How Task Complexity Moderates the Impact of AI-Generated Images on User Experience in Gamified Text Labelling
This study investigates how task complexity influences the impact of AI-generated images on user experience in gamified text-labelling tasks. Participants completed one of two tasks of varying complexity: part-ofspeech (POS) tagging simple and natural language inference (NLI) complex under conditions with and without AIgenerated images. We measured accuracy, engagement, enjoyment, and cognitive load using factorial ANOVAs. Results revealed that task complexity significantly influenced all outcomes: the NLI task yielded lower accuracy, reduced engagement and enjoyment, and increased cognitive load compared with the POS task. AI-generated images had limited impact, negatively affecting perceived usability and overall engagement, with engagement notably higher in the absence of images for the POS task. These findings suggest that while task complexity strongly shapes user experience in gamified labelling tasks, AI-generated images may not enhance performance or engagement.
Authors
- Chris Madge (ORCID: https://orcid.org/0009-0007-4937-8572)
- Fatima Althani (ORCID: https://orcid.org/0009-0008-9028-8613)
- Massimo Poesio (ORCID: https://orcid.org/0000-0001-8469-2072)
Institutions
- Queen Mary University of London (GB)
Publication Details
- Published
- 2025-08-19
- DOI
- https://doi.org/10.1109/cog64752.2025.11114114
- Primary Topic
- Augmented Reality Applications
- Type
- article
- Field-Weighted Citation Impact
- 0.00