An English Cover Letter Essential Wordlist for Second Language Learners

Writing a cover letter is an essential part of the job application process. To find ways to improve second language learners’ cover letter writing ability, this author examined cover letters to create a list of words that are essential for writing English cover letters. A Cover Letter Essential Word List (CLEWL) of 347 words was created from a corpus of 400 cover letters. The CLEWL was analyzed in terms of its make-up, lexical coverage, and lexical frequency profile. This study presents those findings, as well as suggestions for teaching words from the CLEWL. カバーレターを書くことは就職活動に不可欠な部分である。本論では第2言語学習者のカバーレター作成能力を向上させる方法を見つけるために、英語のカバーレターの文例を調査し、カバーレターを書く上で不可欠な単語リストを作成した。400枚のカバーレターのコーパスから、カバーレターの必須単語リスト（CLEWL）347語を作成し、それを構成、語彙の範囲、および語彙頻度プロファイルの観点から分析した。本論ではその調査結果について述べ、CLEWLの単語を教える方法を提案する。

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Helping Second Language Student Writers Improve Their Revision

Writing across the University of Alberta ◽

10.29173/writingacrossuofa29 ◽

2021 ◽

Vol 2 (1) ◽

pp. 1-6

Author(s):

Wenzhe Kang ◽

Ruiyi Zhang

Keyword(s):

Second Language ◽

Language Learning ◽

Language Learners ◽

Second Language Learners ◽

Comprehensive Evaluation ◽

Native English Speakers ◽

English Speakers ◽

Student Writers ◽

Writing Ability ◽

Language Students

Writing ability is a comprehensive evaluation of language learning level. Nowadays, most universities offer writing-related courses to help students lay a good foundation for writing and contribute to their subsequent studies. Compared with native English speakers, second language learners need to do more revision, which is a great challenge for second language learners. Therefore, in this paper, the aim is to make the second language students understand and apply the revision correctly.

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Using lexical indices to predict produced and not produced words in second language learners

The Mental Lexicon ◽

10.1075/ml.5.1.05cro ◽

2010 ◽

Vol 5 (1) ◽

pp. 115-147 ◽

Cited By ~ 9

Author(s):

Scott Crossley ◽

Tom Salsbury

Keyword(s):

Second Language ◽

Language Learners ◽

Second Language Learners ◽

Native Speakers ◽

Word List ◽

Word Production ◽

Word Knowledge ◽

Lexical Knowledge ◽

Data Set ◽

Discriminant Function Analyses

The paper explores how linguistic indices related to lexical networks and psycholinguistic models of lexical knowledge can be used to predict produced and not produced words in second language (L2) speakers. Two hypotheses are tested in this study. The first addresses how lexical properties thought to be important in word knowledge interrelate with word production. The second addresses which lexical properties are most predictive of word production. To test these hypotheses, a set of 45 frequent nouns and verbs produced by L2 learners were collected. A comparison word list of 45 frequent nouns and verbs produced by native speakers, but not found in the L2 data set were also collected. Polysemy and hypernymy values from the WordNet database along with word meaningfulness, concreteness, familiarity, and imagability values from the MRC Psycholinguistic Database and frequency values from SUBTLEXus were collected for each word. ANOVA analyses of variance and discriminant function analyses were conducted for each data set to examine which lexical indices discriminated between produced and not produced words and how these indices interrelated. The results of the noun analysis indicate that produced nouns are more frequent, more meaningful, and more familiar than not produced nouns. Results from the verb analysis show that produced verbs are more frequent, more meaningful, less specific, and more familiar than not produced verbs. These findings provide evidence for the importance of word properties in lexical production.

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A Hard Science Spoken Word List

ITL - International Journal of Applied Linguistics ◽

10.1075/itl.00006.dan ◽

2018 ◽

Vol 169 (1) ◽

pp. 44-71 ◽

Cited By ~ 5

Author(s):

Thi Ngoc Yen Dang

Keyword(s):

Second Language ◽

Language Learners ◽

Second Language Learners ◽

Word List ◽

Spoken Word ◽

Hard Science ◽

Word Families

Abstract A Hard Science Spoken Word List (HSWL) was developed and validated to help second language learners of hard sciences better comprehend academic speech at English-medium universities. It consists of the 1,595 most frequent and wide ranging word families in a 6.5-million running word hard science spoken corpus which represents 12 subjects across two equally-sized sub-corpora. Its coverage in different discourse types indicates that the HSWL truly reflects the language in hard science academic speech. The comparison between the HSWL with Dang, Coxhead, and Webb’s (2017) Academic Spoken Word List shows that the HSWL focuses more on specialized vocabulary in hard science speech. Depending on their vocabulary levels, learners may achieve 93%–96% coverage of hard science academic speech with knowledge of the HSWL words.

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