Generative AI for Data Analysis
Discover how GenAI can assist you with data analysis throughout the research process.
GenAI is rapidly changing how researchers work, including during the data analysis phase. In this interactive, hands-on workshop, you will discover how to use tools such as ChatGPT, Claude, Gemini, and Copilot for data analysis in your research in a practical and responsible way. We focus on qualitative research, quantitative research, and data visualization. No technical background is required, just curiosity and a willingness to experiment. This workshop focuses on the basics of GenAI for data analysis.
Practical information:
Leertraject
Georganiseerd door:
Why follow this workshop?
GenAI can be a powerful co-pilot for data analysis, but to truly unlock its potential, you need insight into what it can do, what it (still) cannot do, and how to apply it responsibly. As a PhD student, postdoc, or research staff member, it is essential to remain critical at every step of the research process. In this workshop, you will learn exactly that: how to use GenAI smartly for data analysis while maintaining scientific integrity.
What can you expect?
The workshop consists of three parts. We start with a clear introduction: what exactly is GenAI, and how does it differ from classical AI? Next, we explore the importance of responsible use, with attention to topics such as privacy, data security, bias, and the role of humans in the process.
In the second part, we get hands-on. In an interactive and practical way, we explore tools such as ChatGPT, Copilot, and Claude. We look at concrete applications for data analysis in the research process. The hands-on part is structured around three pillars:
- Qualitative research: to what extent can GenAI be used responsibly for, among other things, content analysis, as a second coder, or for testing your interview guide?
- Quantitative research: how can GenAI support statistical analysis, data cleaning, interpreting output, and writing code?
- Data visualization: how do you communicate research results visually to different audiences, both academically and for societal outreach?
To close the session, you will apply the insights from the workshop to your own research context. You will leave the session with a clear picture of what GenAI already makes possible today, and with a critical view of its limitations.
Learning objectives
After this workshop, you will be able to:
- Explain how GenAI works and how it differs from classical AI.
- Write effective prompts that match your data analysis tasks.
- Use GenAI responsibly for qualitative research, quantitative research, and data visualization.
- Choose the right tool (ChatGPT, Claude, Copilot, Gemini) for the right task.
- Critically evaluate when GenAI adds value in your research process.
Who is this workshop for?
This workshop is designed for any researcher, PhD students, postdocs, and research staff, regardless of discipline. No technical background is required. The practical applications will be tailored to the participants’ input and needs, so the session is relevant to your research context.
Teacher / speaker
Eva Blondeel
Eva Blondeel is a postdoctoral researcher within the Accounting Education Research Group at the Faculty of Economics and Business Administration of Ghent University. She obtained a Master in Business Economics with specialization in Accountancy and a PhD in Applied Economics at the same university. Prior to her academic career, Eva worked as a Junior Auditor at Deloitte.
Eva's research focuses on improving accounting education by encouraging students to use active learning methods to reduce procrastination. Recently, her research expanded further into the integration of Generative AI (GenAI) within accounting education and finance. She teaches courses such as Financial Accounting and Accounting in Practice and regularly conducts workshops and keynotes on GenAI applications for students, education professionals and academic colleagues. Her scholarly work has been published in multiple international journals such as Assessment & Evaluation in Higher Education, The British Accounting Review, Studies in Higher Education, Issues in Accounting Education and Accounting in Europe.Expertise:
- GenAI in finance, accounting, and accounting education
Learning Trajectory on Generative AI for Professionals in Higher Education
This is a suggestion for a learning trajectory on generative AI, targeted at professionals working in higher education (e.g., researchers, lecturers, administrative and technical staff, policymakers). The learning modules were carefully selected by VAIA to create a holistic and realistic starting point for educating this target group on GenAI. This trajectory gets updated regularly!
