This quasi-experimental study aimed to investigate the effect of task repetition under four conditions on the three dimensions of oral production (accuracy, complexity and fluency) and grammatical knowledge gain of learners of English as a Foreign Language (EFL). 40 young learners of English as a Foreign Language in four classes were randomly assigned into one of the following groups: repetitio...

Grammatical error detection and automated essay scoring are two tasks in the area of automated assessment. Traditionally these tasks have been treated independently with different machine learning models and features used for each task. In this paper, we develop a multi-task neural network model that jointly optimises for both tasks, and in particular we show that neural automated essay scoring...

This paper describes our system in the Chinese Grammatical Error Diagnosis (CGED) task for learning Chinese as a Foreign Language (CFL). Our work adopts a hybrid model by integrating rulebased method and n-gram statistical method to detect Chinese grammatical errors, identify the error type and point out the position of error in the input sentences. Tri-gram is applied to disorder mistake. And ...

This paper presents the IJCNLP 2017 shared task for Chinese grammatical error diagnosis (CGED) which seeks to identify grammatical error types and their range of occurrence within sentences written by learners of Chinese as foreign language. We describe the task definition, data preparation, performance metrics, and evaluation results. Of the 13 teams registered for this shared task, 5 teams de...

This paper presents the NLP-TEA 2016 shared task for Chinese grammatical error diagnosis which seeks to identify grammatical error types and their range of occurrence within sentences written by learners of Chinese as foreign language. We describe the task definition, data preparation, performance metrics, and evaluation results. Of the 15 teams registered for this shared task, 9 teams develope...

To date, most work in grammatical error correction has focused on targeting specific error types. We present a probe study into whether we can use round-trip translations obtained from Google Translate via 8 different pivot languages for whole-sentence grammatical error correction. We develop a novel alignment algorithm for combining multiple round-trip translations into a lattice using the TER...

English as a Second Language (ESL) learners’ writings contain various grammatical errors. Previous research on automatic error correction for ESL learners’ grammatical errors deals with restricted types of learners’ errors. Some types of errors can be corrected by rules using heuristics, while others are difficult to correct without statistical models using native corpora and/or learner corpora...

In recent studies, pre-trained models and pseudo data have been key factors in improving the performance of English grammatical error correction (GEC) task. However, few studies examined role Chinese GEC Therefore, we develop based on three models: BERT, T5, BART, then incorporate these with to determine best configuration for On natural language processing computing (NLPCC) 2018 shared task te...

Researchers feel it is important to conduct research on grammatical errors in students, based mistakes made by students when speaking. In addition, previous relevant research, there are still gaps. This study aims analyze the types of that occur English education program STKIP Yapis Dompu. The method used this qualitative with a descriptive case approach. results indicate four encountered speak...