Looking Beyond Numbers in Qualitative Research: From Data Saturation to Data Analysis

Authors

Prokopis Christou PhD, Cyprus University of TechnologyFollow

Abstract

In the realm of qualitative research, numbers have often been viewed with skepticism, and their role remains controversial. Despite this ambivalence, the importance of numerical data in qualitative research cannot be disregarded. This paper critically examines the increasing integration of numbers and algorithms, particularly through Artificial Intelligence (AI) technologies, within qualitative inquiry. It explores the role and implications of numerical data, emphasizing key principles such as data saturation. The paper highlights concerns associated with AI-assisted data analysis, including the risks of oversimplification, reductionist approaches, and detachment from context. It also addresses the potential dangers of technological over-reliance during the analysis phase, which may inadvertently undermine the richness, depth, and narrative complexity that qualitative research seeks to capture. Additionally, it raises concerns about the deification of technology, where researchers might come to value only AI-generated analyses, leading to an over-dependence on these tools. By providing practical examples and a critical assessment of AI-assisted tools, the paper advocates for a balanced approach that recognizes the benefits of AI technologies while safeguarding the essential interpretative and contextual insights central to qualitative inquiry.

Keywords

qualitative research, data analysis, data saturation, artificial intelligence, AI

Author Bio(s)

Prokopis A. Christou is an Assistant Professor at the Cyprus University of Technology, specializing in qualitative inquiry and the implications of AI in research and social fields. He has published books and numerous articles in prestigious academic journals, covering conceptual papers, critical perspective articles, systematic reviews, and empirical studies, including ethnographic and phenomenological research. His interest in AI stems from its growing utility across various fields, alongside concerns about potential risks, such as the diminishing human element, reduced investment in critical and evaluative thinking, and challenges to ethical and academic integrity. Consequently, he has explored the applications, potentials, dynamics, limitations, and implications of AI in research. Please direct correspondence to prokopis.christou@cut.ac.cy

Publication Date

2-16-2025

Creative Commons License

This work is licensed under a Creative Commons Attribution-Noncommercial-Share Alike 4.0 International License.

DOI

10.46743/2160-3715/2025.7560

Recommended APA Citation

Christou, P. A. (2025). Looking beyond numbers in qualitative research: From data saturation to data analysis. The Qualitative Report, 30(1), 3088-3100. https://doi.org/ 10.46743/2160-3715/2025.7560

ResearcherID

https://orcid.org/0000-0001-6628-2619