Card Sorting with Fewer Cards and the Same Mental Models? A Re-examination of an Established Practice
September 03, 2025 Β· Declared Dead Β· π International Journal of Human-Computer Interaction
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Authors
Eduard Kuric, Peter Demcak, Matus Krajcovic
arXiv ID
2509.03232
Category
cs.HC: Human-Computer Interaction
Citations
0
Venue
International Journal of Human-Computer Interaction
Last Checked
5 months ago
Abstract
To keep card sorting with a lot of cards concise, a common strategy for gauging mental models involves presenting participants with fewer randomly selected cards instead of the full set. This is a decades-old practice, but its effects lacked systematic examination. To assess how randomized subsets affect data, we conducted an experiment with 160 participants. We compared results between full and randomized 60\% card sets, then analyzed sample size requirements and the impacts of individual personality and cognitive factors. Our results demonstrate that randomized subsets can yield comparable similarity matrices to standard card sorting, but thematic patterns in categories can differ. Increased data variability also warrants larger sample sizes (25-35 for 60% card subset). Results indicate that personality traits and cognitive reflection interact with card sorting. Our research suggests evidence-based practices for conducting card sorting while exposing the influence of study design and individual differences on measurement of mental models.
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