Research to date lends general support to the claim that language learning strategies impact positively on language learning,especially where foreign language learning is concerned.To share the highlight in this field...Research to date lends general support to the claim that language learning strategies impact positively on language learning,especially where foreign language learning is concerned.To share the highlight in this field,this empirical study was mainly designed to explore Chinese university students' memory strategy use in their English learning.The results show that the university students reported using a number of memory strategies flexibly in their English learning and that three out of the four subcategories of memory strategies were correlated with the students' English scores.展开更多
Spark,a distributed computing platform,has rapidly developed in the field of big data.Its in-memory computing feature reduces disk read overhead and shortens data processing time,making it have broad application prosp...Spark,a distributed computing platform,has rapidly developed in the field of big data.Its in-memory computing feature reduces disk read overhead and shortens data processing time,making it have broad application prospects in large-scale computing applications such as machine learning and image processing.However,the performance of the Spark platform still needs to be improved.When a large number of tasks are processed simultaneously,Spark’s cache replacementmechanismcannot identify high-value data partitions,resulting inmemory resources not being fully utilized and affecting the performance of the Spark platform.To address the problem that Spark’s default cache replacement algorithm cannot accurately evaluate high-value data partitions,firstly the weight influence factors of data partitions are modeled and evaluated.Then,based on this weighted model,a cache replacement algorithm based on dynamic weighted data value is proposed,which takes into account hit rate and data difference.Better integration and usage strategies are implemented based on LRU(LeastRecentlyUsed).Theweight update algorithm updates the weight value when the data partition information changes,accurately measuring the importance of the partition in the current job;the cache removal algorithm clears partitions without useful values in the cache to releasememory resources;the weight replacement algorithm combines partition weights and partition information to replace RDD partitions when memory remaining space is insufficient.Finally,by setting up a Spark cluster environment,the algorithm proposed in this paper is experimentally verified.Experiments have shown that this algorithmcan effectively improve cache hit rate,enhance the performance of the platform,and reduce job execution time by 7.61%compared to existing improved algorithms.展开更多
This paper reviews the theory of language attrition,which refers to the loss or degradation of second language skills due to lack of using the second language for a certain period of time.Although our country attaches...This paper reviews the theory of language attrition,which refers to the loss or degradation of second language skills due to lack of using the second language for a certain period of time.Although our country attaches great importance to English language teaching,most of college English majors use English far less frequently than that of Chinese in real life,which makes them easily influenced by language attrition.Therefore,it is of great significance for college English majors to improve the efficiency of English vocabulary memory from the perspective of language attrition combined with Forgetting.This thesis consists of three parts.Chapter one is an analysis the concept of language attrition and Forgetting.Chapter two describes and analyzes the existing problems in current vocabulary memory among the college English majors via a questionnaire survey.The final chapter puts forward some corresponding countermeasures to help college English majors get rid of the influence of language attrition on vocabulary learning.展开更多
English speaking skill is one of the most important skills that senior high students need to obtain in learning English.However,there are still many problems existing in students’speaking practice.As a teaching and l...English speaking skill is one of the most important skills that senior high students need to obtain in learning English.However,there are still many problems existing in students’speaking practice.As a teaching and learning strategy,Chunking is now gradually used in English classroom and has received a positive feedback.Therefore,in this paper,the influence of Chunking on improving English speaking skill among senior high school students will be investigated and analyzed through the methods of questionnaire and the follow-up interview to answer four questions:(1)What effect does Chunking have on the oral fluency of high school students?(2)What effect does Chunking have on the oral accuracy of high school students?(3)What effect does Chunking have on the vocabulary?And(4)Does the English speaking performance relate to genders?After analyzing the results of questionnaire by the SPSS and summing up the interview record,we found that most of them agree the fact that the strategy of Chunking does benefit their oral fluency,oral accuracy,and vocabulary.Also,female students have higher scores than male students.展开更多
文摘Research to date lends general support to the claim that language learning strategies impact positively on language learning,especially where foreign language learning is concerned.To share the highlight in this field,this empirical study was mainly designed to explore Chinese university students' memory strategy use in their English learning.The results show that the university students reported using a number of memory strategies flexibly in their English learning and that three out of the four subcategories of memory strategies were correlated with the students' English scores.
基金the National Natural Science Foundation of China(61872284)Key Research and Development Program of Shaanxi(2023-YBGY-203,2023-YBGY-021)+3 种基金Industrialization Project of Shaanxi ProvincialDepartment of Education(21JC017)“Thirteenth Five-Year”National Key R&D Program Project(Project Number:2019YFD1100901)Natural Science Foundation of Shannxi Province,China(2021JLM-16,2023-JC-YB-825)Key R&D Plan of Xianyang City(L2023-ZDYF-QYCX-021)。
文摘Spark,a distributed computing platform,has rapidly developed in the field of big data.Its in-memory computing feature reduces disk read overhead and shortens data processing time,making it have broad application prospects in large-scale computing applications such as machine learning and image processing.However,the performance of the Spark platform still needs to be improved.When a large number of tasks are processed simultaneously,Spark’s cache replacementmechanismcannot identify high-value data partitions,resulting inmemory resources not being fully utilized and affecting the performance of the Spark platform.To address the problem that Spark’s default cache replacement algorithm cannot accurately evaluate high-value data partitions,firstly the weight influence factors of data partitions are modeled and evaluated.Then,based on this weighted model,a cache replacement algorithm based on dynamic weighted data value is proposed,which takes into account hit rate and data difference.Better integration and usage strategies are implemented based on LRU(LeastRecentlyUsed).Theweight update algorithm updates the weight value when the data partition information changes,accurately measuring the importance of the partition in the current job;the cache removal algorithm clears partitions without useful values in the cache to releasememory resources;the weight replacement algorithm combines partition weights and partition information to replace RDD partitions when memory remaining space is insufficient.Finally,by setting up a Spark cluster environment,the algorithm proposed in this paper is experimentally verified.Experiments have shown that this algorithmcan effectively improve cache hit rate,enhance the performance of the platform,and reduce job execution time by 7.61%compared to existing improved algorithms.
文摘This paper reviews the theory of language attrition,which refers to the loss or degradation of second language skills due to lack of using the second language for a certain period of time.Although our country attaches great importance to English language teaching,most of college English majors use English far less frequently than that of Chinese in real life,which makes them easily influenced by language attrition.Therefore,it is of great significance for college English majors to improve the efficiency of English vocabulary memory from the perspective of language attrition combined with Forgetting.This thesis consists of three parts.Chapter one is an analysis the concept of language attrition and Forgetting.Chapter two describes and analyzes the existing problems in current vocabulary memory among the college English majors via a questionnaire survey.The final chapter puts forward some corresponding countermeasures to help college English majors get rid of the influence of language attrition on vocabulary learning.
文摘English speaking skill is one of the most important skills that senior high students need to obtain in learning English.However,there are still many problems existing in students’speaking practice.As a teaching and learning strategy,Chunking is now gradually used in English classroom and has received a positive feedback.Therefore,in this paper,the influence of Chunking on improving English speaking skill among senior high school students will be investigated and analyzed through the methods of questionnaire and the follow-up interview to answer four questions:(1)What effect does Chunking have on the oral fluency of high school students?(2)What effect does Chunking have on the oral accuracy of high school students?(3)What effect does Chunking have on the vocabulary?And(4)Does the English speaking performance relate to genders?After analyzing the results of questionnaire by the SPSS and summing up the interview record,we found that most of them agree the fact that the strategy of Chunking does benefit their oral fluency,oral accuracy,and vocabulary.Also,female students have higher scores than male students.