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专家预告(五)| 中西学者语言认知科学前沿百家讲坛(第三期)——语言习得与认知神经科学交叉论坛

时间:2024-10-17 阅读次数:

“语言习得与认知神经科学交叉论坛”即将开始。

这里将迎来一场盛大的思想盛宴。

这里将汇聚来自世界各地的杰出学者,分享最前沿的研究成果。

在这场学术盛会的前夕,我们满怀期待地邀请您一同见证知识的火花如何照亮我们对语言理解的探索之路。


赵杨教授

北京大学博雅特聘教授、对外汉语学院院长

主要研究领域:

第二语言习得、生成语法、社会语言学和语言教育

报告题目:

Between the Lines: Comparing GAI and Human Writing in Chinese Narrative Texts

报告摘要:

This study investigates the writing quality and linguistic features of Chinese narratives authored by Chinese as a second language learners (L2 learners), native speakers (NS), and Generated Artificial Intelligence (GAI). Automated analysis of lexical, syntactic, and cohesion features suggest that GAI narratives closely mirror those of NS in basic vocabulary but align more with L2 learners in advanced vocabulary use and that at the syntactic level, GAI exhibits near-native competence. In terms of cohesion, however, GAI’s performance is more similar to that of L2 learners and shows considerable disparity from that of NS. The results suggest that GAI can generate texts that approximate or exceed the proficiency level of current L2 learners, making it a potentially valuable tool for L2 Chinese teaching. Nonetheless, GAI is not without flaws and sometimes under performs compared to L2 learners in certain areas,highlighting the need for careful consideration of how GAI can be optimized forL2 instruction.


王瑞明教授

华南师范大学心理学院教授,博导,副院长、国家高层次青年人才

主要研究领域:

学习心理研究

报告题目:

书写产生中的笔尖效应

报告摘要:

书写产生是将思想转化为书面文字的过程。相比口语产生,书写产生在心理语言学领域的研究相对较少。随着数字设备的广泛使用,书写困难的现象引起了研究者的关注。我们在一项大型汉字书写数据库研究中,发现被试报告了一种“理解要写什么,但忘了怎么写”的书写困难现象。我们将其命名为“笔尖效应”(Tip-of-the-Pen, TOP)。我们进一步的将笔尖效应跟提笔忘字(Character amnesia)进行了区分,提笔忘字泛指书写困难的一般现象,内涵更广,而笔尖效应属于提笔忘字现象的特殊表现,即书写者暂时不能提取出自己确切知道的字的字形。我们的研究还发现,笔尖效应的影响因素既包括频率、字形以及语音等与目标字相关的词汇学因素,也包括书写者日常打字频率、日常书写频率以及阅读量等个体差异因素。我们还对笔尖效应产生的认知机制进行了一定的探讨。未来研究应基于书写产生的心理认知过程,进一步探讨笔尖效应的产生阶段和发生机制,进一步从时间进程和相关脑区揭示其神经基础,深入拓展笔尖效应的影响因素,并推进笔尖效应的干预研究


张金桥教授

暨南大学中国语言与文化学院教授、博士生导师,暨南大学应用语言学研究所所长,中国心理学会学习心理学专业委员会常务委员、中国英汉比较学会心理语言学专业委员会委员、《心理探索》编委会委员

主要研究领域:

心理语言学跨学科研究,汉语阅读心理学、汉语词汇与句子习得、实验语用学。

报告题目:

A Study of Contextual Effects on the Interpretation of Discourse Meaning for Chinese Learners

报告摘要:

This article established a classification system for context based on the theory of discourse meaning and context research, providing a theoretical framework for the experimental study of the context effect. Based on this classification system, cognitive psychology behavioral techniques and cognitive neuroscience technologies, primarily ERP technology,were employed to conduct 8 experiments in 4 studies to investigate the contextual effects on discourse meaning comprehension among intermediate to advanced-level Chinese learners under conditions of intra-sentential  context,contextual context, situational context, and encyclopedic knowledge context. A preliminary cognitive model of discourse meaning comprehension by Chinese learners was proposed based on these experimental results.


Anna Ivanova助理教授

乔治亚理工学院心理学助理教授,语言、智能与思维实验室负责人

主要研究领域:

人类和大型语言模型中的语言-思维关系

报告题目:

Dissociating Language and Thought in Humans and in Machines

报告摘要:

What is the relationship between language and thought? This question has long intrigued researchers across scientific fields. In this talk, I will propose a framework for clarifying the language-thought relationship. I will introduce a distinction between formal competence—knowledge of linguistic rules and patterns—and functional competence—understanding and using language in the world. This distinction is grounded in human neuroscience, where a wealth of evidence indicates that formal competence relies on a set of specialized brain regions (“the language network”), whereas functional competence requires the use of multiple non-language-specific neural systems. I will then present a series of case studies illustrating how the formal/functional competence distinction can help (a) delineate the functional architecture of the human brain, providing a framework for studying complex cognitive behaviors, such as computer coding and legal reasoning; (b) understand the capabilities and limitations of today’s large language models, particularly in the realm of general world knowledge.



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