Student engagement with automated feedback on academic writing: a study on Uyghur ethnic minority students in China

Aided by big-data technology and artificial intelligence, automated writing evaluation (AWE) systems aim to help students engage in self-regulated learning and improve their academic writing in the digital era. While much research on student engagement with AWE systems has been conducted in mainstream classrooms, little attention has been paid to ethnic minority students who have different educational experiences and sociocultural backgrounds. This study investigates how a group of ethnic minority students from Xinjiang Uyghur Autonomous Region engaged with an AWE system in academic writing during an 18-week semester at a comprehensive Chinese university. Data were collected from multiple sources including student multiple-draft assignments, AWE feedback, and retrospective interviews with the students. The participants were found to engage with the AWE system behaviourally, cognitively, and affectively in their writing and revision, but the extent to which they engaged in the process is influenced by their multilingual proficiency, familiarity with digital technologies, learning beliefs and sociocultural identities. Those who were more actively engaged and obtained more learning gains tended to capitalise on their linguistic and cultural capital in their engagement with AWE feedback in their writing. The article concludes with educational implications for ethnic minority students in higher education.