眼球运动
可读性
眼动
操作化
扫视
固定(群体遗传学)
计算机科学
阅读(过程)
认知心理学
心理学
自然语言处理
语言学
可预测性
感知
人工智能
文本处理
统计
数学
人口
哲学
人口学
认识论
神经科学
社会学
程序设计语言
作者
Xiaopeng Zhang,Nan Gong
标识
DOI:10.1017/s0272263123000438
摘要
Abstract This study examined how linguistic complexity features contribute to second language (L2) processing effort by analyzing the Dutch English-L2 learners’ eye movements from GECO and MECO, two eye-tracking corpora. Processing effort was operationalized as reading rate, mean fixation duration, regression rate, skipping rate, and mean saccade amplitude. In Study 1, the lexical, syntactic, and discoursal indices in 272 snippets of a novel in GECO were regressed against these eye-movement measures. The results showed that the one-component partial least square regression (PLS-R) models could explain 11%–37% of the variance in these eye-movement measures and outperformed eight readability formulas (six traditional and two recent cognitively inspired formulas based on the readers’ perception on text difficulty) in predicting L2 processing effort. In Study 2, the eye-tracking data from MECO were used to evaluate whether the findings from Study 1 could be applied more broadly. The results revealed that although the predictability of these PLS-R components decreased, they still performed better than the readability formulas. These findings suggest that the linguistic indices identified can be used to predict L2 text processing effort and provide useful implications for developing systems to assess text difficulty for L2 learners.
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