at Google ScholarTitle data
Braune, Justus ; Conradty, Catherine ; Bogner, Franz X. ; Paul, Jürgen:
A game-changer for qualitative research : artificial intelligence as an efficient tool for analyzing student conceptions about microplastics.
In: Frontiers in Education.
Vol. 11
(2026)
.
- 1770878.
ISSN 2504-284X
DOI: https://doi.org/10.3389/feduc.2026.1770878
Project information
| Project title: |
Project's official title Project's id MINT-Lehramt PLUS S-NW-2015-316 SFB 1357: MIKROPLASTIK – Gesetzmäßigkeiten der Bildung, des Transports, des physikalisch-chemischen Verhaltens sowie der biologischen Effekte: Von Modell- zu komplexen Systemen als Grundlage neuer Lösungsansätze 391977956 SYNAPSES - Establishing Teacher Education Networks and Communities of Practice on Teaching for Sustainability Citizenship 101102346 Discovery Space 101086701 Open Access Publizieren No information |
|---|---|
| Project financing: |
Bundesministerium für Bildung und Forschung Deutsche Forschungsgemeinschaft EU-Bildungsprogramme Andere |
Abstract in another language
Qualitative content analysis of learners’ conceptions is due to large datasets time-consuming. This study examined the potential of a Large Language Model (LLM) to support and accelerate qualitative content analysis without compromising validity. Written responses from 180 bachelor students at two German universities to four open-ended questions on microplastics were analysed. ChatGPT was used to inductively develop categories and to assign responses. Two human expert coders conducted the same procedures for comparison purposes. The inter-rater reliability was calculated using Cohen’s kappa and two independent ChatGPT runs were performed to test consistency. The categorization system generated by ChatGPT largely corresponded to the human-developed system. The two ChatGPT runs showed highly consistent classifications, with inter-rater reliabilities of up to κ = 0.96. That exceeded both intra- and inter-rater agreement of the human coders (κ = 0.45–0.90). Overall, our findings suggest that LLMs can support valid and reliable qualitative content analysis while substantially reducing analysis time. In this respect, the use of LLMs may represent a methodological game-changer for qualitative research, making such approaches more efficient and accessible, also for classroom teachers.