A corpus-based study of morphological productivity of English language chemical engineering textbooks

The effective teaching of word identification requires the acquisition and mastery of specific word identification skills. The aim of this study is to determine the patterns of complex words which, because of the large number of meanings signalled by word derivations, are the foundation for decompo...

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Main Author: Norrihan, Sulan
Format: Thesis
Language:English
Published: 2011
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Online Access:http://umpir.ump.edu.my/id/eprint/2740/1/NORRIHAN_BT_SULAN.PDF
http://umpir.ump.edu.my/id/eprint/2740/
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spelling my.ump.umpir.27402018-05-18T01:45:07Z http://umpir.ump.edu.my/id/eprint/2740/ A corpus-based study of morphological productivity of English language chemical engineering textbooks Norrihan, Sulan P Philology. Linguistics The effective teaching of word identification requires the acquisition and mastery of specific word identification skills. The aim of this study is to determine the patterns of complex words which, because of the large number of meanings signalled by word derivations, are the foundation for decomposition skills. It also aims to develop lexical knowledge of words with complex composition through the study of morphologically productive affixes in chemical engineering textbooks. It seeks to find the most productive morphological categories in the specialized corpus created and to find the density of complex words and their morphological patterns. A corpus of Chemical Engineering Level 1 (CELl) textbooks used at Universiti Malaysia Pahang (UMP), Malaysia was designed to capture a range of linguistic features in actual language use for more effective teaching and learning. This study focuses on theories on word recognition which proposed that reading consists of decoding and linguistic comprehension which are necessary for reading success. Baayen's Morphological Productivity Measurement is used to determine the most productive affixes which will be the base for materials development for teaching and learning processes.The study looks at the frequent patterns of morphologically complex words which might enable language instructors to design reading materials based on actual language use. It was found that 75.57% of the affixed words in the corpus are singleaffixed words while the most complex word has six affixes attached to it. The most frequent prefixes in the corpus are un-, re-, de-,pre- and dis- while for suffixes, the most frequent occurrence are ion-, -ly, -er, -a!, -able/ible. For prefixes attached to technical words, dia-, hydro-, poly-, iso-, and thermo- are found to be the most frequently used. The findings from this study are potentially beneficial for developing ESP materials to meet the linguistic needs of students in engineering and related disciplines. The findings have pedagogical implications for language teaching and learning enabling teaching materials to be produced with the information from the CELl corpus. Teaching materials can be designed using the complex word patterns and presented to allow multiple exposure, thus enhancing word recognition skills. 2011-05 Thesis NonPeerReviewed application/pdf en http://umpir.ump.edu.my/id/eprint/2740/1/NORRIHAN_BT_SULAN.PDF Norrihan, Sulan (2011) A corpus-based study of morphological productivity of English language chemical engineering textbooks. PhD thesis, Universiti Teknologi Mara.
institution Universiti Malaysia Pahang
building UMP Library
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Malaysia Pahang
content_source UMP Institutional Repository
url_provider http://umpir.ump.edu.my/
language English
topic P Philology. Linguistics
spellingShingle P Philology. Linguistics
Norrihan, Sulan
A corpus-based study of morphological productivity of English language chemical engineering textbooks
description The effective teaching of word identification requires the acquisition and mastery of specific word identification skills. The aim of this study is to determine the patterns of complex words which, because of the large number of meanings signalled by word derivations, are the foundation for decomposition skills. It also aims to develop lexical knowledge of words with complex composition through the study of morphologically productive affixes in chemical engineering textbooks. It seeks to find the most productive morphological categories in the specialized corpus created and to find the density of complex words and their morphological patterns. A corpus of Chemical Engineering Level 1 (CELl) textbooks used at Universiti Malaysia Pahang (UMP), Malaysia was designed to capture a range of linguistic features in actual language use for more effective teaching and learning. This study focuses on theories on word recognition which proposed that reading consists of decoding and linguistic comprehension which are necessary for reading success. Baayen's Morphological Productivity Measurement is used to determine the most productive affixes which will be the base for materials development for teaching and learning processes.The study looks at the frequent patterns of morphologically complex words which might enable language instructors to design reading materials based on actual language use. It was found that 75.57% of the affixed words in the corpus are singleaffixed words while the most complex word has six affixes attached to it. The most frequent prefixes in the corpus are un-, re-, de-,pre- and dis- while for suffixes, the most frequent occurrence are ion-, -ly, -er, -a!, -able/ible. For prefixes attached to technical words, dia-, hydro-, poly-, iso-, and thermo- are found to be the most frequently used. The findings from this study are potentially beneficial for developing ESP materials to meet the linguistic needs of students in engineering and related disciplines. The findings have pedagogical implications for language teaching and learning enabling teaching materials to be produced with the information from the CELl corpus. Teaching materials can be designed using the complex word patterns and presented to allow multiple exposure, thus enhancing word recognition skills.
format Thesis
author Norrihan, Sulan
author_facet Norrihan, Sulan
author_sort Norrihan, Sulan
title A corpus-based study of morphological productivity of English language chemical engineering textbooks
title_short A corpus-based study of morphological productivity of English language chemical engineering textbooks
title_full A corpus-based study of morphological productivity of English language chemical engineering textbooks
title_fullStr A corpus-based study of morphological productivity of English language chemical engineering textbooks
title_full_unstemmed A corpus-based study of morphological productivity of English language chemical engineering textbooks
title_sort corpus-based study of morphological productivity of english language chemical engineering textbooks
publishDate 2011
url http://umpir.ump.edu.my/id/eprint/2740/1/NORRIHAN_BT_SULAN.PDF
http://umpir.ump.edu.my/id/eprint/2740/
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