Speaker
Description
AI-generated feedback provides immediate and scalable support for writing development. Nonetheless, the effectiveness of this support depends on students’ ability to interpret assessment criteria, exercise evaluative judgment, and translate feedback into meaningful revision. Furthermore, there is little evidence on whether integrating AI-generated feedback and co-construction of rubrics can enhance students’ learning engagement and writing performance in e-portfolio writing. Thus, this study investigates the impact of an integrated intervention combining AI-generated feedback and rubric co-construction on university students’ learning engagement and writing performance in e-portfolio-based academic writing courses. The study will employ an explanatory sequential mixed-methods quasi-experimental design with undergraduate EFL students. Both groups will receive equivalent opportunities for feedback and revision and use the same e-portfolio platform throughout the intervention. The experimental group will co-construct an analytic writing rubric with the instructor and use the negotiated criteria to generate, evaluate, and act on AI-generated feedback over several writing cycles. The active comparison group will receive a rubric developed by the instructor and conventional instructor feedback, following the same task sequence and revision schedule. Quantitative data will include pre- and post-intervention writing scores rated by trained independent raters, validated measures of learning engagement, and e-portfolio trace data on revision frequency and feedback uptake. Thematic analysis will be conducted on qualitative data from semi-structured interviews, reflective entries, and revision histories to explain how students in both groups understand, evaluate, and act on the feedback they receive. The integration of quantitative and qualitative findings will provide insights into how the integrated intervention influences students’ learning engagement and writing development, while identifying the conditions that support their critical evaluation and effective use of feedback in e-portfolio writing.
Keywords: AI-generated feedback, rubric co-construction, student engagement, e-portfolio writing, EFL academic writing.
