How to build a real-life theory of change from your interviews using AI: a Causal Map 4 training session
Atelier | En ligne
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Organisé par:
Causal Map Ltd.
À propos de l'événement
Extracting causal claims from interview transcripts has always been one of the most time-consuming parts of qualitative evaluation.
In this practical training session, we will show you how to speed up this process using our newly rebuilt software, Causal Map 4. We will take raw qualitative data and demonstrate how to find the causal stories hidden inside, using AI as a coding assistant (rather than a black box).
We will guide you through our human-in-the-loop approach. You will see how AI can do the heavy lifting of identifying causal claims, leaving you in full control of the final analysis and interpretation and ultimately use your finished maps to answer practical evaluation questions such as which causal pathways have the most evidence behind them? How do different groups experience the same or different outcomes? What are the unexpected outcomes, and do participants view the changes as mostly positive or negative?
The presentation will cover:
A brief look at what causal mapping is and why it matters for evaluators
A live, step-by-step walkthrough of turning a raw transcript into a clear visual map and how to format it to create empirical theory of change.
How to use AI coding assistance safely and transparently in your workflows
Whether you are new to causal mapping or have used our tools before, this session will give you practical skills to handle your next batch of qualitative data.
In this practical training session, we will show you how to speed up this process using our newly rebuilt software, Causal Map 4. We will take raw qualitative data and demonstrate how to find the causal stories hidden inside, using AI as a coding assistant (rather than a black box).
We will guide you through our human-in-the-loop approach. You will see how AI can do the heavy lifting of identifying causal claims, leaving you in full control of the final analysis and interpretation and ultimately use your finished maps to answer practical evaluation questions such as which causal pathways have the most evidence behind them? How do different groups experience the same or different outcomes? What are the unexpected outcomes, and do participants view the changes as mostly positive or negative?
The presentation will cover:
A brief look at what causal mapping is and why it matters for evaluators
A live, step-by-step walkthrough of turning a raw transcript into a clear visual map and how to format it to create empirical theory of change.
How to use AI coding assistance safely and transparently in your workflows
Whether you are new to causal mapping or have used our tools before, this session will give you practical skills to handle your next batch of qualitative data.
Conférenciers
| Nom | Titre | Biography |
|---|---|---|
| Steve Powell | Co-founder and Director, Causal Map Ltd. | Steve is the lead developer of the Causal Map and QualiaInterviews apps. He has over 25 years of experience in international research and evaluation using quantitative and qualitative approaches. He's the main author of a recent IJSRM paper titled "AI-assisted causal mapping: a validation study". |
| Gabriele Caldas | Outreach Coordinator, Causal Map Ltd | Gabriele is a researcher and internationalist, with experience in qualitative causal analysis, prompt engineering, AI-supported interviewing, and consulting work. She has an MSc in International Development, and she is the co-author of the paper "AI-assisted causal mapping: a validation study". |