Source record

Published by Interacting with Computers (Oxford Academic) (T1.5 source). The original is at https://academic.oup.com/iwc/article/38/3/352/7629774?rss=1.

Pipeline notes

The summary and note below are generated by the signal pipeline — they are Beyond Desk’s reading, not quotations from the source.

Academic study testing how presentation sequence (by label, by image, random) in ML data labeling tasks affects 176 crowd workers' perceived variety, autonomy, motivation, and performance under self-determination theory. Counterintuitively, by-label sorting was perceived as more varied than random sequencing.

Counters the assumption that randomization boosts variety in labeling work. Useful design lever for anyone structuring human-in-the-loop dataset pipelines.

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