English Writing Feedback Based on Online Automatic Evaluation in the Era of Big Data

Abstract

Under the influence of the continuous development of modern information technology, the online automatic evaluation system for English writing teaching was born in response to demand. The rise of the online automatic assessment and correction system has broken through the limitations of the campus, making English writing teaching no longer restricted by time and space. Adapting to the needs of English writing development in the era of big data, making full use of modern information technology to improve writing effect, further promoting the development of educational informatization and the transformation of writing teaching, and realizing the mutual blending and innovative development of education and information technology have become the inevitable trend of future development. This paper applies the combination of teacher feedback and automatic feedback to the teaching of English writing in senior high school and discusses whether the combination of the two can change the disadvantages of the automatic writing evaluation system and solve the problem of traditional single teacher evaluation. In this paper, the text feedback system is introduced into the context information, and the context information is used to filter the difference between the active context and the active context, so as to further reduce the number of participants in collaborative filtering and improve the real-time computing efficiency of the algorithm. By distinguishing dynamic text quality indicators from stable text quality indicators, this paper proposes a similar context-aware neighborhood model. Based on experimental analysis, the accuracy of feedback results is 45.2% higher than that of the original online automatic evaluation system.

Bibliometrically and systematically analyzing automated writing evaluation for English learning

“…The accuracy of combined automated teacher feedback was 45.2% higher than AWE feedback alone (J. Li, 2022). Besides, the combined feedback had more strengths in reducing grammar and mechanics errors (T. Han and Sari, 2022).…”

An Automated English Essay Scoring Engine Based on Neutrosophic Ontology for Electronic Education Systems

“…These methods instead combined NLP-based algorithms, statistics, probabilities, and other data sources such as corpora to arrive at a more accurate approximation of a student's score. Semantic similarity research was widely implemented in essay grading [27][28][29]. However, they require a massive annotation effort in terms of cost, time, and expertise.…”

Retracted: English Writing Feedback Based on Online Automatic Evaluation in the Era of Big Data

“…Tis article has been retracted by Hindawi following an investigation undertaken by the publisher [1]. Tis investigation has uncovered evidence of one or more of the following indicators of systematic manipulation of the publication process:…”