dc.contributor.author |
Myall, Joseph |
en |
dc.date.accessioned |
2015-06-16T10:43:17Z |
|
dc.date.available |
2015-06-16T10:43:17Z |
|
dc.date.issued |
2014-03 |
|
dc.identifier.uri |
http://repository.seinan-gu.ac.jp/handle/123456789/1025 |
|
dc.description.abstract |
Whereas the listening section of the TOEIC listening test includes conversations on where to go for dinner or what happened last weekend, the reading section focusses entirely on business, careers and finance. This is to the student’s advantage in that the type of vocabulary appearing in each test can be predicted relatively easily. Thus aware, the student is faced with the task of fi nding sources of suitablevocabulary input and assimilating it. This short paper is an attempt to address the question of how best to go about that task. A common complaint among students taking the TOEIC test is the lack of time available for the reading section. One way to increase reading speed would be to make students more familiar with common collocations and chunks, so that they become less reliant on the painstaking process of reading word-by-word. As Lewis says: “Firstly, words are not normally used alone and it makes sense to learn them in a strong, frequent, or otherwise typical pattern of actual use. Secondly, it is more effi cient to learn the whole and break it into parts, than to learn the parts and have to learn the whole as an extra arbitrary item.” ( p.37, 7-11) |
ja |
dc.language.iso |
eng |
ja |
dc.publisher |
西南学院大学言語教育センター |
ja |
dc.title |
Towards a Rational Corpus-Based Approach to Vocabulary Acquisition in Preparation for the TOEIC Test Reading Section |
en |
dc.contributor.transcription |
マイオール, ジョセフ |
ja |
dc.publisher.alternative |
Seinan Gakuin University Center for Language Education |
ja |
dc.type.niitype |
Departmental Bulletin Paper |
ja |
dc.identifier.jtitle |
西南学院大学言語教育センター紀要 |
ja |
dc.identifier.volume |
4 |
ja |
dc.identifier.spage |
37 |
ja |
dc.identifier.epage |
40 |
ja |
dc.textversion |
publisher |
ja |
jpcoar.creatorAffiliation.nameIdentifierKakenhi |
37105 |
|