SOURCE-LINKED INTELLIGENCE
Language Proficiency Assessment from Eye Movements in Naturalistic Passage Reading
Standard language proficiency tests rely on linguistic tasks such as vocabulary, grammar and reading comprehension quizzes. An alternative, cognitively motivated approach, introduced in Berzak et al. (2018), proposed instead to predict language proficiency from behavioral traces of eye movements in reading. In this work, we validate and extend this approach from single sentences to more naturalistic reading of contextualized passages in English as a second language, new proficiency measures, prediction models, and reading in an information seeking regime. We find that the approach is effective
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Evidence & attribution
- arXiv · AI, language, vision and robotics · 2026-08-31T10:57:39.000Z
First collected: 2026-09-21T07:01:58.596Z. This is not the publication date.