Anderson's Cognitive Theory and Learning Strategy Studies in Second Language Acquisition

Second language acquisition can not be understood without addressing the interaction between language and cognition. Cognitive theory can extend to describe learning strategies as complex cognitive skills. Theoretical developments in Anderson’s production systems cover a broader range of behavior than other theories, including comprehension and production of oral and written texts as well as comprehension, problem solving, and verbal learning.Thus Anderson’s cognitive theory can be served as a rationale for learning strategy studies in second language acquisition.

象似性研究新进展——Language and Cognition杂志2019—2020专刊述评

基于剑桥大学出版社出版的认知语言学权威期刊Language and Cognition所刊发的10篇象似性论文,本文深度描写、分析并展望象似性研究的国际前沿现状,并对该辑专刊进行述评。结果发现,近年来国外象似性研究主要集中于象似性理论的跨学科研究、手语语言学及其应用与实践等领域。上述发现不但有助于揭示语言与认知的关系,而且对于国内学者把握国际象似性研究的最新进展具有一定的参考意义。

An Intervention Study of Language Cognition and Emotional Speech Community Method for Children’s Speech Disorders

Speech disorders are a common type of childhood disease.Through experimental intervention,this study aims to improve the vocabulary comprehension levels and language ability of children with speech disorders through the language cognition and emotional speech community method.We also conduct a statistical analysis of the inter-ventional effect.Among children with speech disorders in Dongguan City,224 were selected and grouped accord-ing to their receptive language ability and IQ.The 112 children in the experimental group(EG)received speech therapy with language cognitive and emotional speech community,while the 112 children in the control group(CG)only received conventional treatment.After six months of experimental intervention,the Peabody Picture Vocabulary Test-Revised(PPVT-R)was used to test the language ability of the two groups.Overall,we employed a quantitative approach to obtain numerical values,examine the variables identified,and test hypotheses.Further-more,we used descriptive statistics to explore the research questions related to the study and statistically describe the overall distribution of the demographic variables.The statistical t-test was used to analyze the data.The data shows that after intervention through language cognition and emotional speech community therapy,the PPVT-R score of the EG was significantly higher than that of the CG.Therefore,we conclude that there is a significant difference in language ability between the EG and CG after the therapy.Although both groups improved,the post-therapy language level of EG is significantly higher than that of CG.The total effective rate in EG is higher than CG,and the difference is statistically significant(p<0.05).Therefore,we conclude that the language cogni-tion and emotional speech community method is effective as an interventional treatment of children’s speech dis-orders and that it is more effective than traditional treatment methods.

Mixed Method in Language Learner Cognition

Research on mixed method has made great development.In order to explore the practical application of mixed method,this article starts from the perspective of language learner cognition and selects The Modern Language Journal and Language Teaching Research as the research journals.It explores some empirical papers that used mixed method to learn the specific research designs of mixed method as well as the main means of its application.The study finds that mixed method has been applied in several fields and is more scientifically reliable than qualitative and quantitative methods especially in language learner cognition,and the different research tools used in the field of language learner cognition demonstrate the flexibility and relevance of mixed method data collection.

Text Difficulty Study:Do Machines Behave the Same as Humans Regarding Text Difficulty?

With the emergence of pre-trained models,current neural networks are able to give task performance that is comparable to humans.However,we know little about the fundamental working mechanism of pre-trained models in which we do not know how they approach such performance and how the task is solved by the model.For example,given a task,human learns from easy to hard,whereas the model learns randomly.Undeniably,difficulty-insensitive learning leads to great success in natural language processing(NLP),but little attention has been paid to the effect of text difficulty in NLP.We propose a human learning matching index(HLM Index)to investigate the effect of text difficulty.Experiment results show:1)LSTM gives more human-like learning behavior than BERT.Additionally,UID-SuperLinear gives the best evaluation of text difficulty among four text difficulty criteria.Among nine tasks,some tasks’performance is related to text difficulty,whereas others are not.2)Model trained on easy data performs best in both easy and medium test data,whereas trained on hard data only performs well on hard test data.3)Train the model from easy to hard,leading to quicker convergence.