The Practical Use of Syntactic Error Analysis of Pronoun Mistakes in L2 Writing

One of the toughest challenges facing EFL/ESL instructors is that learners find it difficult to translate what they learn in grammar class into their own writing.Moreover,they make the same mistakes repeatedly after being corrected.In order to improve students’writing,grammatical awareness is essential.Therefore,teachers should raise the students’level of awareness of syntactic patterns and transformations of the language(Koffi,2010).In this way,teachers are not merely giving the students answers directly,but are actually showing them how to solve these syntactic puzzles by themselves.The purpose of this paper is to analyze frequently made pronoun mistakes in College ESL students’writings to offer insights into how to use pronouns accurately and to enhance learners’writing skills.This paper will look closely at a set of writings done mostly by Somali ESL students in the hope of developing some pedagogical suggestions for teaching pronouns.Frequently made pronoun mistakes will be discussed with examples from students’writing samples.

An Empirical Study for Building a Common Reference Scale of Cando statements of Syntactical Analysis Ability

This study conducts an empirical study of building a common reference scale of Can-do statements of Syntactical AnalysisAbility for NMEE.Studying on language proficiency scale has been done a lot at abroad,but we haven't had a unified English languageproficiency scale in China until now.Without a common reference standard,this leads to many descriptive problems:such as differentdescriptive indexes,vague definition,unclear level and so on.As an important part of English comprehensive ability,syntactical analy-sis ability processes a large proportion of NMEE.Theoretically Based on Bachman's(Communicative Language Ability,CLA) and Dengjie's Discourse Information Cognitive Processing Ability,this study finds that syntactical analysis ability can be described from 38 per-spectives.

University Learning and Anti-Plagiarism Back-End Services

Plagiarism refers to the use of other people’s ideas and information without acknowledging the source.In this research,anti-plagiarism software was designed especially for the university and its campuses to identify plagiarized text in students’written assignments and laboratory reports.The proposed framework collected original documents to identify plagiarized text using natural language processing.Our research proposes a method to detect plagiarism by applying the core concept of text,which is semantic associations of words and their syntactic composition.Information on the browser was obtained through Request application programming interface by name Url.AbsoluteUri,and it is stored in a centralized Microsoft database Server.A total of 55,001 data samples were collected from 2015 to 2019.Furthermore,we assimilated data from a university website,specifically from the psau.edu.sa network,and arranged the data into students’categories.Furthermore,we extracted words from source documents and student documents using the WordNet library.On a benchmark dataset consisting of 785 plagiarized text and 4,716 original text data,a significant accuracy of 90.2%was achieved.Therefore,the proposed framework demonstrated better performance than the other available tools.Many students mentioned that working on assignments using the framework was suitable because they were able to work on the assignments in harmony,as per their timeframe and from different network locations.The framework also recommends procedures that can be used to avoid plagiarism.