C. Sutarsyah
FKIP Lampung University

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Vocabulary Constraint on Texts C. Sutarsyah
TEFLIN Journal: A publication on the teaching and learning of English Vol 19, No 2 (2008)
Publisher : TEFLIN

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Abstract

This case study was carried out in the English Education Department of State University of Malang. The aim of the study was to identify and describe the vocabulary in the reading text and to seek if the text is useful for reading skill development. A descriptive qualitative design was applied to obtain the data. For this purpose, some available computer programs were used to find the description of vocabulary in the texts. It was found that the 20 texts containing 7,945 words are dominated by low frequency words which account for 16.97% of the words in the texts. The high frequency words occurring in the texts were dominated by function words. In the case of word levels, it was found that the texts have very limited number of words from GSL (General Service List of English Words) (West, 1953). The proportion of the first 1,000 words of GSL only accounts for 44.6%. The data also show that the texts contain too large proportion of words which are not in the three levels (the first 2,000 and UWL). These words account for 26.44% of the running words in the texts.  It is believed that the constraints are due to the selection of the texts which are made of a series of short-unrelated texts. This kind of text is subject to the accumulation of low frequency words especially those of content words and limited of words from GSL. It could also defeat the development of students reading skills and vocabulary enrichment.
The Functions of The Word “get” in Texts C. Sutarsyah
TEFLIN Journal: A publication on the teaching and learning of English Vol 10, No 1 (1999)
Publisher : TEFLIN

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This study investigates the functions of the word ‘get and its use in real communication. The main purposes of this study are to find some patterns and collocation of ‘get in texts, to find their proportion and to discuss the implication of the study for the teaching of English as a foreign language. For this purpose, a number of data from News Bro (Brown corpus), one of the corpora in the computer, was taken as the main data to be analysed and classified. In order to be more accurate, some other data from News Lob (Lob Corpus) were also taken for comparison. Computer software was used to analyse the data in the form of collocations. The result shows that a number of verb patterns of “get” occur more frequently than the others. It also shows that some patterns that are mentioned in the Dictionary do not occur in the data. The result can help teachers of English prepare their teaching material.