The Effects of Integrated Feedback based on AWE on English Writting of Chinese EFL Learners

Authors

  • Mei Liu School of Education Science, Nanjing Normal University, Nanjing Jiangsu 210024, China; School of Education, Linyi University Linyi Shandong 276000, China
  • Changzhong Shao School of Foreign Languages, Linyi University, Linyi Shandong 276000, China

DOI:

https://doi.org/10.12694/scpe.v25i2.2617

Keywords:

integrated feedback, automated writing evaluation, AWE, English writing, Pigai website, English as foreign language, EFL

Abstract

Through a two-semester experiment on the English writing of 64 Chinese EFL learners, this study examines the effects of three types web-based feedback (automatic feedback (AF), automatic feedback with teacher feedback (TF), automatic feedback with peer feedback (PF)) based on Pigai website. The results show that all the three modes of feedback can promote the writing of the English as Foreign Language (EFL) learners with different English proficiency ((high level: F = 2.672, P = .132; low level: F = .388, P = .766). The results also reveal that there is a significant difference in the high-level group between the automatic feedback + peer feedback group and the automatic feedback group (I - J = - 6.636, P = .000) as well as between the automatic feedback + teacher feedback group and the automatic feedback group (I - J = - 6.220, P = .001; I - J = - 5. 100, P =. 001), which indicate that automatic feedback + manual feedback (PF+TF) can promote the improvement of high-level learners’ English writing more than single AF. In the low-level group, between the AF + PF group and the AF group (I - J = -1.221, P = .925) and between the AF +TF group and the AF + PF group (I - J = 6.227, P =. 097). There is no significant difference, but there is a significant difference between the AF group and the AF + TF group (I - J = - 5.122, P =. 032), indicating that AF + TF is of great help in improving the English writing of low-level English learners.

Downloads

Published

2024-02-24

Issue

Section

Special Issue - Scalable Computing in Online and Blended Learning Environments: Challenges and Solutions