Leveraging AI for Evaluations: Prompt Engineering for Qualitative and Theory-Driven Analysis
Oficina | Online
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Organizado por:
Athena Infonomics
Sobre o evento
The quality of AI outputs depends on prompt design. This hands-on workshop focuses on structured prompt engineering for post-coding qualitative analysis, enabling evaluators to move beyond summaries toward causal inference, pattern interrogation, and theory testing. Participants will design prompts to surface patterns and assess explanatory pathways. The session shows how to operationalise contribution analysis, outcome harvesting, and realist evaluation within AI-assisted workflows. Designed for evaluators with working knowledge of AI tools; access to Claude, Copilot, or ChatGPT is required.
Orador/a
| Nome | Título | Biography |
|---|---|---|
| Aikantika Das | Principal Consultant, MERL – Athena Infonomics | Aikantika Das is a Principal Consultant at Athena Infonomics with 10+ years of experience in qualitative evaluation and research. She specialises in approaches such as contribution analysis, outcome harvesting, and realist evaluation, while integrating AI into qualitative and theory-based analysis. |
Moderators
| Nome | Título | Biography |
|---|---|---|
| Anupama Ramaswamy | Director, MERL – Athena Infonomics | Anupama Ramaswamy is a Director at Athena Infonomics with 15+ years of experience in mixed-methods and theory-based evaluations. She applies AI and data-driven approaches to lead global evaluations, strengthen programmes, and drive policy and systems-level impact. |
| Shrija Dey | Consultant, MERL – Athena Infonomics | Shrija Dey is a Consultant at Athena Infonomics with 3 years of experience. She specialises in contribution analysis and realist evaluation, integrating AI to unpack causal pathways, strengthen evidence generation, and translate data into actionable insights. |