Workshops

Fundamentals of Qualitative Research: Design, Interviews, and Analysis

A One-Day Practical Workshop

Overview

Are you starting your qualitative research but feeling unsure about where to begin? Before you use software or AI, you need to understand the basics of how to do research correctly.

This one-day workshop is a step-by-step guide for postgraduate students. We explain complex academic concepts in simple, clear language. You will learn how to design your study, how to interview participants effectively, and how to analyze your data manually. This course gives you the strong foundation you need before moving on to advanced tools.

Who Should Attend:

  • PhD & Master’s Students from all disciplines who want a clear explanation of research methods.

  • Researchers (Home and International) looking for accessible, jargon-free training.

  • First-Year Researchers preparing for their data collection.

Learning Objectives

By the end of this workshop, you will be able to:

  • Understand the Basics: Clearly explain the key concepts of research philosophy (Ontology and Epistemology) and how they fit your study.

  • Design Your Study: Choose the right method for your research (e.g., Case Study, Phenomenology).

  • Collect Good Data: Create interview questions and learn how to be a good interviewer.

  • Analyze by Hand: Learn how to find "codes" and "themes" in your transcripts without using computer software (using the Braun & Clarke method).

  • Ensure Quality: Learn how to make your research trustworthy and academic.

Prerequisites:

  • None. This course is for beginners.

Mastering the Literature Review: Search, Synthesis, and Writing

A One-Day Practical Workshop

Overview

Writing a Literature Review is one of the hardest parts of a thesis. Many students get stuck reading endless papers without knowing when to start writing. Others receive feedback that their writing is "too descriptive" or "lacks critical analysis."

This workshop solves these problems. We guide you through a step-by-step process: from finding the right papers to organizing them into a strong argument. You will learn how to stop summarizing authors one by one and start synthesizing ideas like a scholar. We teach you practical techniques to organize your reading and write with authority.

Who Should Attend:

  • PhD & Master’s Students struggling to structure their Literature Review chapter.

  • Students who feel overwhelmed by the amount of reading they need to do.

  • Researchers who have received feedback that their work needs more critical analysis.

Learning Objectives

By the end of this workshop, you will be able to:

  • Search Smart: Use effective keywords and databases to find the most relevant papers without wasting time.

  • Read Efficiently: Learn how to "gut" a paper quickly to find the key information you need.

  • Synthesize, Don't List: Stop saying "Author A said this, Author B said that." Learn how to group authors by themes and concepts.

  • Structure Your Chapter: Use the "Funnel Method" to organize your chapter from broad topics to your specific research gap.

  • Write Critically: Learn simple sentence structures that show you are analyzing the literature, not just reporting it.

Prerequisites:

  • None. Bringing a few papers from your own research topic is recommended but not required.

AI-Assisted Qualitative Data Analysis: Principles, Practices, and Ethics

A One-Day Intensive Workshop

Overview 

Generative AI is transforming the landscape of qualitative research, offering powerful new ways to interact with data. However, for the rigorous researcher, it also brings critical challenges regarding privacy, bias, and methodological integrity.

This one-day, hands-on workshop goes beyond the hype to provide a grounded, practical guide to integrating AI into your qualitative workflow. Designed for researchers, PhD candidates, and analysts, we focus on augmentation, not replacement—teaching you how to use AI as a capable "virtual research assistant" while maintaining full human control over interpretation and theory building.

Who Should Attend:

  • PhD Students & Early Career Researchers looking to streamline their analysis without compromising rigor.

  • Academic Staff managing large qualitative datasets.

  • Master’s Students handling qualitative data for their dissertations.

Note: No prior coding or technical AI knowledge is required. A foundational understanding of qualitative methods (coding, thematic analysis) is assumed.

Learning Objectives

By the end of this workshop, you will be able to:

  • Navigate the Ethical Landscape: confidently address data privacy (GDPR), algorithmic bias, and transparency in your ethics applications and methodology chapters.

  • Master "Hybrid" Analysis: Use MAXQDA’s AI Assist to summarize transcripts, generate inductive codes, and refine code definitions deductively.

  • Explore AI-Native Tools: Gain hands-on experience with Reveal AI to analyze data at scale using conversational intelligence.

  • Future-Proof Your Reporting: Learn how to document your AI-assisted process to ensure your methodology remains defensible and transparent.

    Prerequisites:

  • A laptop with internet access.

  • Software: Participants will be guided on how to install trial versions of MAXQDA 2024 and access the Reveal AI demo prior to the session.