Duration of the workshop

2.5 h

Target groups

Applied researchers, data scientists, methodologists, and research communicators who want to convert datasets, literature syntheses, or analysis outputs into interactive dashboards and tools without deep full-stack expertise.

Is the workshop geared at an exclusively German or an international audience?

International Audience

Workshop language

English

Description of the content of the workshop

This practical workshop will introduce researchers to vibe coding, a rapidly emerging AI-assisted approach that allows researchers to analyze, design, and share their work through natural language interaction, rather than conventional programming.
Vibe coding is a collaborative and iterative workflow where large language models generate either analytic insight, functional code, or web interfaces based on the goals and feedback of the researcher. In practice, it bridges the entire research cycle, from data analysis (qualitative and quantitative) to digital dissemination. It allows researchers to structure and interpret data
in an interactive way, automate parts of their analysis, and then transform their results into interactive, open, and participatory online formats.
The workshop will explore ways in which emerging AI coding assistants—e.g., OpenAI Codex, Claude Sonnet Code—and cloud-based environments—Replit, Vercel, Windsurf—can support social scientists both in performing analytic tasks and creating lightweight public research portals. Guided demonstrations and teamwork exercises take participants through the steps involved in conceptualizing a design system for the research analysis and communication, experimenting with emergent forms of AI-assisted coding templates, and discussing ethical, privacy, and sustainability considerations.
A short demo—the “Mapping Afghan Diaspora Organizations” portal—will illustrate how vibe coding supports both analytical insight and interactive dissemination within one coherent system.

Goals of the workshop

Understand the principle behind vibe coding and its dual role in data analysis and
dissemination of research findings.
- Use AI-driven tools to analyze or structure data using natural, plain-language
interaction; no prior coding experience is necessary.
- Create a simple interactive prototype that communicates research findings, using
Replit and provided templates.
- Reflect on the ethical and practical issues regarding AI-assisted research with respect
to privacy, bias, transparency, and long-term maintenance.

Necessary prior knowledge of participants

1. No prior programming or "coding" experience is strictly necessary. 2. Familiarity with using Large Language Models (e.g., ChatGPT, Claude) is helpful but not required. 3. A willingness to experiment with new digital tools is essential.

Information about the instructor

Ali Reza Hussani is a PhD candidate at the Institute of Communication Science and Journalism at Leipzig University. His research investigates online behaviors on social media, operating at the intersection of policy, evidence, and social impact. His background is in political science and conflict management. He completed a focused data science bootcamp at Spiced Academy Berlin to enhance his methodological toolkit. He is a passionate enthusiast for AI in academia, continuously adopting and experimenting with new AI-assisted workflows to make research more efficient and interactive.

Maximum number of participants

20

Will participants need to bring their own devices in order to be able to access the Internet? Will they need to bring anything else to the workshop?

Yes. Participants must bring their own laptop.