A Corpus-based Analysis of Collocations in Korean Middle and High School English Textbooks

Kim, Young S.; Oh, Sun-Young

doi:10.30961/lr.2020.56.3.437

Cited by 3 publications

(10 citation statements)

References 33 publications

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“…Overall, the collocations of all subtypes in the textbooks are more repetitive than their counterparts in the reference corpus. The result is conflicting with previous studies which have shown that textbooks present insufficient repetition of target words or collocations (Kim, 2020;Koya, 2004;Tsai, 2015;Yu & Renandya, 2021). It is noticed that NNCs are recycled to a greater extent than VNCs and ANCs in the textbook corpus (24.71 for VNCs, 25.08 for ANCs, and 14.56 for NNCs).…”

Section: Repetition Ratecontrasting

confidence: 69%

“…Frankenberg-Garcia et al (2018) found that a threshold of logDice score greater than or equal to 5 works well for identifying lexical collocations. The logDice with a minimum score of 5 is therefore used in this study (Frankenberg-Garcia et al, 2018;Kim, 2020). And the minimum frequency of occurrence for a word combination to be taken to be a collocation was set at 5.…”

Section: Statistical Criteriamentioning

confidence: 99%

“…Secondly, collocation diversity is used to measure the number of collocation types in the target corpus. To minimize the corpus size effect, the formula "collocation diversity = the number of collocation types/the square root of word tokens" was used (Kim, 2020).…”

Section: Distributional Measuresmentioning

confidence: 99%

“…To identify collocations, the present study adopted the approach used by Tsai (2015) and Kim (2020). A reference collocation list was first generated from the native reference corpus and used to identify collocations in the textbook corpus.…”

Section: Collocation Identification In Target Corporamentioning

confidence: 99%

“…It indicates the degree to which the same collocation types are repeated in an inverse way. In other words, a higher RTTR score indicates less repetition of the collocation types found in a corpus, while a lower RTTR score means more recurrences of the same collocation types (Kim, 2020).…”

Section: Repetition Ratementioning

confidence: 99%

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A Corpus-based Analysis on Distributional Patterns of Collocations in Chinese High School English Textbooks

2022

CURTM

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The paper explores the distributional patterns of collocations identified in Chinese high school textbooks in comparison with collocations found in the native reference corpus. Six series of Chinese high school English textbooks from the six publishers were compiled as the textbook corpus. The British National Corpus (BNC) was selected as the native norm. Three collocation types, adjective + noun collocation (ANC), verb + noun collocation (VNC) and noun + noun collocation (NNC), were investigated in the paper. The distribution of the collocations was compared between the two corpora in terms of four statistical measures: density, diversity, repetition and association strength. The results showed that whereas the diversity of collocations was higher in the native reference corpus than in the textbook corpus, the other measures showed the opposite pattern. This may partly be due to the pedagogical nature of the textbooks. Moreover, the findings revealed that the textbooks represent a comparable number of VNCs, overrepresent ANCs and under-represent NNCs in comparison with the native reference corpus. The findings suggest that textbook authors take account of incorporating more diverse collocations and more NNCs to model more native-like texts in the teaching materials targeting higher-grade students.

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Section: Repetition Ratecontrasting

confidence: 69%

Section: Statistical Criteriamentioning

confidence: 99%

Section: Distributional Measuresmentioning

confidence: 99%

Section: Collocation Identification In Target Corporamentioning

confidence: 99%

Section: Repetition Ratementioning

confidence: 99%

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A Corpus-based Analysis on Distributional Patterns of Collocations in Chinese High School English Textbooks

2022

CURTM

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Input optimization: Verb-argument constructions in English textbooks in Türkiye

Gedik¹

2023

FELT

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Based on usage-based approaches to second language acquisition, studies point at a statistically significant correlation between type-token frequency, skewed distribution of items, and faster learning. Madlener (2016) shows a positive correlation between a Zipfian distribution of items in a German construction and faster, more accurate learning of the construction. While there are many studies that analyze input in English language teaching materials, no study has scrutinized selected constructions from an input optimization perspective, following Madlener (2016). Thus, using TAASSC (Kyle, 2016), the present paper analyzes four constructions, V in N, V about N, V for N, V with N, and the ditransitive constructions in the high school English textbooks in Türkiye. The results indicate that the input available for these constructions are not viable for generalizations to occur, leaving learners with unproductive one-time instantiations of the constructions, and low token frequency of these constructions also suggest that little to no entrenchment might take place. As such, the study proposes adopting a more corpus-based approach to English teaching materials.

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A Corpus-Based Analysis of Lexical Collocation in Conversation Texts of English Textbooks

Intamanjana,

Sada

2024

JEFLE

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This study revealed the analysis of lexical collocation in conversation texts of curriculum-based English textbook entitled “Bahasa Inggris” for tenth- grade students. In the textbook, it was found that there were 46 lexical collocations of VN, AdjN, NN, AdvAdj, and VAdv combination. Five out of seven types of lexical collocation combinations were presents in the conversation texts. The MI (Mutual Information) score of the collocation combinations were mostly above 3.00 which considered ‘strong collocation’. Semantically, the collocations were dominated by ‘free combination’ followed by ‘restricted collocation’ then figurative idiom’. The result also showed the lack of repetition of collocation combination in the conversation texts. Moreover, there was an absence of ‘pure idioms’ as one of the part that construct a conversationKey Words: conversation, corpus, lexical collocation

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A Corpus-based Analysis of Collocations in Korean Middle and High School English Textbooks

Cited by 3 publications

References 33 publications

A Corpus-based Analysis on Distributional Patterns of Collocations in Chinese High School English Textbooks

A Corpus-based Analysis on Distributional Patterns of Collocations in Chinese High School English Textbooks

Input optimization: Verb-argument constructions in English textbooks in Türkiye

A Corpus-Based Analysis of Lexical Collocation in Conversation Texts of English Textbooks

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