SACM - United Kingdom
Permanent URI for this collectionhttps://drepo.sdl.edu.sa/handle/20.500.14154/9667
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Item Restricted A Proposed Model of Automated, Peer, and Teacher (APT) Feedback and Its Impact on L2 Learners’ Engagement and Writing Performance Changes Over Time.(University of Southampton, 2024-12) Alsharif, Seham; Şahan, ÖzgürEnhancing the quality of teacher feedback to students' work is a challenge in L2 writing contexts, especially in Asian educational settings. L2 teachers generally have numerous responsibilities and might not have sufficient time to give focused feedback on content. This, in turn, might prevent substantial progress in L2 writing. A novel approach has the potential to solve this particular issue by combining various sources of feedback. In this context, Automated Writing Evaluation (AWE) tools can ensure accuracy, while peer feedback can address various aspects of accuracy and content. This approach frees up teachers to concentrate more on the content and ideas. Such a model, which incorporates automated, peer, and teacher feedback (APT), not only enhances writing improvement at both the surface and meaning levels, but also increases the engagement of L2 learners. This is because it goes beyond traditional feedback techniques that stretch outside the conventional red-pen corrections, fostering a far more enriching and supportive learning environment. By following a mixed-methods design utilising students’ essay writing drafts, pre-test and post-test, observation notes, focus groups, reflective journals, and post-study questionnaire, the integrated data findings suggested the following. First, the APT has decreased the feedback items/errors the students produce in their essays over time. Moreover, they become able to make longer essays with fewer errors. In addition, the APT collaboration work on L2 students’ essays was relatively successful. Although every source overlapped a little with the other at the beginning, over time, every source acted uniquely complementing the other and providing a comprehensive model for improving the L2 writing. This improvement would not be possible if the students were not engaged. Despite some influencing factors that affect certain students’ engagement with the model, the findings showed that the use of three sources facilitated a positive behavioural, cognitive, and affective engagement gradually in the L2 writing context.21 0Item Restricted Exploring the Efficacy of ChatGPT Feedback in L2 Writing: Perspectives from Teachers and Students(Lancaster University, 2024) Alamri, Tahani; Lo, JustinThe emergence of user-friendly, widely accessible generative AI tools like ChatGPT has sparked widespread interest in academia. As students increasingly turn to these tools for various tasks, educational institutions have adopted different policies, from complete bans to active exploration of their potential applications. One frequently proposed application in recent research is using these tools to provide written corrective feedback on students' writing. This dissertation investigates the efficacy of ChatGPT feedback and the potential of AI tools in L2 writing instruction through the perspectives of L2 teachers and students. The aim is to contribute to the current understanding of AI and how it could potentially benefit or hinder L2 writing instruction, as well as determine the optimal approach for incorporating this tool. To achieve this, two online questionnaires were utilized, one targeting teachers and one for students. Participants evaluated samples of GPT feedback on a 5-criteria scale and shared their insights about the potential role of GPT in writing instruction in addition to the potential benefits and concerns. The findings showed that teachers and students generally viewed GPT feedback favorably. However, they acknowledged the limitations of AI feedback and the potential challenges AI systems might create if misused. Therefore, the majority opted for a balanced approach between teacher and AI feedback for maximized benefits and reducing risks.44 0