Abstract
This study aims to prove the effectiveness of AWE (automated writing evaluation) feedback in English writing with the aid of the online grading system—Pigaiwang. A contrastive teaching experiment was employed with one class as experimental class and another class as control class. The two classes were required to take a pre-test to decide their writing level and a post-test to check their improvement. After a semester’s teaching experiment, the data was collected and analyzed. The results showed that most students in the experimental class held favorable attitude towards using AWE and their writing skills improved a lot by constant revision. However, the students in the control class, who only relied on teacher’ evaluation and feedback, did not improve their writing skills as greatly as students in experimental class because they seldom revised their essay and wrote the second draft. Given the efficiency of AWE feedback for L2 learners, it can be applied to the English writing teaching extensively. Though the online grading system has its advantages in improving students’ writing level, it also has limitations. So, the best choice should be a combination of human feedback and intelligent feedback.
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References
Fang, Y.: Perceptions of the computer-assisted writing program among EFL college. Learn. J. Educ. Technol. Soc. 13(3), 246–256 (2010)
Högemann, J., Cunha, J., et al.: Writing intervention with elementary students struggling with writing: examining approach profiles to the teacher feedback on writing quality and motivational variables. Read. Writ. 92(1), 1–30 (2021)
Elliot, S., Mikulua, C.: The impact of MyAccess! Use on student writing performance: a technology overview and four studies. Paper Presented at the Annual Meeting of the American Educational Research Association, San Diego, C.A (2014)
Ranalli, J.: L2 student engagement with automated feedback on writing: potential for learning and issues of trust. J. Second. Lang. Writ. 52, 40–47 (2021)
Xu, J., Zhang, S.: Understanding AWE feedback and English writing of learners with different proficiency levels in an EFL classroom: a sociocultural perspective. Asia Pac. Educ. Res. 29(3), 1–11 (2021)
Zhang, Z.: Engaging with automated writing evaluation (AWE) feedback on L2 writing: student perceptions and revisions. Assess. Writ. 43(6), 78–85 (2020)
Koh, W.-Y.: Effective applications of automated writing feedback in process-based writing instruction. Engl. Teach. 72(3), 91–118 (2017)
Teresa, M.: Assessment and Feedback in Higher Education: Peer and Collaborative Assessment. UCL Press, pp. 99–177 (2020)
Nigel, F., Craig, N.-J.: Critical Perspectives on the Scholarship of Assessment and Learning in Law. ANU Press (2021)
Warschauer, M., Ware, P.: Automated writing evaluation: Defining the classroom research agenda. Lang. Teach. Res. 10(2), 1–24 (2016)
Chen, N., Rong, B., Zhang, X., Kadoch, M.: Scalable and flexible massive MIMO precoding for 5G H-CRAN. IEEE Wirel. Commun. Mag. 24(1), 46–52 (2017)
Chen, L., Yu, F.R., Ji, H., Rong, B., Li, X., Leung, V.C.M.: Green full-duplex self-backhaul and energy harvesting small cell networks with massive MIMO. IEEE J. Sel. Areas Commun. 34(12), 3709–3724 (2016)
Nessa, A., Kadoch, M., Rong, B.: Fountain coded cooperative communications for LTE-A connected heterogeneous M2M network. IEEE Access 4, 5280–5292 (2016)
Acknowledgements
This work was supported by The Higher Education Reform Project of Jilin Provincial Department of Education and “13th Five-Year Plan” of Education and Science in Jilin Province, 2020 annual (general) project (number: GH20384).
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Zhao, X., Kidston, M. (2022). AWE Feedback on the Effectiveness of the Automatic Scoring System for English Writing. In: Sun, S., Hong, T., Yu, P., Zou, J. (eds) Signal and Information Processing, Networking and Computers. ICSINC 2021. Lecture Notes in Electrical Engineering, vol 895. Springer, Singapore. https://doi.org/10.1007/978-981-19-4775-9_82
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