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GESIS Training Courses
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Wiss. Koordination

Alisa Remizova

Administrative Koordination

Noemi Hartung

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Integrating AI into the Qualitative Research Workflow

About
Veranstaltungsort:
Online via Zoom
General Topics:
Computational Social Science, Qualitative Methods
Course Level:
Beginner
Format:
Workshop
Software used:
none
Duration:
2 days
Language:
English
Fees:
Student: 220 €
Academic: 330 €
Commercial: 660 €
 
Keywords
Additional links
Dozierende: Christina Silver

Referenteninformationen - Christina Silver

Seminarinhalt

Registration deadline: 11.02.2027
Registration after this date might be possible, but is subject to sufficient demand and availability of places. 
 
The capabilities of Large Language Models (LLMs) and the AI-assisted analysis tools that derive from these technologies raise significant questions for qualitative research. This course will provide a comprehensive understanding of the landscape of Artificial Intelligence (AI) in qualitative research, covering the principles, practices, and ethics of using these technologies throughout the analytic workflow. A range of tools designed to facilitate qualitative research that harness AI in different ways will be introduced, and you will have the opportunity to experiment with a selection of them, using sample data and your own research materials, if appropriate.
The emphasis of the course will be on critically reflecting on the potential role and appropriate use of AI-driven tools in qualitative research. This will include the recently emerging generative AI tools, and also more traditional AI tools that have been available for longer. Ethical issues will be central, along with how to document the use of AI transparently, and best practices for integrating AI with human interpretation in qualitative studies. We will also discuss the future of qualitative research in the generative AI world, reflecting on the impact of these technologies on methods. You will leave the course with a clear understanding of the implications of employing AI in qualitative studies and with practical experience of several tools.
The qualitative AI space is evolving quickly, so the tools focused on during this course are subject to change, depending on what will be available at the time of the course, but will include tools from across the qualitative AI space. You will have free access to all the tools used for the purpose of the course and will be provided access ahead of the first sessions.
 
Organizational structure of the course
The course will comprise lectures, discussion, guided instruction, and group work. Typically, each session will begin with a theoretical discussion in the form of a lecture and discussion, followed by either guided instruction or group work (in breakout rooms), followed by feedback and discussion. Theoretical discussions will be accompanied by lecture notes/slides and supplementary resources, and will be delivered either live or via short, pre-recorded lectures. Guided instruction will involve the lecturer demonstrating the use of a software or online app to enact an aspect of an analysis method, which you will follow on your own devices in real time. Group work will involve you working together in small groups (4-5 students) following analytic exercises provided in handouts. Full instructions will be provided for each exercise, and the lecturer will be available to support group work as necessary. You are required to feedback your evaluations for discussion afterwards.  


Zielgruppe

You will find the course useful if:
  • You are embarking on a qualitative research project and are planning your analysis;
  • You are experienced in qualitative research and want to understand how new AI technologies can be appropriately harnessed;
  • You are interested in contemporary discussions and debates about the role of AI in qualitative social science research.  


Lernziel

By the end of the course, you will:
  • Understand historical contexts of current developments in AI within the qualitative research field;
  • Understand the range of ethical issues involved in using AI for qualitative research and how to navigate its use in appropriate ways;
  • Possess critical thinking skills around the role of AI in different qualitative research contexts;
  • Understand the potential uses of AI tools at different stages of the qualitative analysis workflow;
  • Understand the methodological consequences of using AI tools (potentials and risks);
  • Possess skills in harnessing AI tools in ways that enable human-centered approaches.


Voraussetzungen

  • You will need to be able to access trial versions of software to follow the hands-on exercises (free access will be provided, but the software may need to be installed ahead of time);
  • You should have a general understanding of qualitative research and analysis (e.g. how qualitative research differs from quantitative and mixed-methods research, and at least a basic appreciation of the differences between analytic methods, such as qualitative content analysis, thematic analysis, and discourse analysis);
  • You will be required to complete a pre-course exercise involving the coding of a short extract of qualitative data that will be used as the basis of comparing human and AI analysis.
 
Software requirements
This course will use examples from different genres of AI tools for qualitative analysis, as follows. Details for accessing/installing as relevant will be provided ahead of the course for registered participants. No cost is incurred.
 
  • General purpose AI Chatbot (e.g. ChatGPT, Claude, Copilot, etc.). This can be a free version or enterprise version available to you via your institutional affiliation.
  • Reveal (free trial version). This is an online app, so no prior installation is required, only signing up for a trial account.
  • MAXQDA with AI Assist enabled (free trial version). The software requires local installation ahead of the course.


Zeitplan

Literaturempfehlungen