In Tandem With Artificial Intelligence: A working Framework for Coding in ATLAS.ti™

As a leading qualitative researcher, Norman Denzin advocated for a bigger tent to expand and deepen qualitative inquiry. The “tent” metaphor has therefore been used by scholars to advocate for considerations of diverse options around philosophies of inquiry. With the advent of Artificial Intelligence (AI), researchers face additional options around research decisions, philosophically, practically and ethically. Researchers table numerous research questions around AI, given its rapid uptake. These include re-visiting the established notions of human-centered coding, as well as exploring the potential of AI coding, within these notions. There is therefore room to expand “the tent” to delineate 1) the specific use of AI within qualitative data analysis, specifically AI coding, which is now an established function within bespoke qualitative data analysis software (QDAS). Additionally, with AI providing a stream of independent coding, 2) researchers may well deliberate the need for multiple, second or independent coders. This paper responds to this two-fold aim of the study using action research that involved researchers doing coding and using independent coding, in tandem with AI. The contribution of the paper is an outline of these action steps, reflectively culminating in a practical framework. This may be used by researchers, both curious and confident, in seeking novel ways to broaden the scope of their coding practices.

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Institutions

Publication Details

Journal
International Journal of Qualitative Methods
Published
2025-02-01
DOI
https://doi.org/10.1177/16094069241306551
Citations
5
Primary Topic
Qualitative Research Methods and Applications
Type
article
Field-Weighted Citation Impact
44.63

Funders

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article

In Tandem With Artificial Intelligence: A working Framework for Coding in ATLAS.ti™

Charmaine Williamson, Annelien van Rooyen, Rika Dry
5 citations
International Journal of Qualitative Methods
Qualitative Research Methods and Applications
44.63
article

In Tandem With Artificial Intelligence: A working Framework for Coding in ATLAS.ti™

Charmaine Williamson, Annelien van Rooyen, Rika Dry
article en
5 citations

Abstract

As a leading qualitative researcher, Norman Denzin advocated for a bigger tent to expand and deepen qualitative inquiry. The “tent” metaphor has therefore been used by scholars to advocate for considerations of diverse options around philosophies of inquiry. With the advent of Artificial Intelligence (AI), researchers face additional options around research decisions, philosophically, practically and ethically. Researchers table numerous research questions around AI, given its rapid uptake. These include re-visiting the established notions of human-centered coding, as well as exploring the potential of AI coding, within these notions. There is therefore room to expand “the tent” to delineate 1) the specific use of AI within qualitative data analysis, specifically AI coding, which is now an established function within bespoke qualitative data analysis software (QDAS). Additionally, with AI providing a stream of independent coding, 2) researchers may well deliberate the need for multiple, second or independent coders. This paper responds to this two-fold aim of the study using action research that involved researchers doing coding and using independent coding, in tandem with AI. The contribution of the paper is an outline of these action steps, reflectively culminating in a practical framework. This may be used by researchers, both curious and confident, in seeking novel ways to broaden the scope of their coding practices.

International Journal of Qualitative MethodsVol. 24
University of South Africa (ZA)
University of South Africa
Openalex Percentile: Top 0%
Qualitative Research Methods and Applications
44.63
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In Tandem With Artificial Intelligence: A working Framework for Coding in ATLAS.ti™ — Charmaine Williamson, Annelien van Rooyen, et al. · International Journal of Qualitative Methods (2025) | TGRS Research Map | TGRS