{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,6,17]],"date-time":"2026-06-17T14:52:26Z","timestamp":1781707946159,"version":"3.54.5"},"reference-count":19,"publisher":"Frontiers Media SA","license":[{"start":{"date-parts":[[2026,6,17]],"date-time":"2026-06-17T00:00:00Z","timestamp":1781654400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":["frontiersin.org"],"crossmark-restriction":true},"short-container-title":["Front. Psychol."],"abstract":"<jats:sec>\n                    <jats:title>Introduction<\/jats:title>\n                    <jats:p>Estimating cognitive load in English translation education is important for understanding learners' processing difficulty and supporting adaptive instructional decisions. However, cognitive load is a latent psychological construct and cannot be treated as a directly observed token level label. To address this issue, this study proposes a cross linguistic cognitive load estimation framework based on hierarchical attention and probabilistic modeling.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Methods<\/jats:title>\n                    <jats:p>Cognitive load proxy scores are constructed from human derived translation process measurements, including subjective workload ratings, eye tracking, pupillometry, keystroke logs, timing records, and translation performance indicators. The proposed Hierarchical Cognitive Load Estimator integrates three modules: a Variational Constraint Optimizer, an Attention guided Temporal Segmenter, and an Uncertainty aware Output Regularizer. These modules enable the model to capture token , segment , and document level dependencies, represent latent learner and task specific factors, and estimate predictive uncertainty. The task is formulated as continuous probabilistic regression rather than categorical classification. Experiments are conducted on translation process datasets covering English-Chinese, English-Japanese, and English-Spanish settings, with standard, cross subject, and cross language evaluation protocols. The proposed model is compared with feature based regression, neural sequence models, structured state space models, hierarchical attention baselines, and probabilistic uncertainty baselines.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Results and discussion<\/jats:title>\n                    <jats:p>Results show that the proposed framework improves regression performance, probabilistic fit, and uncertainty calibration. Additional ablation, sensitivity, interpretability, and educator facing analyzes indicate that the model's predictions align with known difficulty indicators and can support instructional diagnosis, learner feedback, curriculum adjustment, and adaptive intervention in translation education.<\/jats:p>\n                  <\/jats:sec>","DOI":"10.3389\/fpsyg.2026.1771134","type":"journal-article","created":{"date-parts":[[2026,6,17]],"date-time":"2026-06-17T13:56:34Z","timestamp":1781704594000},"update-policy":"https:\/\/doi.org\/10.3389\/crossmark-policy","source":"Crossref","is-referenced-by-count":0,"title":["Cross linguistic cognitive load estimation via hierarchical attention in English translation education"],"prefix":"10.3389","volume":"17","author":[{"given":"Xiaoyan","family":"Dong","sequence":"first","affiliation":[{"name":"Yancheng Institute of Technology","place":["Yancheng, Jiangsu, China"]}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1965","published-online":{"date-parts":[[2026,6,17]]},"reference":[{"key":"B1","doi-asserted-by":"publisher","DOI":"10.1002\/9781119241485.ch29","article-title":"\u201cEvolution, challenges, and perspectives for research on cognitive aspects of translation,\u201d","author":"Alves","year":"2017","journal-title":"The Handbook of Translation and Cognition"},{"key":"B2","doi-asserted-by":"publisher","DOI":"10.4324\/9781315178127","author":"Alves","year":"2021","journal-title":"The Routledge Handbook of Translation and Cognition"},{"key":"B3","doi-asserted-by":"crossref","unstructured":"Carl\n              M.\n            \n          \n          10.63317\/4yt2527b3dza\n          Translog-ii: A program for recording user activity data for empirical translation process research\n          \n          2012","DOI":"10.63317\/4yt2527b3dza"},{"key":"B4","doi-asserted-by":"publisher","first-page":"952","DOI":"10.7202\/1011262ar","article-title":"Gazing and typing activities during translation: a comparative study of translation units of professional and student translators","volume":"56","author":"Carl","year":"2011","journal-title":"Meta"},{"key":"B5","doi-asserted-by":"publisher","first-page":"49","DOI":"10.1075\/target.17.1.04dra","article-title":"Segmentation in translation: differences across levels of expertise and difficulty","volume":"17","author":"Dragsted","year":"2005","journal-title":"Target. 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