AI in Dissertation Examination: Opportunities for Undergraduates and Postgraduates in Zambia, Rwanda, and Kenya

The integration of Artificial Intelligence (AI) in dissertation examination presents a transformative opportunity for higher education institutions in Zambia, Rwanda, and Kenya. As student enrollments continue to rise, universities face challenges in efficiently evaluating dissertations while maintaining academic integrity. AI-driven tools offer innovative solutions by automating tasks such as plagiarism detection, language quality assessment, and contract cheating identification. This study aims to explore the opportunities, challenges, and impact of AI adoption in dissertation assessment across selected universities. A mixed-methods research design was employed, incorporating surveys, semi-structured interviews, and data analysis from AI-assisted dissertation evaluations at Copperbelt University (Zambia), the University of Rwanda, and Jomo Kenyatta University of Agriculture and Technology (Kenya). Findings indicate that AI enhances efficiency by reducing faculty workload and improving feedback quality for students. However, challenges such as digital literacy gaps, infrastructure limitations, and concerns over AI’s fairness and ethical implications hinder full adoption. Despite these obstacles, there is strong support among students and faculty for AI integration, provided it is complemented by human oversight. The study concludes that AI has significant potential to revolutionize dissertation evaluation but requires investment in infrastructure, faculty training, and policy frameworks to ensure responsible implementation. Collaboration among universities, policymakers, and technology providers is essential to optimizing AI-driven dissertation assessment while upholding academic rigour.

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Publication Details

Journal
LatIA
Published
2025-03-29
DOI
https://doi.org/10.62486/latia2025329
Citations
2
Primary Topic
Artificial Intelligence in Healthcare and Education
Type
article
Field-Weighted Citation Impact
1.31
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article

AI in Dissertation Examination: Opportunities for Undergraduates and Postgraduates in Zambia, Rwanda, and Kenya

Petros Chavula, Fredrick Kayusi, Rashmi Mishra, Michael Keari Omwenga et al.
2 citations
LatIA
Artificial Intelligence in Healthcare and Education
1.31
article

AI in Dissertation Examination: Opportunities for Undergraduates and Postgraduates in Zambia, Rwanda, and Kenya

Petros Chavula, Fredrick Kayusi, Rashmi Mishra, Michael Keari Omwenga, Timothy Mwewa, Linety Juma
article en
2 citations

Abstract

The integration of Artificial Intelligence (AI) in dissertation examination presents a transformative opportunity for higher education institutions in Zambia, Rwanda, and Kenya. As student enrollments continue to rise, universities face challenges in efficiently evaluating dissertations while maintaining academic integrity. AI-driven tools offer innovative solutions by automating tasks such as plagiarism detection, language quality assessment, and contract cheating identification. This study aims to explore the opportunities, challenges, and impact of AI adoption in dissertation assessment across selected universities. A mixed-methods research design was employed, incorporating surveys, semi-structured interviews, and data analysis from AI-assisted dissertation evaluations at Copperbelt University (Zambia), the University of Rwanda, and Jomo Kenyatta University of Agriculture and Technology (Kenya). Findings indicate that AI enhances efficiency by reducing faculty workload and improving feedback quality for students. However, challenges such as digital literacy gaps, infrastructure limitations, and concerns over AI’s fairness and ethical implications hinder full adoption. Despite these obstacles, there is strong support among students and faculty for AI integration, provided it is complemented by human oversight. The study concludes that AI has significant potential to revolutionize dissertation evaluation but requires investment in infrastructure, faculty training, and policy frameworks to ensure responsible implementation. Collaboration among universities, policymakers, and technology providers is essential to optimizing AI-driven dissertation assessment while upholding academic rigour.

LatIAVol. 3
Pwani University (KE), Maasai Mara University (KE), Copperbelt University (ZM), University of Technology and Applied Sciences - Al Mussanah (OM), World Agroforestry Centre (KE)
Openalex Percentile: Top 17%
Artificial Intelligence in Healthcare and Education
1.31
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