Enoch O. Oladunmoye has introduced postgraduate students to QUALIVERS, a next-generation AI-assisted qualitative analysis application, as part of advanced research training at Kampala International University (KIU), Uganda.
Associate Professor Oladunmoye is a lecturer and researcher at KIU and currently serves as the Research Coordinator of the College of Humanities and Social Sciences (CHSS). In this dual role—both as a classroom instructor and a research leader—he is directly involved in strengthening postgraduate research capacity across the university.
Introducing a New Way of Doing Qualitative Thematic Analysis
During postgraduate research methods sessions, Associate Professor Oladunmoye introduced master’s and PhD students to a modern, systematic approach to qualitative thematic analysis using QUALIVERS, particularly after the transcription of interview and focus group data.
Rather than relying solely on traditional, time-intensive manual methods, students were exposed to a workflow that combines:
- rigorous qualitative methodology
- structured thematic analysis
- and responsible AI-assisted support
This approach enables students to move from raw transcripts to meaningful themes more efficiently, while still maintaining full methodological control and interpretive responsibility.
Context: Teaching Research Methods at Master’s and PhD Levels
As the lecturer responsible for Research Methods at the master’s level and Advanced Research Methods for PhD students, Associate Professor Oladunmoye emphasized that qualitative research today demands more than basic coding skills.
He noted that postgraduate researchers increasingly work with:
- large interview datasets
- multi-site fieldwork
- digital and online qualitative data
- time-constrained academic schedules
QUALIVERS was presented as a tool that aligns with these realities—supporting thematic analysis, code development, theme generation, visualization, and reporting, all within a single, coherent platform.
From Transcripts to Themes: A Structured Workflow
Students were guided through a practical qualitative workflow, including:
- Uploading and organizing transcribed interview data
- Segmenting text into meaningful analytic units
- Conducting manual and AI-assisted coding
- Developing code hierarchies and thematic structures
- Reviewing, refining, and naming themes
- Visualizing relationships among codes and themes
This process highlighted how QUALIVERS supports methodological rigor, rather than replacing the researcher’s analytical judgment.
Bridging Theory, Technology, and Research Practice
In his engagement with students, Associate Professor Oladunmoye stressed that QUALIVERS is not merely software, but part of a broader shift in qualitative research practice—one that integrates:
- sound qualitative theory
- ethical and transparent AI use
- reproducible and auditable workflows
- and modern research demands
As Research Coordinator for CHSS, he emphasized the importance of equipping postgraduate students with future-ready research tools that align with both academic standards and global research trends.
Strengthening Postgraduate Research Capacity at KIU
The introduction of QUALIVERS reflects KIU’s broader commitment to research excellence within the College of Humanities and Social Sciences. By exposing students to contemporary qualitative analysis tools early in their postgraduate journey, the university continues to strengthen:
- thesis and dissertation quality
- methodological competence
- analytical confidence among emerging researchers
Looking Ahead
The engagement with QUALIVERS marks a step toward redefining how qualitative research is taught and practiced at postgraduate level—moving from purely manual traditions to intelligent, structured, and transparent analytic systems.
As qualitative research continues to evolve in the age of AI and digital data, initiatives like this ensure that students are not only methodologically grounded, but also technologically prepared.
QUALIVERS — advancing qualitative research, one insight at a time.
