Abstract

This study aims at exploring comparative linguistic variation across Pakistani and Chinese learners’ English argumentative essays using a multidimensional analysis (MDA) approach. This study uses a quantitative approach to describing co-occurring linguistic features. The corpus comprising 400 Pakistani and Chinese learners’ essays used in this study has been electronically derived from an online source, ICNALE. The representative corpus has been tagged and analysed through MAT tagger. This study addresses how the language of Pakistani and Chinese learners vary comparatively linguistically; it also explores their linguistic characterization which distinguishes their variety through their co-occurring linguistic features using MD analysis by utilizing five dimensions. The study is restricted to only two countries i.e., Pakistan and China, and the size of the data is considerably more restricted to one sub-register of essay writing, namely, argumentative essays. The results indicate that the language of Pakistani learners’ essays is informational but Chinese learners’ essays are involved in dimension 1 Chinese learners’ essays are narrative whereas Pakistanis learners’ essays are non-narrative on dimension 2. Dimension 3 specifies that Pakistani learners’ essay writings implement that the text is independent of context and contains significant nominalizations while Chinese learners’ essay writings are context-dependent in nature. Dimension 4 indicates that Chinese learners’ essay writings are more explicit and persuasive specifying extensive use of modal verbs than Pakistani learners’ writings. The nature of Chinese learners’ essays is abstract, formal, and technical while Pakistani learners’ essays are non-abstract, objective, and natural on Dimension 5. This study has shed light on how learners acquire new words and expressions from reading different texts that identify various lexical grammatical aspects writers employ and serve as the fundamental source of variety in their language. The categories of dimensions are developed based on particular linguistic features that are over- or under-utilized by assessing the statistical data.

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