CLApr 19, 2018

Assessing Language Proficiency from Eye Movements in Reading

arXiv:1804.07329v21098 citations
Originality Incremental advance
AI Analysis

This provides a novel tool for second language proficiency assessment, though it is incremental in applying eye-tracking to a specific domain.

The researchers tackled the problem of assessing second language proficiency by analyzing eye movements during reading, showing that their method correlates strongly with standardized tests and can accurately predict test outcomes.

We present a novel approach for determining learners' second language proficiency which utilizes behavioral traces of eye movements during reading. Our approach provides stand-alone eyetracking based English proficiency scores which reflect the extent to which the learner's gaze patterns in reading are similar to those of native English speakers. We show that our scores correlate strongly with standardized English proficiency tests. We also demonstrate that gaze information can be used to accurately predict the outcomes of such tests. Our approach yields the strongest performance when the test taker is presented with a suite of sentences for which we have eyetracking data from other readers. However, it remains effective even using eyetracking with sentences for which eye movement data have not been previously collected. By deriving proficiency as an automatic byproduct of eye movements during ordinary reading, our approach offers a potentially valuable new tool for second language proficiency assessment. More broadly, our results open the door to future methods for inferring reader characteristics from the behavioral traces of reading.

Foundations

The foundational work for this paper's niche, ranked by how specifically the neighbourhood builds on it — not by global fame.

Your Notes