Abstract
This corpus-based comparative study was about morphemic derivational patterns in grammatical categories: adjective, noun and verbs in different varieties: English as native language (ENL), English as second language (ESL), and English as foreign language (EFL). This study was done on data collected from ICNALE in which learners’ data from three different varieties of English was compared. The data was tagged through CLAWS tagger and analyzed through AntConc software. In result of analysis, the frequency-based differences in the morphemic derivational patterns were observed after normalizing the data. Such differences across varieties in morphemic patterns were realized through the existence and absence of derivational morphemes. The results showed that the native speakers have higher ability of using a greater number of morphemic patterns than second and foreign language speakers of English. Due to their native like competence, they are more competent is the usage of morphemic derivational patterns. Those distinctive patterns should also be taken as pedagogical implication for second and foreign language learners of English. It can also be helpful for second and foreign language learners in achieving native like ability to use English language.
Highlights
This is a comparative study about the patterns, variations in the use, and frequency of derivational morphemes across three varieties of English: English as native language (ENL), English as second language (ESL) and English as foreign language (EFL)
This corpus-based comparative study was about morphemic derivational patterns in grammatical categories: adjective, noun and verbs in different varieties: English as native language (ENL), English as second language (ESL), and English as foreign language (EFL)
I will report the frequencies of derivational morphemes making three grammatical categories in three varieties of English language
Summary
This is a comparative study about the patterns, variations in the use, and frequency of derivational morphemes across three varieties of English: ENL, ESL and EFL. The data from these varieties are taken for the study. ENL represents the native data, ESL represents second language users which includes Pakistani portion of ICNALE, and EFL represents foreign language users which constitutes Chinese portion. Antconc is the software used for the analysis of tagged corpus. Corpus is tagged through CLAWS tagger that is an online Parts of Speech (POS) tagger. The data were taken from ICNALE that is online available for research purpose
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