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【每日电子书】Defining and Assessing Lexical Proficiency等2本电子书

919 阅读 125 下载 2020-07-14 13:34:00 上传 3.34 MB

【每日电子书】由LingLab和“语言学小电”倾力打造的全新版块,每日会推出数量不等的电子书讯,网罗国际顶级出版社、涵盖语言学各领域分支,海量资源,新鲜速递,任您挑选!详情可添加“语言学小电”的微信13764179404进行咨询!


Defining and Assessing Lexical Proficiency等2本电子书


张明辉(微信zhangxiaojian160408)


今日推出2本电子书资源:


①Routledge出版社2020年重磅新著Defining and Assessing Lexical Proficiency

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②Routledge2014年前沿专著Using Statistics in Small-Scale Language Education Research: Focus on Non-Parametric Data

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【书名】:Defining and Assessing Lexical Proficiency

【作者】:Agnieszka Leńko-Szymańska

【年份】:2020

【出版社】:Routledge出版社

【简介】:劳特利奇应用语言学研究书系的最新专著,关于词汇能力的一本书!

This comprehensive account of performance-based assessment of L2 lexical proficiency analyzes and compares two of the primary methods of evaluation used in the field and unpacks the ways in which they tap into different dimensions of one model of lexical competence and proficiency.

 

This book builds on the latest research on performance-based assessment, which has most recently pointed to the application of more quantitative measures to L2 data, to systematically explore the qualitative method of using human raters in assessment exercises and the quantitative method of using automatic computation of statistical measures of lexis and phraseology. Supported by an up-to-date review of the existing literature, both approaches’ unique features are highlighted but also compared to one another to provide a holistic overview of performance-based assessment as it stands today at both the theoretical and empirical level. These findings are exemplified in a concluding chapter, which summarizes results from an empirical study looking at a range of lexical and phraseological features and human raters’ scores of over 150 essays written by both L2 learners of English and native speakers. Taken together, the volume challenges existing tendencies within the field which attempt to use one method to validate one another by demonstrating their capacity to indicate very different elements of lexical proficiency, thereby offering a means by which to better conceptualize performance-based assessment of L2 vocabulary in the future.

 

This book will be of interest to students and researchers working in second language acquisition and applied linguistics research, particularly those interested in issues around assessment, vocabulary acquisition, and language proficiency.

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【书名】:Using Statistics in Small-Scale Language Education Research: Focus on Non-Parametric Data

【作者】:Jean L. Turner

【年份】:2014

【出版社】:Routledge出版社

【简介】:Assuming no familiarity with statistical methods, this text for language education research methods and statistics courses provides detailed guidance and instruction on principles of designing, conducting, interpreting, reading, and evaluating statistical research done in classroom settings or with a small number of participants. While three different types of statistics are addressed (descriptive, parametric, non-parametric) the emphasis is on non-parametric statistics because they are appropriate when the number of participants is small and the conditions for use of parametric statistics are not satisfied. The emphasis on non-parametric statistics is unique and complements the growing interest among second and foreign language educators in doing statistical research in classrooms. Designed to help students and other language education researchers to identify and use analyses that are appropriate for their studies, taking into account the number of participants and the shape of the data distribution, the text includes sample studies to illustrate the important points in each chapter and exercises to promote understanding of the concepts and the development of practical research skills. Mathematical operations are explained in detail, and step-by-step illustrations in the use of R (a very powerful, online, freeware program) to perform all calculations are provided.

 

A Companion Website extends and enhances the text with PowerPoint presentations illustrating how to carry out calculations and use R; practice exercises with answer keys; data sets in Excel MS-DOS format; and quiz, midterm, and final problems with answer keys.

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