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使用优化的迈克网模拟器对阅读中的个体差异进行建模:阅读教学的影响。

Modelling individual differences in reading using an optimised MikeNet simulator: the impact of reading instruction.

作者信息

Chang Ya-Ning, Chang Ting-Jung, Lin Wei-Fen, Kuo Ching-En, Shi Yu-Ting, Lee Hung-Wei

机构信息

Miin Wu School of Computing, National Cheng Kung University, Tainan, Taiwan.

Department of Computer Science, National Yang-Ming Chiao-Tung University, Hsinchu, Taiwan.

出版信息

Front Hum Neurosci. 2024 Jun 21;18:1356483. doi: 10.3389/fnhum.2024.1356483. eCollection 2024.

DOI:10.3389/fnhum.2024.1356483
PMID:38974479
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC11224532/
Abstract

Reading is vital for acquiring knowledge and studies have demonstrated that phonology-focused interventions generally yield greater improvements than meaning-focused interventions in English among children with reading disabilities. However, the effectiveness of reading instruction can vary among individuals. Among the various factors that impact reading skills like reading exposure and oral language skills, reading instruction is critical in facilitating children's development into skilled readers; it can significantly influence reading strategies, and contribute to individual differences in reading. To investigate this assumption, we developed a computational model of reading with an optimised MikeNet simulator. In keeping with educational practices, the model underwent training with three different instructional methods: phonology-focused training, meaning-focused training, and phonology-meaning balanced training. We used semantic reliance (SR), a measure of the relative reliance on print-to-sound and print-to-meaning mappings under the different training conditions in the model, as an indicator of individual differences in reading. The simulation results demonstrated a direct link between SR levels and the type of reading instruction. Additionally, the SR scores were able to predict model performance in reading-aloud tasks: higher SR scores were correlated with increased phonological errors and reduced phonological activation. These findings are consistent with data from both behavioral and neuroimaging studies and offer insights into the impact of instructional methods on reading behaviors, while revealing individual differences in reading and the importance of integrating OP and OS instruction approaches for beginning readers.

摘要

阅读对于获取知识至关重要,研究表明,对于有阅读障碍的儿童,以语音为重点的干预措施通常比以意义为重点的干预措施在英语学习中能带来更大的进步。然而,阅读教学的效果因人而异。在影响阅读技能的各种因素中,如阅读量和口语技能,阅读教学对于促进儿童成长为熟练读者至关重要;它能显著影响阅读策略,并导致阅读方面的个体差异。为了研究这一假设,我们使用优化后的MikeNet模拟器开发了一个阅读计算模型。按照教育实践,该模型采用三种不同的教学方法进行训练:以语音为重点的训练、以意义为重点的训练以及语音 - 意义平衡训练。我们使用语义依赖(SR),即在模型的不同训练条件下对从印刷到声音和从印刷到意义映射的相对依赖程度的一种度量,作为阅读中个体差异的指标。模拟结果表明了SR水平与阅读教学类型之间的直接联系。此外,SR分数能够预测大声朗读任务中的模型表现:较高的SR分数与语音错误增加和语音激活减少相关。这些发现与行为研究和神经影像学研究的数据一致,为教学方法对阅读行为的影响提供了见解,同时揭示了阅读中的个体差异以及将语音教学(OP)和语义教学(OS)方法整合对于初学者的重要性。

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Front Hum Neurosci. 2024 Jun 21;18:1356483. doi: 10.3389/fnhum.2024.1356483. eCollection 2024.
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本文引用的文献

1
The influence of oral vocabulary knowledge on individual differences in a computational model of reading.口语词汇知识对阅读计算模型中个体差异的影响。
Sci Rep. 2023 Jan 30;13(1):1680. doi: 10.1038/s41598-023-28559-3.
2
How you read affects what you gain: Individual differences in the functional organization of the reading system predict intervention gains in children with reading disabilities.你阅读的方式会影响你所获得的东西:阅读系统功能组织的个体差异预示着阅读障碍儿童干预效果的差异。
J Educ Psychol. 2022 May;114(4):855-869. doi: 10.1037/edu0000672. Epub 2021 Sep 23.
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A unified neurocomputational bilateral model of spoken language production in healthy participants and recovery in poststroke aphasia.
健康受试者口语产生的统一神经计算双边模型和中风后失语症的恢复。
Proc Natl Acad Sci U S A. 2020 Dec 22;117(51):32779-32790. doi: 10.1073/pnas.2010193117. Epub 2020 Dec 3.
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The relationships between oral language and reading instruction: Evidence from a computational model of reading.口语和阅读教学之间的关系:来自阅读计算模型的证据。
Cogn Psychol. 2020 Dec;123:101336. doi: 10.1016/j.cogpsych.2020.101336. Epub 2020 Aug 18.
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Individual differences in learning the regularities between orthography, phonology and semantics predict early reading skills.在学习正字法、音系学和语义学之间的规律方面的个体差异预示着早期阅读技能。
J Mem Lang. 2020 Oct;114. doi: 10.1016/j.jml.2020.104145. Epub 2020 Jun 7.
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Understanding Dyslexia Through Personalized Large-Scale Computational Models.通过个性化的大规模计算模型理解阅读障碍
Psychol Sci. 2019 Mar;30(3):386-395. doi: 10.1177/0956797618823540. Epub 2019 Feb 7.
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Ending the Reading Wars: Reading Acquisition From Novice to Expert.终结阅读之争:新手到专家的阅读习得。
Psychol Sci Public Interest. 2018 Jun;19(1):5-51. doi: 10.1177/1529100618772271.
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The place of morphology in learning to read in English.形态学在英语阅读学习中的地位。
Cortex. 2019 Jul;116:45-54. doi: 10.1016/j.cortex.2018.02.008. Epub 2018 Feb 24.
9
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J Exp Psychol Gen. 2017 Jun;146(6):826-858. doi: 10.1037/xge0000301. Epub 2017 Apr 20.
10
Reading through the life span: Individual differences in psycholinguistic effects.贯穿一生的阅读:心理语言学效应中的个体差异。
J Exp Psychol Learn Mem Cogn. 2017 Aug;43(8):1298-1338. doi: 10.1037/xlm0000366. Epub 2017 Mar 20.