Naftali Ndeapo Indongo
Current Organizations / Institutes
The organizations/institutes from the scholar's latest article
Naftali Ndeapo Indongo has a total of 12 co-authors. Here are the top co-authors by number of shared publications:
- Heike Winschiers-Theophilus
Software Engineering, Namibia University of Science and Technology, Windhoek, Namibia
2 shared publications - Rachel Charlotte Smith
Dept. of Digital Design and Information Studies, Aarhus University, Aarhus, Denmark
2 shared publications - Cassius Guiob-Badmos
Namibia University of Science and Technology,Department of Software Engineering,Windhoek,Namibia
1 shared publication - Franco Beukes
Namibia University of Science and Technology,Department of Software Engineering,Windhoek,Namibia
1 shared publication - Johnson Haimbili Kaulinge
Namibia University of Science and Technology,Department of Software Engineering,Windhoek,Namibia
1 shared publication - Josephina Muntuumo
School of Computing, Faculty of Science, Forestry and Technology, University of Eastern Finland, Joensuu, Finland
1 shared publication
Latest Publications
- Open Access
- 19 July 2026
- Published by Association for Computing Machinery (ACM)
- p. 5297-5300
Offline-First Information Retrieval for Curriculum-Aligned STEM Resources in Low-Resource Namibian Schools
Many Namibian schools face recurring connectivity and infrastructure constraints, yet ICT-in-education initiatives often assume always-on internet and cloud-based platforms for STEM teaching and learning. This paper asks what changes when the school, rather than the cloud, is treated as the primary locus of information retrieval. We describe the design of an offline-first IR prototype that hosts a curriculum-aligned STEM repository locally and supports keyword search, BM25 ranking, and curriculum-aware facets. Framing the system explicitly as IR raises questions that current offline educational platforms tend to leave under-specified: how should ranking and faceted search be designed when bandwidth, devices, storage, and power are scarce; how might teachers' and learners' retrieval behaviour change when queries remain inside the school network; and how can such systems be evaluated when large-scale logging and A/B testing are unlikely to be feasible in many classrooms? We outline the system architecture and a mixed-methods evaluation plan combining local interaction logs, teacher-rated relevance judgements, and qualitative classroom evidence.
- 19 July 2026
- Published by Association for Computing Machinery (ACM)
- p. 5297-5300
Open AccessOffline-First Information Retrieval for Curriculum-Aligned STEM Resources in Low-Resource Namibian Schools
Many Namibian schools face recurring connectivity and infrastructure constraints, yet ICT-in-education initiatives often assume always-on internet and cloud-based platforms for STEM teaching and learning. This paper asks what changes when the school, rather than the cloud, is treated as the primary locus of information retrieval. We describe the design of an offline-first IR prototype that hosts a curriculum-aligned STEM repository locally and supports keyword search, BM25 ranking, and curriculum-aware facets. Framing the system explicitly as IR raises questions that current offline educational platforms tend to leave under-specified: how should ranking and faceted search be designed when bandwidth, devices, storage, and power are scarce; how might teachers' and learners' retrieval behaviour change when queries remain inside the school network; and how can such systems be evaluated when large-scale logging and A/B testing are unlikely to be feasible in many classrooms? We outline the system architecture and a mixed-methods evaluation plan combining local interaction logs, teacher-rated relevance judgements, and qualitative classroom evidence.
- Open Access
- 14 June 2026
- Published by Association for Computing Machinery (ACM)
- p. 446-456
Designing Responsible AI with Indigenous Communities: Towards Participatory AI with ovaHimba and San People in Namibia
- 14 June 2026
- Published by Association for Computing Machinery (ACM)
- p. 446-456
Open AccessDesigning Responsible AI with Indigenous Communities: Towards Participatory AI with ovaHimba and San People in Namibia
- 5 August 2025
- Published by Institute of Electrical and Electronics Engineers (IEEE)
- p. 1-9
Mirror of Reflections: Creating Relatable AI-Generated Motivational Stories from San Youth Experiences and San Elders' Wisdom
In the absence of digital texts from minority groups, such as San from Southern Africa, public generative AI systems create responses that lack relevance and contextual understanding of local people. This study explores the relatability of AI-generated motivational stories from a Retrieval-Augmented Generation system accessing a curated knowledge base of previously collected real-life San youth experiences and San elder's wisdom proverbs. A focus group session was conducted with 46 members of the San community to collaboratively frame how AI could be used to generate culturally valid motivational stories to promote educational resilience. An AI story generation was simulated with San youth to determine relatability. Based on this, a fully functional prototype was developed, with a smart mirror interface, that detects basic emotions to trigger the construction of motivational stories for San youth. The system was evaluated through feedback sessions with youth and elders, focusing on emotional resonance, cultural appropriateness, and contextual understanding. Results showed that participants responded positively to stories grounded in their lived experiences and traditional wisdom, confirming the importance of contextual knowledge bases. The system was seen as a source of emotional encouragement; however, challenges such as limited literacy among users also highlighted the need for further development to make the tool fully inclusive and culturally grounded.
- 5 August 2025
- Published by Institute of Electrical and Electronics Engineers (IEEE)
- p. 1-9
Mirror of Reflections: Creating Relatable AI-Generated Motivational Stories from San Youth Experiences and San Elders' Wisdom
In the absence of digital texts from minority groups, such as San from Southern Africa, public generative AI systems create responses that lack relevance and contextual understanding of local people. This study explores the relatability of AI-generated motivational stories from a Retrieval-Augmented Generation system accessing a curated knowledge base of previously collected real-life San youth experiences and San elder's wisdom proverbs. A focus group session was conducted with 46 members of the San community to collaboratively frame how AI could be used to generate culturally valid motivational stories to promote educational resilience. An AI story generation was simulated with San youth to determine relatability. Based on this, a fully functional prototype was developed, with a smart mirror interface, that detects basic emotions to trigger the construction of motivational stories for San youth. The system was evaluated through feedback sessions with youth and elders, focusing on emotional resonance, cultural appropriateness, and contextual understanding. Results showed that participants responded positively to stories grounded in their lived experiences and traditional wisdom, confirming the importance of contextual knowledge bases. The system was seen as a source of emotional encouragement; however, challenges such as limited literacy among users also highlighted the need for further development to make the tool fully inclusive and culturally grounded.