School of Languages at XJTLU Conference 2024

Engaging students effectively with feedback remains a significant concern in educational settings, supported by research that shows students often fail to act on feedback or consistently repeat the same errors in subsequent tasks (Lee, 2008; Zimbardi et al., 2017). Winstone et al. (2017) identify key barriers contributing to this issue, including challenges such as difficulty decoding feedback, lacking knowledge about effective strategies, experiencing a sense of disempowerment, and struggling with the translation of feedback into actionable steps.

In light of these challenges, Generative Artificial Intelligence (GAI) emerges as a promising solution, offering well-documented advantages. These include real-time interaction and feedback, personalized language instruction, an extensive knowledge base, natural language processing capabilities, and the ability to generate human-like responses. Leveraging GAI holds the potential to assist students in overcoming barriers to feedback engagement, fostering a proactive and empowered student response to feedback in educational settings.

Our research intends to investigate the influence of generative Artificial Intelligence (GAI) on enhancing students' engagement with feedback in English for Academic Purposes (EAP) writing coursework. The study focuses on two EAP modules, one from the first year and another from the second year, where traditional feedback, delivered via a checklist, was supplemented by the use of GAI tools, Xipu AI, in particular. Students were tasked with utilizing GAI to comprehend the feedback provided by their teachers and subsequently revise their writing. The research used questionnaires and interviews to gather students' perceptions of the integrated approach, evaluating their perspectives across three dimensions: behavior, cognition, and affection. Additionally, the research seeks to compare whether Year 1 and Year 2 students have different perceptions of this integrated approach. The comparison explores variations in GAI-enhanced feedback engagement effectiveness based on students' academic maturity and EAP curriculum familiarity, providing insights into the nuanced dynamics across academic levels.