with sub-Saharan Africa. The chapter outlines practical and actionable strategies, including policy reviews and formulation where none exist to including hybrid deployment systems combining offline AI capabilities. Teacher trainings that focus on prompt engineering with open-source tools and public-private partnerships to ensure sustainable implementation. | en_US |
| dc.language.iso | en | en_US |
| dc.publisher | IGI Global scientific publishing | en_US |
| dc.subject | The Future of Learning | en_US |
| dc.subject | Openly Accessible Generative AI Models | en_US |
| dc.subject | Educational Equity | en_US |
| dc.subject | Sub-Saharan African Countries | en_US |
| dc.title | The Future of Learning: Openly Accessible Generative AI Models as a Catalyst for Educational Equity in Sub-Saharan African Countries in F. Williams | en_US |
| dc.title.alternative | In book: Advancing Access to Digital Learning (pp.311-348) | en_US |
| dc.type | Book chapter | en_US |