ISSN 1671-3710
CN 11-4766/R
主办:中国科学院心理研究所
出版:科学出版社

心理科学进展 ›› 2024, Vol. 32 ›› Issue (1): 100-117.doi: 10.3724/SP.J.1042.2024.00100

• 研究前沿 • 上一篇    下一篇

阅读研究中常用眼动控制模型的对比分析

陈松林, 陈新炜, 李璜夏, 药盼盼()   

  1. 北京语言大学心理学院, 北京 100083
  • 收稿日期:2023-04-06 出版日期:2024-01-15 发布日期:2023-10-25
  • 通讯作者: 药盼盼 E-mail:yaopp@blcu.edu.cn
  • 基金资助:
    北京市社会科学基金青年项目(22YYC016);北京语言大学校级项目(中央高校基本科研业务费专项资金)(21YBB33);北京语言大学一流学科团队支持计划(2023YGF07);北京语言大学院级项目(中央高校基本科研业务费专项资金)(22YJ250001);北京语言大学研究生创新基金(中央高校基本科研业务费专项资金)(23YCX106)

Comparison of models of eye movement in reading

CHEN Songlin, CHEN Xinwei, LI Huangxia, YAO Panpan()   

  1. School of Psychology, Beijing Language and Culture University, Beijing 100083, China
  • Received:2023-04-06 Online:2024-01-15 Published:2023-10-25
  • Contact: YAO Panpan E-mail:yaopp@blcu.edu.cn

摘要:

建立于序列加工理论、平行加工理论和交互激活理论, 一些经典的眼动控制模型对阅读过程中常见的眼动行为、实验效应及其背后可能的信息加工认知机制进行了模拟和探究。阅读研究中的5种经典眼动控制模型——E-Z Reader 10th、SWIFT、Glenmore、OB1 Reader和CRM, 在模型结构、模型基本逻辑、解释常见眼动行为、解释常见实验效应上存在相似性亦有独特性。基于对上述模型的对比分析, 未来模型需要考察词汇后整合的问题、语序的问题、语言外因素的问题, 可尝试对偏好注视位置的最新实证研究结果进行一定程度的解释, 建立模型对比的统一标准, 探索各个模型的跨语言解释力。

关键词: E-Z Reader, SWIFT, Glenmore, OB1 Reader, CRM, 眼动控制

Abstract:

Based on sequential processing theory, parallel processing theory and interactive activation theory, some classic models about eye movement control are constructed to simulate the eye movements, experimental effects, and to explore the possible cognitive mechanisms of information processing during reading. A systematic and in-depth comparative analysis of five classic models (E-Z Reader 10th, SWIFT, Glenmore, OB1 Reader and CRM) was made in this paper. Specifically, the similarities and differences among these models were analyzed and discussed.

There are similarities among the five models: visual acuity and word frequency are all considered to influence the recognition of letters/ Chinese characters and words; common eye movement patterns including fixation, regression and saccade are all simulated; typical experimental effects such as word frequency, word length, word prediction, and preview effects are well explained.

The core difference of the five models is whether the distribution of attention in the perceptual span is sequential or parallel, and this difference evoked significant consequences on the five models. First, different claims were made regarding letter/Chinese character recognition and word recognition. The sequential attention shift (SAS) models claimed that multiple words cannot be processed simultaneously, while the parallel graded processing (PG) models raised the opposite argument. Second, different interpretations of common eye movement patterns were made. For example, the SAS models claimed that regressions are derived from post-lexical integration, while the PG models argued that regressions come from lexical recognition. Third, different explanations for some typical effects were made. For example, the SAS models argued that readers cannot obtain semantic meanings from preview, and there is no parafoveal on foveal effect, while the PG models made the opposite argument. Forth, each model can explain some specific effects that other models cannot. For example, based on the special feature of Chinese script (the lack of word boundary demarcation), CRM raised a reasonable explanation for the word segmentation and preferred viewing location in Chinese reading; E-Z Reader simulated some effects of post-lexical integration which were not considered in other models; SWIFT, Glenmore, and OB1 all discussed the effects of extralinguistic factors which were not included in other models.

For the future development of eye movement control models, researchers may need to take the following aspects into consideration. First, post-lexical integration needs to be considered and simulated. Semantic integration plays an important role in reading. But only E-Z Reader contained a module of post-lexical integration and simulated the possible mechanism of semantic integration. More attentions should be laid on the semantic integration procedure for further model development. Second, the word order coding in reading should be considered. Compared to the SAS models which provided a relatively intuitive answer to word order coding, the PG models require a clear answer to this question. OB1 Reader tried to solve this problem by adding a spatiotopic representation module, which however is not suitable for Chinese reading due to the specific features of Chinese. Further studies need to focus on understanding how word order is coded in Chinese reading under the framework of parallel processing. Third, some extralinguistic factors need to be considered. Now, SWIFT, Glenmore, and OB1 Reader discussed the influences of reader specificity or task difficulty in eye movement patterns in reading. In the future, more extralinguistic factors such as age, gender, intelligence, attention and language proficiency level should be considered to make the model more interpretable. Forth, general standards to compare the suitability of models should be made. Each model simulated specific experimental effects based on their corresponding empirical data, which makes it difficult to compare different models quantitatively and directly. Future studies should try to build a unified large-scale database for the convenience of comparing the explanatory power of different models for the same effect. Last, the possibility of cross-language explanations should be explored. Each of the existing models was based on a specific language. In future studies, researchers may try to explore whether the models based on a specific language can be applied to other languages.

Key words: E-Z Reader, SWIFT, Glenmore, OB1 Reader, CRM, eye movement control

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