XJTLU Graduate School

1. Metadiscourse Use in L2 Student Essay Writing: A Longitudinal Cross-Contextual Comparison

Author:Ruan, ZL


Abstract:This paper investigates developmental patterns of metadiscourse use in Chinese students' EAP writing in an English medium university, in comparison with English majors' EFL writing in mainstream state universities and L1 student writing in UK universities. Taking a longitudinal and cross-contextual perspective, the study explores corpora of L1 and L2 student writing gathered from three sources: EAP essays written by Chinese undergraduate students at an English Medium Instruction (EMI) university; argumentative essays written by English majors in the Written English Corpus of Chinese Learners (WECCL); and academic essays of English L1 students from the British Academic Written English (BAWE) corpus. Hyland's (2005a) model of metadiscourse was adopted to identify interactive and interactional devices in each corpus, and results were compared between different levels as well as across the corpora to reveal developmental features. Findings show marked differences in metadiscourse use between Chinese EMI students' EAP essays and English major students' EFL essays in mainstream state universities, whereas a similar pattern of use occurred in EAP essays and English L1 student academic essays. Significant changes were also found between different year levels in two L2 essay corpora. The findings suggest that metadiscourse use in L2 writing had developmental trajectories distinctive to different institutional contexts, with EAP instruction in the EMI institution having mixed effects on Chinese students' awareness and use of metadiscourse in essay writing.
2. Application of time series method to the passenger flow prediction in the intelligent bus transportation system with big data


Source:Smart Innovation, Systems and Technologies,2021,Vol.176

Abstract:© Springer Nature Singapore Pte Ltd 2021. Based on the real data collected from the bus IC card payment devices, first a time series plot on the daily passenger volume was obtained and then three kinds of time series models were proposed to do the prediction. The results show that the ARMA model with quadratic trend is the most suitable to the current data and performs the most effectively in the prediction.
Total 2 results found
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