Søby Katrine Falcon, Ishkhanyan Byurakn, Kristensen Line Burholt
Department of Nordic Studies and Linguistics, University of Copenhagen, Copenhagen, Denmark.
Front Psychol. 2023 Jul 13;14:1124227. doi: 10.3389/fpsyg.2023.1124227. eCollection 2023.
Grammar errors are a natural part of everyday written communication. They are not a uniform group, but vary from morphological errors to ungrammatical word order and involve different types of word classes. In this study, we examine whether some types of naturally occurring errors attract more attention than others during reading, measured by detection rates. Data from 211 Danish high school students were included in the analysis. They each read texts containing different types of errors: syntactic errors (verb-third word order), morphological agreement errors (verb conjugations; gender mismatches in NPs) and orthographic errors. Participants were asked to underline all errors they detected while reading for comprehension. We examined whether there was a link between the type of errors that participants did not detect, the type of errors which they produce themselves (as measured in a subsequent grammar quiz), and the type of errors that are typical of high school students in general (based on error rates in a corpus). If an error is infrequent in production, it may cause a larger surprisal effect and be more attended to. For the three subtypes of grammar errors (V3 word order, verb errors, NP errors), corpus error rates predicted detection rates for most conditions. Yet, frequency was not the only possible explanation, as phonological similarity to the correct form is entangled with error frequency. Explicit grammatical awareness also played a role. The more correct answers participants had in the grammar tasks in the quiz, the more errors they detected. Finally, we found that the more annoyed with language errors participants reported to be, the more errors they detected. Our study did not measure eye movements, but the differences in error detection patterns point to shortcomings of existing eye-tracking models. Understanding the factors that govern attention and reaction to everyday grammar errors is crucial to developing robust eye-tracking processing models which can accommodate non-standard variation. Based on our results, we give our recommendations for current and future processing models.
语法错误是日常书面交流中很自然的一部分。它们并非一个统一的类别，而是从形态错误到不合语法的词序各不相同，涉及不同类型的词类。在本研究中，我们通过检测率来考察某些自然出现的错误类型在阅读过程中是否比其他类型更能吸引注意力。分析纳入了来自211名丹麦高中生的数据。他们每人阅读包含不同类型错误的文本：句法错误（动词 - 第三个词序）、形态一致错误（动词变位；名词短语中的性别不匹配）和拼写错误。要求参与者在为理解而阅读时，划出他们检测到的所有错误。我们考察了参与者未检测到的错误类型、他们自己产生的错误类型（在随后的语法测验中测量）以及一般高中生典型的错误类型（基于语料库中的错误率）之间是否存在关联。如果一种错误在产出中不常见，它可能会产生更大的意外效应并更受关注。对于语法错误的三种亚型（V3词序、动词错误、名词短语错误），语料库错误率在大多数情况下预测了检测率。然而，频率并非唯一可能的解释，因为与正确形式的语音相似性与错误频率相互交织。明确的语法意识也起到了作用。参与者在测验中的语法任务中答对的正确答案越多，他们检测到的错误就越多。最后，我们发现参与者报告对语言错误越恼火，他们检测到的错误就越多。我们的研究没有测量眼动，但错误检测模式的差异指出了现有眼动追踪模型的不足之处。了解控制对日常语法错误的注意力和反应的因素对于开发能够适应非标准变体的强大眼动追踪处理模型至关重要。基于我们的结果，我们为当前和未来的处理模型给出了建议。
