Automatic essay scoring (AES) is an essential educational application in natural language processing. This automated process will alleviate the burden by increasing the reliability and consistency of the assessment. With the advances in text embedding libraries and neural network models, AES systems achieved good results in terms of accuracy.…

Manually scoring and revising student essays has long been a time-consuming task for educators. With the rise of natural language processing techniques, automated essay scoring (AES) and automated essay revising (AER) have emerged to alleviate this burden. However, current AES and AER models require large amounts of training data and lack…

E-learning systems are transforming the educational sector and making education more affordable and accessible. Recently, many e-learning systems have been equipped with advanced technologies that facilitate the roles of educators and increase the efficiency of teaching and learning. One such technology is Automatic Essay Grading (AEG) or…

This study conducts a comprehensive quantitative evaluation of OpenAI's language model, ChatGPT 4, for grading Task 2 writing of the IELTS exam. The objective is to assess the alignment between ChatGPT's grading and that of official human raters. The analysis encompassed a multifaceted approach, including a comparison of means and reliability…

This study explores using transfer learning in machine learning for natural language processing (NLP) to create generic automated essay scoring (AES) models, providing instant online scoring for statewide writing assessments in K-12 education. The goal is to develop an instant online scorer that is generalizable to any prompt, addressing the…

Whether type of written corrective feedback (WCF) impacts L2 learning has been investigated for decades. While many product-oriented studies report conflicting findings, the paucity of studies adopting both a process-oriented and curricular approach (e.g., Caras, 2019) underscores the call for further research on: (1) the processing dimension of…

The aim of the present study is to examine experimentally the influence of using lexical chunks on the achievement of second-year-university students of English in the writing fluency. Lexical chunks, as the composites of form, meaning and function, stored and retrieved as a whole in brain, can release the language processing burden and improve…

When viewed through a generic, one-size-fits-all perspective, use of input enhancement does not appear effective. Through analysis of individual grammatical features and different learner proficiency levels, a significant impact may be revealed. To study the impact of input enhancement on diverse grammatical features, 16 short reading texts and…

The use of collocation has always been considered as a good yardstick by which the idiomaticity of second language (L2) use is reliably judged. Hence, this study aims at investigating the relationship between optimizing the lexical approach and improving the collocational accuracy and the ability to operate on the idiom principle in the writing of…

To help EFL learners realize the use of nominals and clauses in practicing productive skills of academic writing in English writing tests, experiments have been exploited using the tasks similar to those of internet-based test of English as a foreign language to determine the nominal and clause level information during sentence and paragraph…

Automated scoring by means of Latent Semantic Analysis (LSA) has been introduced lately to improve the traditional human scoring system. The purposes of the present study were to develop a LSA-based assessment system to evaluate children's Chinese sentence construction skills and to examine the effectiveness of LSA-based automated scoring function…

A study was conducted to examine the associations among the processes, skills, and content of the writing of children aged 9 through 14 years. A further objective was to explore the impact of developmetal changes by comparing the performance of children at the 9-10, 11-12, and 13-14 year age-levels. Subjects were 340 average students and 268…

The 7th International Conference on Education Data Mining held on July 4th-7th, 2014, at the Institute of Education, London, UK is the leading international forum for high-quality research that mines large data sets in order to answer educational research questions that shed light on the learning process. These data sets may come from the traces…