Key points are not available for this paper at this time.
Automated Written Evaluation (AWE) not only provides feedback on grammar and machine language in China today, but also aims to find inconsistencies and text errors and provide timely feedback and correction for independent and comprehensive writing tasks in these areas. It has provided services to more than 1400 universities and research institutions nationwide. Considering the effectiveness and significance of its problem-solving, the study has read a large number of professors’ research literature and reviewed it. AWE has gradually become an auxiliary teaching method. Many literatures have proven their help to second language writing, but there are also a few problems and shortcomings. Only by combining various kinds of feedback (teacher feedback and AWE feedback; AWE feedback and peer feedback) can the paper effectively reverse the feedback effect of AWE. In addition, not only the advantages of AWE itself affect the correctness of learners’ second language, but also the differences in the cognition and application of AWE between teachers and students will affect the effectiveness of AWE.
Gao et al. (Thu,) studied this question.
Synapse has enriched 5 closely related papers on similar clinical questions. Consider them for comparative context: