Transforming Monitoring and Evaluation in Africa: Leveraging Ai for Contextualised and Decolonised Approaches

小组座谈 | Online

About the Event


This panel is designed for anyone involved in producing, using, or questioning evidence in Africa, particularly those interested in how AI can be applied responsibly while advancing contextualised and decolonised evaluation approaches. The audience thus can be as varied as monitoring and evaluation professionals, government and policy makers, development and donor organisations, Ai, data and technology experts, ethics, governance and advocacy stakeholders, and emerging evaluation professionals.

Participants will gain insights into how AI can be leveraged to strengthen evidence generation and use, while remaining grounded in contextualised, Made-in-Africa evaluation approaches. The discussion will also critically engage with questions of ethics, governance, and human judgment, equipping attendees with perspectives and tools to navigate a rapidly evolving and increasingly contested evidence ecosystem.

Key Takeaways:
The panel will explore how artificial intelligence is reshaping the Monitoring and Evaluation landscape in Africa, with a focus on practical applications and emerging trends. Participants will gain insights into how AI can be leveraged to strengthen evidence generation and use, while remaining grounded in contextualised, Made-in-Africa evaluation approaches. The discussion will also critically engage with questions of ethics, governance, and human judgment, equipping attendees with perspectives and tools to navigate a rapidly evolving and increasingly contested evidence ecosystem.

The event will be a fully online event and will be hosted on Google Meet. The platform will support high-quality video conferencing, screen sharing, live captions, and recording to ensure accessibility and documentation of the session.

The session will conclude with closing reflections from panelists, highlighting key insights and practical takeaways for participants. This format ensures a dynamic, interactive, and insight-driven discussion that balances expert input with audience participation.

Speakers

名称 标题 Biography
(Note: The panelists identities will be revealed only after the proposals are accepted, as their consent is still being sought.) Panelist 1 will be a resource person who has contributed to integrating AI into Monitoring and Evaluation by advancing Made-in-Africa AI approaches that centre local contexts, knowledge systems, and languages in evidence generation. Panelist 2 will be a resource person who has contributed to integrating AI into Monitoring and Evaluation by advancing the use of AI-powered evidence gap maps to synthesise large volumes of research on complex issues like gender-based violence. Panelist 3 will be a resource person who leads the broader research on AI policy, governance, and responsible innovation on the continent and would provide high level insights into standards and governance frameworks.

Moderators

名称 标题 Biography
Ms Eleanor Hazell Executive Manager: Monitoring and Evaluation Ms Eleanor Hazell is a monitoring and evaluation specialist and researcher with over 17 years’ experience in evaluation and research in the education and social sectors across South Africa and Sub-Saharan Africa. She is Executive Manager: Monitoring and Evaluation at JET and holds an MPhil in Monitoring and EvaluationMethods (cum laude) from Stellenbosch University and a Master’s in Development Studies from the University of KwaZulu-Natal. Eleanor has led more than 25 monitoring, evaluation, and research assignments, including design, process, outcome, and impact evaluations, many using mixed-methods and quasi-experimental approaches. She has extensive experience developing monitoring and evaluation frameworks, clarifying programme theories of change, designing evaluation matrices and indicators, and translating evaluation findings into actionable learning for programme and policy stakeholders. She has served as technical evaluation lead on multiple large-scale evaluations within South Africa’s National Evaluation Plan and has provided advisory support to Ministries of Education across several African countries on monitoring and evaluation systems and programme performance frameworks.
Jaya Sojen Monitoring and Evaluation Officer Ms Jaya Sojen is an experienced M&E officer with a strong background in research and M&E projects. She holds a Masters Degree in Management with a focus on M&E, as well as a Postgraduate Diploma in Development Management. Additionally, she has a Masters Degree in Agricultural Sciences. Ms Sojen has extensive experience in conducting impact evaluations using both quantitative and qualitative methods, specifically in development projects. Ms Sojen is skilled in Results-Based Management Systems and has expertise in data collection, analysis, and indicator development in multiple sectors. Ms Sojen is an experienced Monitoring, Evaluation, Research, and Learning (MERL) practitioner with a strong track record in project managing complex evaluation assignments. She demonstrates advanced proficiency in the conceptualisation and design of evaluation studies, with particular strength in aligning evaluation questions to appropriate methodological approaches to ensure rigor, relevance, and utility of findings. Her academic training further strengthens her applied expertise, having conducted evaluation research. This experience has contributed to her ability to navigate education-sector evaluations with contextual sensitivity and methodological depth. Jaya has a strong interest in innovation within the evaluation field, particularly in the integration of artificial intelligence (AI) to enhance data collection, analysis, and learning processes. She actively engages in professional communities of practice in MERL, contributing to knowledge exchange and staying abreast of emerging trends and best practices in the field.

Topics and Themes

Evaluators Evaluation Comissioners Evaluation users Decision makers VOPEs / Evaluation networks Yearly Theme: Evaluation, Evidence and Trust in the Age of AI

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