Written by Dr. Susanne Friese
Throughout the year, I've had the pleasure of sharing a series of blog posts focused on the art and science of analyzing qualitative data using traditional Computer-Assisted Qualitative Data Analysis Software (CAQDAS), particularly ATLAS.ti. These posts were inspired by a book I published back in 2019, providing insights and guidance for researchers navigating the intricacies of ATLAS.ti in their qualitative research endeavors.
When I authored the book, the software ATLAS.ti was at its 8th iteration. Since 2021, versions have been named after the corresponding year, making 2023 the latest release as I pen this post. However, I've decided against updating my book due to the rapid pace of software development, which far outstrips the traditional publishing process.
Remarkably, the advancements in AI I've witnessed and participated in are reshaping our approach to data analysis. The methods I described in my book now seem antiquated in the face of these new technologies. In the future, coding of data will become obsolete. We will interact with our data more intuitively, using AI assistants to ask questions and extract pertinent information. This paradigm shift from code-based querying to AI-assisted analysis is not just a possibility—it's an impending reality. It's an exciting time to challenge and redefine the methodologies we've adhered to for the last 30 to 50 years, leveraging the cutting-edge technologies now at our disposal.
I recognize, though, that the adoption of such groundbreaking technology won't be instantaneous. There will be a transitional period where traditional coding methods coexist with these new AI-driven approaches.
For those who continue to rely on traditional coding methods, I have updated and shared key sections from my 2019 book throughout this year in this blog.
Furthermore, I've created a comprehensive video series covering the entire spectrum of computer-aided qualitative data analysis, from project setup to research write-up. These videos include methodologies and practical applications in both MAXQDA and ATLAS.ti. Here's the link to the video playlist.
While ATLAS.ti ventured into the realm of AI, their approach has been predominantly technological, somewhat diverging from the essence of qualitative data analysis. Once a software deeply rooted in research and crafted by researchers, ATLAS.ti seems to have transitioned away from this philosophy.
Although the features developed by and for qualitative researchers remain, the AI components introduced may not fully resonate with the core objectives of qualitative analysis. To delve deeper into my perspective on the effectiveness of ATLAS.ti's AI features, I invite you to view the following videos:
The video below delves into the reasons why the current implementation of the AI coding feature is neither effective nor efficient. Since recording the video, there have been extensions to the AI functionalities (as shown in the video above), yet the results remain unconvincing.
2023 and Beyond
The year 2023 was a period of extensive experimentation for me, as I explored AI features in both traditional CAQDAS software and innovative apps like Coloop and AILYZE, designed from the ground up with AI. These explorations led me to conceptualize a unique approach to AI-powered qualitative data analysis. To turn this vision into reality, I teamed up with a remarkable partner and a dedicated group of developers. Together, we're crafting a new application that promises to revolutionize the way we conduct qualitative research. Visit out website at: https://www.qeludra.ai/
Therefore, this article signifies a pivotal moment as we confidently stride into an AI-enhanced future. It marks the beginning of a series dedicated to guiding you through this transition, from traditional coding methods to the dynamic and limitless world of AI in qualitative research.
Cite as follows:
Friese, S. (2023). "From Coding to AI: Bridging the Past and Future of Qualitative Data Analysis." Dr. Susanne Friese's Blog. Available at: https://www.drsfriese.com/post/from-coding-to-ai-bridging-the-past-and-future-of-qualitative-data-analysis