Design of intelligent English writing self-evaluation auxiliary system

Man Liu

doi:10.31449/inf.v43i2.2783

Abstract

Since the reform and opening up, the exchanges between China and the world have become more and more frequent. English, as a widely used international language, plays an important role in international exchanges. English teaching includes five aspects, listening, speaking, reading, writing and translation. Writing teaching is very important but difficult. In order to improve students' autonomous writing ability, this paper briefly introduced the real-time multi-writing teaching mode and designed an automatic scoring algorithm of writing self-evaluation auxiliary system, random sampling based Bayesian classification and combinational algorithm. One thousand CET-4 and CET-6 compositions from Chinese Learner English Corpus (CLEC) were evaluated, and the scoring effect of Bayesian classification algorithm was also tested. The results showed that the accuracy rate, recall rate and F value of the proposed algorithm was better than that of Bayesian classification algorithm under 150 feature extraction dimensions, the two algorithms had improved scoring effect under the optimal feature extraction dimensions, and the improvement amplitude of the algorithm proposed in this study was larger. In summary, the random sampling based Bayesian classification and combinational algorithm is effective and feasible as an automatic scoring algorithm of writing self-evaluation auxiliary system.

Highlights

As the economic globalization deepens, the communication between China and other countries is more and more frequent, and the most frequently used language is English
The automatic scoring effect of the writing self-evaluation system was evaluated in the aspects of accuracy rate, recall rate and F value [15]
Based on the binary phrase features, the compositions which involved four themes were scored under 150 feature extraction dimensions, i.e., the 1000 compositions were classified into four score grades using the algorithm proposed in this study

Summary

Introduction

As the economic globalization deepens, the communication between China and other countries is more and more frequent, and the most frequently used language is English. English writing ability can be improved through a large number of writing exercises and comments of teachers. If students lack guidance about writing exercises, the improvement effect will be greatly reduced. Despite the fact that the writing language is changeable and the effect is not ideal in practice, it is still of great help to lighten the burden on teachers and improve students' English writing level. Li [4] selected two parallel classes as the object, one was taught by the traditional business English writing teaching mode and the other was guided by computer assisted technology. The teaching quality was evaluated after one academic term, and it was found that computer assisted technology had positive effect on business English writing. The questionnaire result suggested that most of the students had positive learning result, indicating the teaching mode could improve the effectiveness of English writing learning. The scoring effect of the Bayesian classification algorithm was tested and compared with the automatic scoring algorithm

Methods

Results

Conclusion