Cross linguistic cognitive load estimation via hierarchical attention in English translation education
Xiaoyan Dong · 2026
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Description
Xiaoyan Dong proposes a computer framework to estimate mental load in translation students in a 2026 study. Cognitive load is a hidden state that cannot be read off single words, so the method builds proxy scores from human measures. Those inputs include workload ratings, eye tracking, pupil size, keystroke logs, timing, and translation quality.
Three modules handle limits, time segments, and output uncertainty, letting the model follow word, segment, and whole text levels at once. The task is framed as continuous prediction rather than fixed classes. Tests span English to Chinese, Japanese, and Spanish data sets, with checks across new learners and new languages against several rival model types.
Catalog record
| CREATOR | Xiaoyan Dong |
|---|---|
| YEAR | 2026 |
| COLLECTION | PAPERS |
| FORMAT | TXT |
| FILE SIZE | 94103 |
| LICENSE | https://creativecommons.org/licenses/by/4.0 |
| RIGHTS | CC BY |
| SOURCE | Europe PMC |