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

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 signaled by word derivations, are the foundation for decomposi...

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Main Author:	Sulan, Norrihan
Format:	Thesis
Language:	English
Published:	2011
Subjects:	Morphology Malaysia
Online Access:	http://ir.uitm.edu.my/id/eprint/14942/ http://ir.uitm.edu.my/id/eprint/14942/1/TP_NORRIHAN%20SULAN%20ED%2011_5.PDF

id	uitm-14942
recordtype	eprints
spelling	uitm-149422016-10-13T04:32:14Z http://ir.uitm.edu.my/id/eprint/14942/ A corpus-based study of morphological productivity of English language chemical engineering textbooks / Norrihan Sulan Sulan, Norrihan Morphology Malaysia 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 signaled 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 (CEL1) 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 single affixed 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, -al, -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 CEL1 corpus. Teaching materials can be designed using the complex word patterns and presented to allow multiple exposure, thus enhancing word recognition skills. 2011 Thesis NonPeerReviewed text en http://ir.uitm.edu.my/id/eprint/14942/1/TP_NORRIHAN%20SULAN%20ED%2011_5.PDF Sulan, Norrihan (2011) A corpus-based study of morphological productivity of English language chemical engineering textbooks / Norrihan Sulan. PhD thesis, Universiti Teknologi MARA.
repository_type	Digital Repository
institution_category	Local University
institution	Universiti Teknologi MARA
building	UiTM Institutional Repository
collection	Online Access
language	English
topic	Morphology Malaysia
spellingShingle	Morphology Malaysia Sulan, Norrihan A corpus-based study of morphological productivity of English language chemical engineering textbooks / Norrihan Sulan
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 signaled 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 (CEL1) 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 single affixed 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, -al, -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 CEL1 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	Sulan, Norrihan
author_facet	Sulan, Norrihan
author_sort	Sulan, Norrihan
title	A corpus-based study of morphological productivity of English language chemical engineering textbooks / Norrihan Sulan
title_short	A corpus-based study of morphological productivity of English language chemical engineering textbooks / Norrihan Sulan
title_full	A corpus-based study of morphological productivity of English language chemical engineering textbooks / Norrihan Sulan
title_fullStr	A corpus-based study of morphological productivity of English language chemical engineering textbooks / Norrihan Sulan
title_full_unstemmed	A corpus-based study of morphological productivity of English language chemical engineering textbooks / Norrihan Sulan
title_sort	corpus-based study of morphological productivity of english language chemical engineering textbooks / norrihan sulan
publishDate	2011
url	http://ir.uitm.edu.my/id/eprint/14942/ http://ir.uitm.edu.my/id/eprint/14942/1/TP_NORRIHAN%20SULAN%20ED%2011_5.PDF
first_indexed	2023-09-18T22:52:45Z
last_indexed	2023-09-18T22:52:45Z
_version_	1777417653583872000

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

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