DeepSeek' s Feedback on Short Essay-Writing in EFL: Pre-service Primary School Teachers' Perceptions

Abstract

[EN] Over the past few years, there has been a growing use of generative Artificial Intelligence (AI) tools to support the development of writing skills among language learners. However, limited attention has been given to the potential of AI in pre-service teacher (PST) education, and specifically, the tool DeepSeek has yet to be examined. This study, therefore, aims to investigate PSTs perceptions of the usefulness of DeepSeek's feedback on the production of a text following a task-based teaching intervention. Thirty-nine primary education pre-service teachers took part, they were first-year students from a Spanish university whose English proficiency ranged from A2 to B2. The task required them to write a short essay. Data were collected using a pre- and post-test with open-ended questions adapted from Di Sarno-García and Argüelles-Álvarez (in press), along with a focus group discussion, thus adopting a mixed-methods approach that triangulates quantitative and qualitative data. The results of the Wilcoxon signed-rank test indicated a statistically significant decline in some items, as well as a slight decrease in mean scores from pre- to post-test which are aligned with the participants contributions from the open-ended questionnaire and focus group. These findings suggest that DeepSeek may not have been as effective as anticipated in providing feedback on content and text organisation for this particular task. Nevertheless, participants reported that they found the tool helpful for improving grammar, vocabulary, and spelling in their texts.